Active Management of Distribtion Networks.pdf

7/28/2019 Active Management of Distribtion Networks.pdf

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Project Title

Integration of operation of embedded

generation and distribution networks

K/EL/00262/REP

URN 02/1145

Final Report

Prof. Goran Strbac (UMIST)

Prof. Nick Jenkins (UMIST)

Martin Hird (UMIST/Econnect)

Predrag Djapic (UMIST)

Guy Nicholson (Econnect)

MANCHESTERCENTRE FORELECTRICAL ENERGY

Department of Electrical Engineering &Electronics

PO Box 88, Manchester, M60 1QD

May 2002


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Integrated operation of embedded generation and distribution networks

Page 2 of 95 UMIST, 2002


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CONTENT

Page number

Executive summary........................................................................................................4

1. Control Strategies for Close Integration of Embedded Generation and

Distribution Networks..................................................................................................10

1.1. Background .............................................................................................................10

1.2. From Passive to Active Distribution Networks..........................................................12

1.3. Active Management of Voltage Rise Effect in Rural Areas.........................................17

1.4. Qualitative Analysis of Options for Control of Voltage Rise Effect..............................19

1.4.1 Worst Case Scenario (Minimum Load Maximum Generation) Approach...........20

1.4.2 Managing the voltage rise effect by generation curtailment..................................21

1.4.3 Managing the voltage rise effect by reactive compensation.................................22

1.4.4 Managing the voltage rise effect using coordinated voltage control.....................22

1.5. Application to a characteristic situation................................................................ ......23

2. Distribution Management System for Close Integration of Embedded

Generation and Distribution Networks.......................................................................28

2.1. Introduction..............................................................................................................28

2.2. Design of a Distribution Management System Controller............................................29

2.2.1 Outline of Operation.........................................................................................29

2.2.2 Network..........................................................................................................30

2.2.3 Hardware Configurations..................................................................................32

2.2.4 Communications...............................................................................................36

2.2.5 Software..........................................................................................................37

2.3. State Estimation........................................................................................................39

2.3.1 Background - Transmission State Estimation.....................................................39

2.3.2 Distribution State Estimation.............................................................................40


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2.3.3 A Distribution State Estimator...........................................................................41

2.4. Control Scheduling...................................................................................................45

2.4.1 Priority List......................................................................................................46

2.4.2 Optimal Power Flow........................................................................................47

2.5. Implementation.........................................................................................................50

3. Quantifying the Benefits of Active Management of Distribution Networks .............54

3.1. Introduction..............................................................................................................54

3.2. Case Studies ............................................................................................................56

3.2.1 Description of the System.................................................................................56

3.2.2 Base Case Scenarios........................................................................................58

3.2.3 Tool for Modelling the Operation of an Active Distribution System....................58

3.2.4 Generation Curtailment.....................................................................................60

3.2.5 Reactive Compensation and Voltage Control....................................................65

3.2.6 Area Based Voltage Control by OLTC ............................................................66

3.2.7 Area Based Voltage Control by OLTC and Voltage Regulator..........................68

3.2.8 Impact of Voltage Controls on Losses................................ ..............................70

4. Commercial Arrangements to Support Active Management.....................................73

4.1. Background.............................................................................................................73

4.2. Voltage Rise Effect and Connection Costs ................................................................74

4.3. Problems with Present Arrangements........................................................................75

4.4. Cost Benefit Analysis of Implementing Active Management of Distribution

Networks.................................................................................................................78

4.5. Commercial Arrangements for Active Distribution Networks .....................................82

4.6. Unbundling of Distribution Network Services ............................................................83

5. Conclusions ...................................................................................................................89

6. References....................................................................................................................93


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Executive summary

Rural distribution systems in which embedded generation is connected are susceptible to voltage

rise. In order to minimise the overall effect of embedded generation, network operators prefer

to connect embedded generation to higher voltages where their impact onto voltage profile is

minimal. However, the commercial viability of embedded generation projects is sensitive to

connection costs. These costs increase considerably with the voltage level at which the

embedded generation is connected; generally the higher the voltage or sparser the network, the

higher the connection cost. The developers of embedded generation therefore generally prefer

to connect at lower voltages. The amount of generation that can be connected is usually

established through deterministic load flow studies, usually with the critical case representing

conditions of minimum/maximum load and maximum embedded generation output. This

operating policy limits considerably the capacity of generation that can be connected to the

existing distribution network.

In this context, this project assesses the potential benefits of changing the operation philosophy

of distribution network and embedded generation from passive to active management. This

report deals with voltage control aspect of active management while issues associated with fault

levels are not considered.

The following four main control strategies are quantified:

(i) Active power generation curtailment: The developer of embedded generation schemes

may find it profitable to curtail some of the output for a limited period if allowed to

connect greater generator capacity. This may be particularly attractive if the probability of

the coincidence of high generation output with low network load condition is low.


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(ii) Reactive power management: Absorbing reactive power can be very beneficial in

controlling the voltage rise effect, especially in weak overhead networks with embedded

generation. By absorbing reactive power, an increase of the output of active power can

be realised.

(iii) Area based coordinated voltage control of On Load Tap Changing Transformers

(OLTCs): The present voltage control in distribution networks is primarily carried out by

OLTCs. Clearly, the voltage rise effect in distribution networks with embedded

generation can therefore be controlled by OLTCs (by reducing the voltage at times of

high generation output). However, the present voltage control policy is designed for

passive networks with strictly unidirectional power flows. Alternative voltage control

practices that go beyond the present local voltage control, such as an area-based control

of OLTC are considered in this study and the benefits of such policies quantified. The

studies performed in this study show that this form of control is likely to bring the largest

benefits in terms of the increase of embedded generation that can be connected to weak

distribution networks.

(iv) Application of voltage regulators: In the context of the voltage rise effect, minimum

load - maximum generation conditions are usually critical for the amount of generation that

can be connected. However, it may also be necessary to consider maximum load

maximum generation conditions. This is because, the use of OLTC transformers to reduce

the voltage on the feeder where the generator is connected, may produce an

unacceptably low voltage on adjacent feeders that supply load. In this case it may be

beneficial to separate the control of voltage on feeders which supply load, from the

control of voltage on feeder to which the generator is connected. This can be achieved by

the application of voltage regulators on appropriate feeders.

The benefits of an active management of distribution network, exercised through the above

alternative control strategies, are quantified by the volume of the annual energy and


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corresponding revenue that can be generated for various capacities of embedded (wind)

generation installed. This analysis is carried out on a characteristic 33 kV network that exhibits

all the phenomena of interest.

The studies performed clearly show significant benefits of active control of distribution network.

The most beneficial are schemes with area based voltage control by OLTCs and voltage

regulators achieving a 3 fold increase in the capacity of embedded generation that can be

connected.

The report also discusses how this control might be achieved and also maps out a possible

implementation path so that the concepts proposed can begin to be implemented quickly. The

outline design of a Distribution Management System (DMS) controller suitable for embedded

generation is discussed. Five hardware configurations are proposed of increasing complexity.

The simplest relies merely on local measurements at the 33/11kV substation while the most

complex proposes a hierarchical arrangement of DMS controllers. Although the first,

straightforward approach is conceptually simple, it is likely to give considerable improvements in

the capacity of embedded generation that may be connected.

The overall concept for the controller software is then discussed with the two major elements:

state estimation and control scheduling. Although state estimation techniques are well developed

for transmission networks these approaches are not directly transferable to distribution systems

with embedded generation. The basis of state estimation is explained and then the further work

that is required to adapt existing techniques to dealing with the limited number of measurements

available on distribution networks and the use of load data to provide pseudo-measurements is

outlined.

Two approaches have been identified for control scheduling. A priority-list, rule-based

approach may be applied whereby engineering judgement and knowledge of various contracts


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is used to determine the order in which various controls should be adjusted. This approach is

attractive for an early implementation of a simple system, as it is conceptually straightforward

and transparent to practicing engineers. For more complex implementations it may be preferable

to consider using an optimal power flow to optimise the control rigorously.

Furthermore, a possible implementation route is discussed given the present constraints on

distribution network operates and generators. Initially, simple implementations are proposed

with the embedded generator under local control and the controller operating on the Automatic

Voltage controller (AVC) at the 33/11 kV transformer.

The presence of embedded generation in distribution systems alters radically the way these

networks should be viewed not only from technical but also from a commercial vantage point.

With the introduction of embedded generation, distribution networks are expected to offer an

non-discriminatory open access to the networks and facilitate competition in the generation and

supply sectors. This requirement introduces a new role for distribution networks. Distribution

network operators now are required to provide network services to generators and to enable

them to take part in provision of such services.

Under the present regulatory framework Distribution Network Operators (DNOs) do not have

any incentive to connect generation and offer active management services to reduce the

connection costs and increase the amount of embedded generation that can be connected. In

this report, costs and benefits of active management of distribution networks are identified and

discussed. This is necessary for the development of appropriate commercial incentives for

DNOs. Furthermore, the report discusses a number of issues associated with present

commercial arrangements, particularly in relation to pricing that may impact an reactive power

based voltage control.


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A market based exchange of services between distribution network operators and embedded

generators (and other network users in general) is proposed and discussed.

This would require unbundling of distribution network services and enabling users to contribute

to the major responsibilities of DNOs (i) voltage and (ii) service quality management. As a

consequence of the historical development of distribution systems, these objectives have been

traditionally met by employing the operational and development practices that involved the use of

assets, facilities and resources owned and managed by DNOs. In this traditional approach

embedded generation is effectively excluded from the opportunity to support DNOs in carrying

out their main duties and also from receiving enhanced services from DNOs which would

provide more choice in connection (active management).

The new role of distribution networks requires unbundling of distribution network services and

the development of commercial arrangements within which DNOs would carry out their

responsibilities at least cost and efficiently, by using services from a number of potential

providers. Under this scenario DNOs would maintain the responsibility of managing all

components of service quality, but the means of achieving this objective would involve not only

distribution network facilities. It would also make use of the inputs provided by embedded

generation, and more generally, by demand-side management, storage facilities, reactive

compensation facilities including an active interchange of services between the DNOs and the

TNO on the distribution-transmission boundary. In the context of embedded generation, this

concept could open the possibility for generators to provide DNOs with network support

(substitute for network capacity), with voltage regulation and contribute to service quality. On

the other hand, DNOs could offer enhanced network services to generators, such as active

distribution management and enable them to control their connection costs. The value of various

services provided by and to DNOs could be determined on a market basis.


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1. Control Strategies for Close Integration of Embedded

Generation and Distribution Networks

1.1. Background

The UK Government is working towards a target of renewable energy providing 10% of UK

electricity supplies by 2010 with 10GW of CHP by the same date. Depending on the load

factor assumed, this will require the installation of up to 14 GW of generation capacity on to

distribution networks (i.e. at voltages of 132 kV and below). Renewable generation will benefit

considerably from the Renewables Obligation that rewards green energy through a mechanism

of Renewables Obligation Certificates [1]. However, under the present conditions the owners

and operators of the distribution networks, the Distribution Network Operators (DNOs)

anticipate that they can integrate only a much more limited capacity of generation [2] without a

major reinforcement.

The environment in which distribution companies function creates a number of interrelated

regulatory, commercial and technical questions that need addressing in order to facilitate thisgrowth in small-scale generation. This reflects

(i) the historic function of the distribution network, that has been primarily viewed as a

transport provider, rather than in the role of a facilitator of competition in the generation

and supply sectors, and


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(ii) the historic passive configuration of the distribution system, in which the expectation is

that virtually all the electricity is supplied from the transmission networks at several

points in each DNOs area and is then distributed to consumers at lower voltages.

An open access based framework for distribution networks clearly needs to be developed. The

Utilities Act 2000 requires DNOs to facilitate competition, which is effectively a vehicle for

opening up distribution networks and for providing equitable access to the energy market. In

order to take full advantage of this opportunity an adequate regulatory and commercial

environment needs to be developed and a number of technical issues related to network

operation and development resolved, as documented in the Report of the OFGEM/DTI

Embedded Generation Working Group [4]. The report recognises that at present there are

neither commercial nor technical frameworks to encourage the DNOs to integrate this

embedded generation (EG) into their systems in an optimal manner.

The overall problem can be viewed as a conflict between two regulatory systems: the aggressive

economic regulation of the UK power industry, which is dominated by relatively short-term

issues of economic efficiency, and the environmental which aims to establish incentives for small-

scale, less carbon intensive technologies in pursuit of climate change objectives. It may be seen

that a high penetration of embedded generation, which is essential if renewable energy sources

and CHP are to be introduced to meet government targets, represents a paradigm shift in the

UK electricity system.

Specifically, this work is centred around an analysis of the benefits that can be derived from

changing the operation philosophy of distribution networks from passive to active. The emphasis

is on the design of control strategies of active distribution systems that would enhance the ability

of the existing networks to accommodate additional embedded generation.


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In this section the fundamental features of passive distribution networks are examined and their

inability to accommodate increased amounts embedded generation discussed. It is

demonstrated how the voltage rise effect, the main limiting factor in rural areas, can be

effectively controlled within an active network environment, and as a result, enable considerably

higher levels of penetration of embedded generation into existing systems. The following three

main control strategies are then elaborated in some detail:

(i) Active power generation curtailment

(ii) Reactive power management

(iii) Area based coordinated voltage control

(iv) Application of voltage regulators

Qualitative analysis of these alternatives is then carried out on a simplistic distribution network

model where the effect of these controls can be easily understood.

The ability of active networks to accommodate embedded generation is illustrated on a

characteristic case study of connecting a wind farm to a weak distribution network. It is shown

that through reactive power management or coordinated voltage control the amount of

embedded generation that can be connected to the existing system can be increased for a factor

of 3, in comparison with passive networks.

1.2. From Passive to Active Distribution Networks

Modern distribution systems were designed to accept bulk power from the transmission

network and to distribute it to customers. Thus the flow of both real power (P) and reactive

power (Q) was always from the higher to the lower voltage levels. This is shown schematically


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in Figure 1.1 and, even with interconnected distribution systems, the behaviour of the network is

well understood and the procedures for both design and operation long established.

Load

P,Q P,Q

Figure 1.1 - Conventional distribution network deign and operation

However, with significant penetration of embedded generation the power flows may become

reversed and the distribution network is no longer a passive circuit supplying loads but an active

system with power flows and voltages determined by the generation as well as the loads. This is

shown schematically in Figure 1.2. For example, the CHP generation scheme with the

synchronous generator (S) will export real power when the electrical load of the premises falls

below the output of the generator but may absorb or export reactive power depending on the

setting of the excitation system of the generator. The wind turbine will export real power but is

likely to absorb reactive power as its induction (sometimes known as asynchronous) generator

(A) requires a source of reactive power to operate. The voltage source converter of the

photovoltaic (pv) system will allow export of real power at a set power factor but may

introduce harmonic currents, indicated as in Figure 1.2. Thus the power flows through the

circuits may be in either direction depending on the relative magnitudes of the real and reactive

network loads compared to the generator outputs and any losses in the network.


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P,Q? P,Q?

A

P,-Q

CHP S

pv

P+/-QP,+/-QIn

Figure 1.2 - Ad-hoc approach with existing operation practice

The change in real and reactive power flows caused by embedded generation has important

technical and economic implications for the power system. To date, most attention has been

paid to the immediate technical issues of connecting and operating generation on a distribution

system and most countries have developed standards and practices to deal with these. In

general, the approach adopted has been to ensure that any embedded generation does not

reduce the quality of supply offered to other customers and to consider the generators as

negative load. No real attempt has been made to consider how the overall performance of a

distribution system with a significant penetration of embedded generation may be optimised.

Clearly, a number of difficulties, following from the different objectives of the generator and

network operator, can be identified immediately. At present in the UK networks, the objective

of the generator is to supply the maximum energy (kWh) to the network and so receive the

largest payment. The objective of the DNO is to maintain supply to all customers, the majority

of whom will be load customers. As the network operator has no control over the embedded

generator all decisions concerning the network must be made considering the worst possible

conditions of the generation for any set of network conditions. Hence at minimum (or even zero)

load the maximum generation is assumed and at maximum load, minimum generation is assumed.

In summary, there is no mechanism where the overall distribution network and embedded

generation system can be optimised.


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Every DNO has an obligation to supply its customers at a voltage within specified limits. This

requirement often determines the design and expense of the distribution circuits and so, over the

years, techniques have been developed to make the maximum use of distribution circuits to

supply customers within the required voltages. For example, it is well known that the ratio of the

MV/LV transformer is usually adjusted so that at times of maximum load the most remote

customer receives acceptable voltage. During minimum load the voltage received by all

customers is just below the maximum allowed. If an embedded generator is now connected to

the end of such a circuit then the flows in the circuit will change and hence the voltage profiles.

The most onerous case is likely to be when the customer load on the network is at a minimum

and the output of the embedded generator must flow back to the source.

In some cases, the voltage rise can be limited by reversing the flow of reactive power (Q) either

by using an induction generator or by under-exciting a synchronous machine and operating at

leading power factor. This can be effective on higher voltage overhead circuits, which tend to

have a higher X/R ratio. However, on LV cable distribution circuits the dominant effect is that of

the real power (P) and the network resistance (R) and so only very small embedded generators

may generally be connected to LV networks.

Some DNOs use more sophisticated control of on-load tap changers of the HV/MV

distribution transformers including the use of a current signal compounding the voltage

measurement. One technique is that of line drop compensation and as this relies on an assumed

power factor of the load, the introduction of embedded generation and the subsequent change in

power factor may lead to greater uncertainty in operation if the embedded generator is large

compared to the customer load.

As the present network operation philosophy is known to considerably limit the amount of

embedded generation that can be connected, the focus of this particular piece of work is on

quantifying the benefits of the integration of embedded generation into distribution network


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operation in terms of the increased ability of the networks to accommodate embedded

generation. This integration effectively changes the conventional doctrine of the operation of

distribution networks from passive to active and this work carries out a conceptual analysis of

the operation of such active networks. Various degrees of integration are possible, ranging from

a simple local based control of generation to a coordinated control between distribution and

generation facilities over interconnected distribution circuits. This co-ordinated, system level

voltage and flow control could be based on a controller that allows this integrated operation to

be implemented.

The controls may be implemented either using central Distribution Management System

controllers, such as one depicted in Figure 1.3 (say one for each 33/11 kV substation), or by

distributing the control functions among the various controllers associated with each item of plant

(i.e. generators, tap-changers). However this choice is largely an issue of implementation only as

the control philosophy proposed accepts the requirement for communication between the

various items of plant. The control actions required are slow (e.g. change of tap-changer set-

point or generator despatch) and so low cost, slow, communications systems will be

appropriate. The overall control system will be arranged in a hierarchy with the controllers of the

33/11 kV substations communicating upwards to similar equipment in 132/33 kV substations

etc. Particular attention must be paid to the consequences of failure of the communications

systems and how the system then reverts to a safe state.


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A

P,-Q

CHP S

pv

P+/-Q

P,+/-Q

DMSController

P,Q,V, P,Q,V,

P,Q,V,

DMS Controller inputs-Network flows and voltages (P, Q, V)-Contracts for constraining on and off

generation;

DMS controller outputs:Tap positions and generator dispatch

(P , Q)

Figure 1.3 - Active distribution network operation

As indicated earlier, the degree of integration can vary from a simple local based control of

generation to a coordinated control between distribution and generation facilities over

interconnected distribution circuits.

1.3. Active Management of Voltage Rise Effect in Rural Areas

Connections of embedded generation in ruraldistribution systems are susceptible to voltage

rise. Current operating policy based on passive operation of distribution network limits the

capacity of generation connected based on the extreme condition of minimum load, maximum

generation. In order to minimise the overall effect of embedded generation network operatorsprefer to connect embedded generation at higher voltages where their impact onto voltage levels

is minimal. However, the commercial viability of embedded generation projects is sensitive to

connection costs. These costs increase considerably with the voltage level at which the

embedded generation is connected; generally the higher the voltage or sparser the network, the

higher the cost. The developers of embedded generation therefore prefer to connect at lower

voltages. This conflict of objectives between embedded generation developers and network


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operators is usually settled through simple deterministic load flow studies, usually based on one

critical case representing conditions of minimum load and maximum embedded generation

output.

As this will demonstrate, an active distribution network will allow considerably greater

penetration of embedded generation. Three alternative control strategies are evaluated1:

(a) Active power generation curtailment (shedding) can be used as a means of reducing the

voltage rise effect. The generator may find it profitable to curtail some of its output for a

limited period if allowed to connect a larger capacity. This may be particularly suitable for

embedded generation, as the generation curtailment is likely to be required during times of

relatively low value of energy (such as summer nights). This mode of control is local and,

generally, there is no need for communication system.

(b) Secondly, absorbing reactive power can be beneficial to controlling voltage rise effect,

especially in weak overhead networks with embedded generation. This mode of control is

also local and, generally, there is no need for communication system. In this respect, the use

of a reactive compensation facility, such as a STATCOM, at the connection point is

discussed in [3]. However, reactive power management as a means of increasing the

penetration of embedded generation has not been widely applied in the UK. Within this

work an advanced optimal power flow method will be applied to illustrate the potential of

reactive power management in the context of managing voltage rise-effect.

(c) Thirdly, the introduction of a co-ordinated voltage control policy may be beneficial from the

embedded generation penetration levels point of view. Present voltage control in

1Application of voltage regulators is elaborated in Section 3 of the report


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distribution networks is primarily carried out by On Load Tap Changing-transformers

(OLTC). Voltage control is usually based on a simple constant voltage policy or a scheme

that takes into account circuit loading while determining the voltage that should be

maintained. It is important to bear in mind that this voltage control policy was designed for

passive networks with strictly unidirectional power flows. In active distribution networks

with multi-directional power flows, the validity of this local control voltage practice becomes

inherently inadequate. In fact, this practice limits the degree of openness and accessibility of

distribution networks and therefore has a considerable adverse impact on the amount of

generation that can be accommodated. On the other hand, alternative voltage control

practices that go beyond the present local voltage control, such as an area-based control of

OLTC will be considered and the benefits of such policies quantified. This coordinated

control would be accompanied with an adequate communication system and measurements

from a number of points along the feeder.

(d) Finally, application of voltage regulators may be very beneficial for decoupling voltage

control on feeders supplying loads from feeders to which generation is connected.This is

useful when it is necessary to consider maximum load maximum generation conditions.

This is because, the use of OLTC transformers to reduce the voltage on the feeder where

the generator is connected, may produce an unacceptably low voltage on adjacent feeders

that supply load. In this case it may be beneficial to separate the control of voltage on

feeders which supply load, from the control of voltage on feeder to which the generator is

connected. This can be achieved by the application of voltage regulators on appropriate

feeders.

1.4. Qualitative Analysis of Options for Control of Voltage Rise Effect

The voltage rise effect is illustrated using a simple circuit shown in Figure 1.4. This figure

represents the basic features of a distribution system into which an embedded generator, G, is

connected (assumed at 11kV). This generator (PG, QG) together with a local load (PL, QL) and


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a reactive compensator (QC) is connected to the distribution system (DS) via a weak rural

distribution overhead line with impedance Z and, say a 33/11 kV transformer with an On Load

Tap Changer (OLTC).

QC

PGG

Q Comp

PL, QL

QG

Z=R + jX

1

2

OLTC

DS

Figure 1.4 - Simple system for modelling voltage rise

The voltage at busbar 2 (V2) can be approximately calculated as follows:

X)QQQ()PP(RVV CLGLG12++

(1)

This simple equation can be used to qualitatively analyse the relationship between voltage at

busbar 2 and the amount of generation that can be connected to distribution network, as well as

the impact of alternative control actions.

1.4.1 Worst Case Scenario (Minimum Load Maximum Generation) Approach

As discussed above, the capacity of generation that can be connected to a distribution circuit

determined by analysing the extreme conditions of the coincidence of minimum load (PL= 0, QL

= 0) and maximum generation (PG = PGMAX). This policy enables DNOs to continue to operate

their systems as if generators were not connected at all. The effect of such connection policy on

the amount of generation that can be connected to existing system can be analysed by the


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following expression (for the simplicity sake unity power factor operation is assumed, i.e.

QGQC=0):

max

G12 PRVV + (2)

The capacity of the generator that can be accommodated in the existing system is clearly limited

by the maximum voltage at busbar 2:

R

VVP 1

max

2max

G

(3)

It is important to observe that the real part of the network impedance, R, is critical for the

amount of generation that can be connected (as the value of reactance, X, is not relevant as the

generator is assumed to operate with a unity power factor). This resistance is determined by

conductor size and is assumed constant for a given system.

1.4.2 Managing the voltage rise effect by generation curtailment

It is important to observe that the probability of such extreme situation (coincidence of minimum

load with maximum generation) actually occurring is generally low, and hence it may be

beneficial to accommodate a larger generator at busbar 2 and curtail it when voltage at busbar 2

rises to that of the limit. The effect of generation curtailment on the capacity that can be

connected is given by the equation below.

R

VVPP 1

max

2cur

G

max

g

+ (4)

The likelihood of the coincidence of minimum load with maximum generation will determine the

total annual energy curtailed. As the price of electricity is primarily driven by load demand, and


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generation curtailment occurs typically during periods of low load, the value of this energy

curtailed is likely to be relatively low.

1.4.3 Managing the voltage rise effect by reactive compensation

Managing of reactive power injections can make a considerable impact on the capacity of

generation that can be connected to weak overhead distribution networks. If reactive power,

Qimport (i.e. ( )CLG QQQ ), is absorbed from the network, the amount of generation that

can be connected under no load conditions can be increased:

R

XQ

R

)VV(P

import1

max

2max

G+

(5)

Observe that the effectiveness of reactive power import is greatly influenced by the value of line

reactance X. In this context, reactive compensation is considerably more effective on overhead

networks (with typical reactance of]km/[4.0XOH

), than on cable networks (with typical

reactance of ]km/[1.0XC ). It is also important to bear in mind that absorbing reactive

power would lead to an increase in losses, and the evaluation of this control option should

therefore include loss assessment.

1.4.4 Managing the voltage rise effect using coordinated voltage control

Control of voltage at busbar 2 by regulating voltage V1, at busbar 1, using the OLTC, can

considerably increase the capacity of embedded generation. In this control option, the OLTC is

used to lower voltage to the minimum value min1V , enabling larger injection of active power at

busbar 2:


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R

VV

P

min

1

max

2max

G

(6)

However, in a more complex network, the value of this voltage, and the corresponding tap

position of the OLTC, would have to be optimised.

All these three methods of regulating voltage can be applied in combination. It should also be

noted that reinforcing the system could also enhance the amount of generation that can be

accommodated. This is however out of scope of this study that is focused on voltage regulation

in the existing system.

1.5. Application to a characteristic situation

In order to illustrate the limitation of passive distribution network operating philosophy and the

benefits of active control of distribution systems arising from the management of the rise effect

(and hence connection cost), a weak 20 kV distribution network to which a wind farm is to be

connected is considered (Figure 1.5). Network and load parameters are given in Table 1.1 and

Table 1.2. Induction generators with power factor correction capacitors are considered for the

operation of the wind farm. The combined active-reactive characteristic of the group of

generators (without power factor correction) to be used is given in Figure 1.6. The size of the

fixed power factor correction used is 3 MVAr. Voltage at busbar 2 is held at 1.03 p.u. by the

transformer tap changer.

High and low loading conditions as two characteristic snap shot situations are analysed.

Minimum demand is set to be at 10% of the peak.

Table 1.1. Circuit data

Line Records


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From

Number

To Number R(p.u.) X(p.u.)

2 1 0.01869 0.17726

2 3 0.03100 0.40174

2 5 0.33290 0.58310

3 4 0.09000 0.15770

3 5 0.64460 0.86000

5 6 0.23900 0.21040

6 7 0.24762 0.25132

1

1.00 pu

21.03 pu

3

1.01 pu

4

0.99 pu

51.00 pu

6

1.00 pu

7

1.00 pu

12.8 MW

12.8 MW12.1 MW12.0 MW

0.6 MW

0.6 MW

0.0 MW

0.0 MW0.0 MW0.0 MW

8.8 MW

8.6 MW

31.50 MW6.31 MVR

12.00 MW2.40 MVR

54 MW18 MVR

9.20 MW1.85 MVR

0.00 MW

53.7 MW

53.2 MW

2.97 MVR0.00 MVR

3.00 MVR

2.6 MVR-2.4 MVR

0.0 MVR-0.0 MVR

0.0 MVR

-0.0 MVR

1.2 MVR

-1.1 MVR

4.5 MVR

-3.8 MVR

-12.0 MVR

17.7 MVR

1.2 MVR

-0.7 MVR

Figure 1.5 - Seven-bus network

Table 1.2. Load data

Load Records

Busbar MW MVAr MVA

2 31.5 6.31 32.13


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4 12.0 2.40 12.24

5 9.2 1.85 9.387 0 3.00 3.00

Induction generator circle diagram (without pfc)

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60

Power export (MW)

ReactivePowerimport(MVAr)

Figure 1.6 - Induction generator circle diagram

Assuming that allowable voltage variation in the network are +/- 5%, three exercises are

performed:

(i) Passive network operation is simulated and the maximum amount of embedded

generation that can be connected to the network is determined. Both heavy and light

loading conditions are considered. By performing a number of load flow calculations it

can be concluded that 13.5 MW and 4.6 MW can be absorbed under heavy and light

loading conditions respectively.

(ii) Active distribution network operation is simulated with local control via a reactive

power compensation plant, installed at the point of connection. The case study


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demonstrates that absorbing reactive power can be very beneficial to controlling voltage

rise effect, and hence enable increased amount of embedded generation to be connected

to the existing system. Furthermore, the minimum size of the plant to allow various

amounts of generation to be connected is determined. It is important to observe changes

in active losses as shown in Table 1.3 (voltage at busbar 2 is held at 1.03 p.u.). The

compensation plant is modelled simplisticly as a synchronous condenser, which is

certainly adequate for this type of analysis.

Table 1.3

High loading conditions Low loading conditions

PG QG Q absorbed by

the compensator

Plosses Q absorbed by the

compensator

Plosses

(MW) (MVAr) (MVAr) (MW) (MVAr) (MW)

1.0 3.2 0 0.99 0 0.01

3.0 3.6 0 0.92 0 0.05

5.0 4.0 0 0.91 0.16 0.15

10.0 5.0 0 1.13 3.18 0.78

15.0 7.3 0.66 1.85 3.81 1.83

20.0 9.5 1.18 3.02 4.12 3.27

This table shows that, at the extreme, this network could accommodate 20.0MW, from the

voltage rise point of view, if a compensation of 4.12 MVArs (of reactive absorption) is installed.

Note that in this particular case losses would be more than 3MW under all load conditions.

When considering the economics of reactive compensation plant, the installation cost of thisreactive support will have to balance against the value of the increase in generation output taking

into account negative effects on system losses. This topic is discussed in Section 3.

(iii) In passive distribution networks voltage regulation is carried out by On Load Tap

Changing-transformers (OLTC). Voltage control is usually based on a simple constant

voltage policy. In active distribution networks with embedded generation and multi-


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directional power flows, the validity of this local control voltage practice may become

inadequate. This case study illustrates the benefit that a co-ordinated voltage control

including OLTC with respect to amount of embedded generation that can be connected

and the amount of reactive support required (Table 1.4 and 1.5). Thus, with busbar 2

maintained at 1.015 pu a 7 MW generator may be connected with no additional reactive

compensation. Reducing busbar 2 voltage to 1.pu increases this to almost 15 MW.

Table 1.4 - Set voltage at bus 2 V = 1.015 p.u.


PG QG Q absorbed by

the compensator


compensator

Plosses


1.0 3.2 0 1.00 0 0.01

3.0 3.6 0 0.94 0 0.06

5.0 4.0 0 0.93 0 0.15

10.0 5.0 0 1.17 1.47 0.68

15.0 7.3 0 1.84 2.18 1.67

20.0 9.5 0 2.91 2.56 3.07

Table 1.5 - Set voltage at bus 2 V = 1.00p.u.


PG QG Q absorbed by

the compensator


compensator

Plosses


1.0 3.2 0 1.02 0 0.01

3.0 3.6 0 0.95 0 0.06

5.0 4.0 0 0.95 0 0.1610.0 5.0 0 1.19 0 0.64

15.0 7.3 0 1.89 0.53 1.55

20.0 9.5 0 2.99 0.98 2.89

The exercises performed clearly show that a coordinated voltage control has a significant

potential for increasing the level of penetration of embedded generation to weak overhead

distribution networks.


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2. Distribution Management System for Close Integration of

Embedded Generation and Distribution Networks

2.1. Introduction

It has been shown in Section 1 that there is very considerable benefit in integrating the control of

embedded generation and the local distribution networks. This section discusses how this

control might be achieved and also maps out a possible implementation path so that the

concepts proposed can begin to be implemented quickly.

Firstly the outline design of a Distribution Management System (DMS) controller suitable for

embedded generation is discussed. Five hardware configurations are proposed of increasing

complexity. The simplest relies merely on local measurements at the 33/11kV substation while

the most complex proposes a hierarchical arrangement of DMS controllers. Although the first,

straightforward approach is conceptually simple, it is likely to give considerable improvements in

the capacity of embedded generation that may be connected.

The overall concept for the controller software is then discussed with the two major elements:

(1) state estimation and (2) control scheduling. Although state estimation techniques are well

developed for transmission networks these approaches are not directly transferable to

distribution systems with embedded generation. The basis of state estimation is explained and

then the further work that is required to adapt existing techniques to dealing with the limited


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number of measurements available on distribution networks and the use of load data to provide

pseudo-measurements is outlined.

Two approaches have been identified for control scheduling. A priority-list, rule-based

approach may be applied whereby engineering judgement and knowledge of ancillary services

contracts is used to determine the order in which various controls should be adjusted. This

approach is attractive for an early implementation of a simple system, as it is conceptually

straightforward and transparent to practicing engineers. For more complex implementations it

may be preferable to consider using an optimal power flow to optimise the control.

Finally, a possible implementation route is discussed given the present constraints on distribution

network operates and generators. Initially, simple implementations are proposed with the

embedded generator under local control and the controller operating on the AVC controller at

the 33/11 kV transformer.

2.2. Design of a Distribution Management System Controller

2.2.1 Outline of Operation

Conceptually, the DMS controller is located at the primary substation which is the lowest

voltage point on the network with an on load tap changer for voltage control although in practice

there is no reason why its capabilities cannot be distributed amongst other controllers. It has the

necessary data to provide a model of the local HV distribution network. At a set interval,

perhaps every half-hour, the DMS controller estimates the state of the part of the network that

is under its control. The estimate comprises the voltage at each bus of the network. To


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calculate the estimate, the DMS controller uses models of the loads connected to the network

and a minimum number of real-time measurements.

Using the state estimate, the DMS controller calculates control values and outputs these to

devices connected to network elements, such as on-load tap-changers and embedded

generators. The control values are calculated to optimise the power flow in that part of the

network.

If any real-time measurement changes significantly, the DMS controller calculates and outputs

new control values within a few seconds, to prevent infringement of, or reduce the probability

of, network constraints.

The DMS controller comprises software that runs on a hardware platform that is connected to

the electrical network. The main features of the electrical network and hardware platform are

described in the following sections. The software inputs and outputs are then briefly described.

A detailed description of the software is given in Sections 2.3 and 2.4.

2.2.2 Network

Figure 2.1 is a simplified schematic diagram of part of a distribution network. The primary

substation transformers are fitted with on-load tap-changers (OLTC) that are controlled by

automatic voltage control (AVC) relays. For the DMS controller to control the voltage at a

multi-transformer substation, as illustrated, the AVC relays are assumed to be operated in

master-follower configuration and the DMS controller controls the set point of the master. For a

single transformer substation, the DMS controller controls the set point of the single AVC relay.

The voltage at more than one substation can be controlled by different DMS controllers or by

communication from one controller.


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Several circuits are shown connected to the substation, each comprising several busbars

connected together by lines or cables. The DMS controller can re-configure the network, which

can be radial or meshed, by opening or closing circuit breakers.

Customer loads are connected to the buses. The DMS controller can control some loads by

disconnecting and reconnecting them.

Embedded generators are connected to several of the busbars. These have different types of

controller, depending upon the type of generator. The DMS controller controls the active and

reactive power export of embedded generators by sending control signals to their controllers.

Examples of control signals are: a set point for the automatic voltage regulator of a synchronous

generator, a set point for the governor of an engine, a signal to a wind farm supervisory control

and data acquisition (SCADA) system to stop a number of wind turbines in a wind farm or to

change the set point of the pitch angles in all wind turbines in a wind farm to a new maximum

output.

Measurements of voltage, current or power are taken at the substation bus bar and several

other busbars. These would typically be busbars to which generators are connected or at which

large voltage variations are expected. The DMS controller uses the minimum number of

measurements necessary to calculate a state estimate sufficiently accurate for satisfactory control

of the network.

Reactive power compensation devices, such as capacitor banks or static compensators may

also be connected to the network. The DMS controller controls these by, for instance,

connecting and disconnecting a capacitor bank.


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33 / 11 kV

Transformer

with On-line

Tap-changer

Measurement

Generator

KEY

11 kV / 230 V

Transformerwith low

voltage loads

Network bus

Network line

or cable

VAR

LOAD

Reactive

power

com ensator

VAR

Controllable

LoadLOAD

Circuit

breaker

3

2

1

Figure 2.1 - Schematic diagram of part of a distribution network

2.2.3 Hardware Configurations

Schematic diagrams of possible DMS controller hardware configurations are shown in Figures

2.2 and 2.3. Five different possibilities are shown, increasing in scale and complexity.


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Remote Terminal

Unit

Remote Terminal

Unit

Real-time

Microcomputer

Automatic Voltage

Control Relay

Local

measurements

Real-time

Microcomputer

Automatic Voltage

Control Relay

Local

measurements

Remote Terminal

Unit

Real-time

Microcomputer

Automatic Voltage

Control Relay

Local

measurements

Remote Terminal

Unit

1

2

3

Figure 2.2 - Schematic diagrams of simple DMS controller hardware configurations


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Remote Terminal

Unit

Remote Terminal

Unit

Real-time

Microcomputer

Automatic Voltage

Control Relays

Local

measurements

Remote Terminal

Unit

4

Embedded Generators

Loads, Compensators,

Circuit Breakers

5

DMS

Controller

DMS

Controller

DMS

Controller

DMS

Controller

DMS

Controller

DMS

Controller

DMS

Controller

Figure 2.3 - Schematic diagrams of more complex DMS controller hardware configurations

The three configurations shown in Figure 2.2 illustrate simple applications of the DMS

controller, which control only a single AVC relay. The DMS control software runs on the real-

time microcomputer and the output is a single set point value to an AVC relay. The computer

and relay are sited at a primary substation (e.g. 33/11kV). These two units are in each of the


35/95



three configurations; the difference between the configurations is the number and type of real-

time measurements that are provided as inputs to the software.

Configuration 1 is the simplest and uses only local substation measurements. Examples of these

are substation busbar voltage, total substation power, feeder power, total substation current and

feeder current. This configuration may provide workable control for a radial network with a

single embedded generator.

In configuration 2, local substation measurements are supplemented with network measurements

from a single remote terminal unit (RTU). The RTU is a partially intelligent device that has

monitoring, communications and some control functions. The RTU is sited at a key point on the

network, such as the busbar at which an embedded generator is connected or the bus at which

the largest voltage variations are expected. The RTU takes measurements at this point and

communicates them to the real-time microcomputer (DMS controller). Examples of network

measurements are bus voltage, load (or generator) power, feeder power, load (or generator)

current and feeder current. This configuration may be suitable for a radial network with a single

embedded generator for which configuration 1 provides insufficient data to allow workable

control.

Configuration 3 is the same as configuration 2, except that it has several RTUs. This

configuration may be suitable for a radial or meshed network with one or more embedded

generators.

Figure 2.3 shows two more complex configurations. These configurations control AVC relays,

embedded generators, loads, reactive power compensators and circuit breakers.

Configuration 4 uses local measurements and measurements from several RTUs, in the same

way as configuration 3. Configuration 4 controls many network devices, therefore it is likely that


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it will require a larger number of RTUs than configuration 3. Configuration 4 is suitable for

control of a re-configurable radial or meshed network with one or more substations, several

embedded generators, controllable loads and reactive power compensators.

Configuration 5 shows how the DMS controllers could be used in a hierarchical manner. Each

controller is as illustrated in configuration 4. At the lowest level, the four controllers would

typically be sited at primary substations or perhaps at a lower level at in-line voltage

regulators. The intermediate level controllers could be sited at medium voltage substations (bulk

supply points 132/33kV). The highest-level controller could be sited at a grid supply point

(e.g.400 or 275/132kV). Configuration 5 is suitable for control of part of a distribution network

that contains a large number of embedded generators and is supplied from a single grid supply

point.

2.2.4 Communications

For configuration 1 the real-time microcomputer, the local measurement device and the AVCrelay are directly connected to each other. In configurations 2 to 5, remote communications are

needed between the RTUs and the real-time computer. In configurations 4 and 5 remote

communications are additionally needed between the real-time computer and the devices

connected to the network.

Measurement data is communicated from an RTU to the real-time microcomputer once per

interval, say every half hour, or if there is a significant change in a measurement. The number of

data values communicated each time is typically less than five e.g. voltage magnitude, real power

and reactive power.

A control value is communicated from the real-time microcomputer to a controlled device when

a change in the device output is required. The number of data values communicated each time is


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typically one or two e.g. a set point for generator real power output and a set point for

generator power factor, or a binary value to open or close a breaker.

The choice of remote communications medium depends largely on the required speed of data

transfer. It is common for AVC devices to have an initial delay of 10 120 s between measuring

an over or under voltage and outputting a change tap signal to the OLTC. Once a change tap

signal has been output, some AVCs have a 5 60 s delay before outputting a second change

tap signal. These durations reflect present distribution network voltage control practice.

If the time between a significant real-time measurement change and a controlled device receiving

a new control value is no more than 5 s, then the DMS controller is operating in line with

present voltage control practice.

Two types of communication that permit this speed of data transfer are:

A public data network e.g. Vodafone Paknet, which gives call set-up times of less than

0.5 s.

Power line carrier.

2.2.5 Software

Figure 2.4 is a block diagram of the DMS controller software, showing its inputs and outputs.

The measurement input comprises the local and network measurements. The outputs are the

control values for the various devices under control. These are all real-time signals. The

remaining inputs are off-line data.


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The network data input comprises the network topology and electrical parameters. The pseudo

measurement input provides values for all un-measured quantities that are required for the state

estimator. This input is described in more detail in Section 2.3.

The constraints input comprises three types of constraint:

Primary plant constraints e.g. embedded generator capacity

Control limits e.g. OLTC maximum number of tap steps

Network constraints e.g. voltage limits

The contracts input comprises the details of ancillary service contracts between the distribution

network operator and owners of:

Embedded generators

Controllable loads

Reactive power compensators

The DMS controller software has two functional blocks: state estimation and control scheduling.

The state estimation block uses the network electrical parameters, network topology, load

models and real-time measurements to calculate a network state estimate. This is passed to the

control-scheduling block, which uses it to calculate a new set of control values for the devices

connected to the network. The set of control values optimises the power flow in the network,

while observing all the constraints and taking account of all the contracts.

State estimation and control scheduling are discussed in detail in Sections 2.3 and 2.4.


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StateEstimationMeasurements

NetworkData

Pseudomeasurements

Automatic voltagecontrol relays

EmbeddedGenerators

Contracts

EstimatesControl

Scheduling

Loads,Compensators,Circuit breakers

Constraints

Figure 2.4: Block diagram of DMS controller software

2.3. State Estimation

2.3.1 Background - Transmission State Estimation

A state vector is a set of variables that defines all the possible states of a system. Knowledge of

the state vector provides a basis for real-time control of the system. In the case of a power

system, the state variables are usually taken to be the voltage magnitude and relative phase angle

at each bus. These can be calculated using a load flow, given the system load and generation.

On a transmission network, the number of measurements is usually larger than the number of

state variables. The measurements contain errors and are therefore not necessarily the variables

required for load flow calculations. State estimation (SE) provides a means of utilising all

available measurements, taking account of the expected errors, to calculate the best estimate of


40/95



the state vector. SE is used widely in Energy Management Systems (EMS) as the basis for real-

time control of transmission networks.

2.3.2 Distribution State Estimation

State estimation has not been widely applied to distribution networks. The main reason for this

is that distribution networks have traditionally been operated as passive radial networks and so

there was little need to estimate their state accurately.

The level of automation in distribution networks has increased in recent years, drive n mainly by

a perceived need to improve the quality of supply. Distribution management systems (DMSs)

have been installed that can rapidly re-configure the network to restore customers supplies

following a fault. The recent growth in embedded generation presents new challenges to these

systems. Embedded generators are far from being integrated into distribution networks, meaning

that their full potential is not realised. For this to happen, DMSs need to incorporate the

generation scheduling features of EMSs. As SE is the basis for these EMS functions, work isrequired to transfer SE from transmission to distribution systems.

Some work on distribution state estimation (DSE) has been reported in the academic literature

in the 1990s [1]-[7]. The following features of distribution networks are identified as being

different from those of transmission networks when applying SE.

Lack of real-time measurements although the number of measurements available to a

DMS is increasing, it is still much less than the number of state variables. This necessitates the

use of pseudo measurements, which are derived from historical data.

Network size distribution networks are topologically much larger than transmission networks.

Researchers have therefore developed computationally efficient algorithms for Distribution State

Estimators (DSE) that can be applied to a large part of a distribution network [1]-[4]. Network


41/95



reduction methods have also been applied to provide a network model that is sufficiently simple

to analyse.

Low X/R ratio 11 kV distribution line impedance typically has a ratio of inductance to

resistance of about 0.5. The same ratio for a transmission line is typically about 10. This means

that transmission SE algorithms that decouple active and reactive power terms may not be

appropriate for distribution networks.

Radial topology distribution systems are generally operated as radial networks, unlike

transmission systems, which are operated as mesh networks. As the amount of embedded

generation increases, distribution networks may be operated meshed. A DSE algorithm

therefore needs to perform satisfactorily on both radial and meshed networks.

Bi-directional power flow distribution networks were generally designed for uni-directional

power flows from a few grid supply points radially outwards to customers. An embedded

generator may reverse the direction of power flow. A DSE algorithm therefore needs to take

account of bi-directional power flow on a radial network.

Unbalanced loads - distribution networks are operated with unbalanced loads in the USA and

consequently DSE algorithms that estimate state variables for all three phases have been

developed [2]-[4]. These may be unnecessary for UK distribution systems, which are operated

with more or less balanced loads compared to the USA.

2.3.3 A Distribution State Estimator

The following is a description of a distribution state estimator that is suitable for use with

embedded generation. The approach to selecting the SE method has been to use the simplest

applicable established techniques.


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Weighted Least Squares Algorithm

The most common SE algorithm is the weighted least squares formulation, defined by Equation

1 below:

i2

{x1, x2, , xNs}

J (x1, x2, , xNs) = [Zi

eas fi(x1, x2, , xNs)]2

Nm

i = 1

min

(2.1)

Where:

x is a state variable

Ns is the number of state variables

fi is the function relating the ith measurement to the state variables

Zimeas is the ith measurement

Nm is the number of measurements

i2 is the variance of the ith measurement

J(x) is the measurement residual

The algorithm finds the best fit between the state variables and the available measurements,

taking account of the accuracy of the measurements. The difference between a measurement

and the measurement value calculated from the state variables is first taken. This is then squared

and divided by the variance of the measurement. The sum of these terms is then minimised by

adjusting the values of the state variables. This method has been proven in transmission systems

and is applicable to both radial and meshed networks.

Newton-Raphson Solution

The functions fi are non-linear and so Equation 2.1 cannot be solved directly. The Newton-

Raphson method finds the set of state variables for which the derivative of Equation 2.1 is zero,

by approximating the derivatives of the functions fi with Taylor series. This method is used in


43/95



load flow and transmission state estimation (TSE) and so is well documented and is suitable for

use with the low line X/R ratio on distribution networks. Other methods, such as forward-

backwards sweep can be applied only to radial network.

State Variables

The state variables are taken as the bus voltage magnitudes and relative phase angles. These are

the most commonly used state variables in load flow and TSE and so their use is well

documented. In addition to these, the statuses of circuit breakers are taken as state variables.

Their use at transmission level is documented in [9] and their application to DSE is reported in

[8].

Some researchers have used branch currents as state variables for DSE, claiming improved

computational efficiency [3]. This is worth further investigation for application to the DMS

controller.

Measurement Functions

The functions fi relate measurements to state variables. The constants in these functions are the

network line impedances. Functions fi for DSE measurements are:

Bus active power injection

Bus reactive power injection

Line active power flow

Line reactive power flow

Line current magnitude

Bus voltage magnitude

Measurement equipment for some or all of these quantities may already be installed on a

particular part of a network.


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Pseudo measurements

On distribution networks, the number of measurements is much less than the number of state

variables. A SE algorithm requires the number of measurements to be the same as or larger than

the number of state variables. The unmeasured quantities are provided by pseudo

measurements. These are measurement values that are derived from off-line data. Some

researchers have investigated the availability and use of such data [6], while others have

assumed it to be available [4]. It is proposed to calculate pseudo measurements using standard

load profiles for three load classes: domestic, commercial and industrial. The profiles specify a

normalised load expected value and variance for each half hour of the day. These will be

matched to the particular network using available historical data. The variance associated with

each pseudo measurement will be much larger than that associated with each measurement.

Statistical SE

In TSE, each measurement is modelled as an independent normally distributed random variable

with expected value Zimeas and variance i

2. The estimated state variables are therefore also

random variables. In TSE, generally only the expected values are considered. This is because in

TSE there are more measurements than state variables and so the state estimate is the most

accurate representation of the system state available.

In DSE, as the variances of the pseudo measurements are much larger than the variances of the

real measurements, the accuracy of the state estimate can be improved by increasing the number

of measurements. Clearly, the balance must be struck between cost of measurements and the

value that they bring.

A particular accuracy of state estimate will be necessary for control scheduling and this will

require a particular number of measurements. This accuracy and number of measurements can

be determined by calculating the statistical properties of the state variables and using these to set


45/95



confidence limits. For example, consider an estimated bus voltage magnitude, modelled as a

normally distributed random variable and a fixed system voltage magnitude limit. If the expected

value of the estimated voltage is three standard deviations from the voltage limit, then there is a

99.73 % certainty that the actual bus voltage is within the limit. An acceptable level of certainty

is chosen and this determines how many standard deviations from a limit the expected value of a

state variable can be. The number of measurements is then chosen to provide a sufficiently small

state variable standard deviation to allow the state variable expected value to vary over an

acceptable range for control scheduling.

Three approaches to statistical DSE have been made. These use probabilistic load flow [5],

stochastic load flow [7] and fuzzy state estimation [8]. The stochastic load flow approach is the

simplest. It assumes that the measurements and pseudo measurements are normally distributed

random variables and approximates the state variables as normally distributed random variables.

It also allows correlation of measurements and pseudo measurements.

The accuracy of the stochastic state estimate will also depend upon the goodness of fit of a

normally distributed random variable to the actual variations of the measurements and pseudo

measurements.

2.4. Control Scheduling

Two methods have been considered for scheduling controls. These are priority list and optimal

power flow.


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2.4.1 Priority List

A priority list is specific to the part of network under the control of the DMS controller. The

network is studied off-line and a priority list of controls and sets of rules are drawn up. A set of

controls is then selected in real-time by testing the state estimate against the rules.

The priority list might comprise, for example, 30 sets of controls, with set 1 being the most

preferred and set 30 the least preferred. One set of controls comprises a setting for each device

under the control of the DMS controller. Each set of controls has an associated set of rules. Aset of rules comprises a permissible range for each state variable. The control-scheduling

algorithm tests the state estimate against each set of rules, starting with the most preferred set of

controls and continuing down the priority list. If the state estimate obeys all the rules for a

particular set of controls, then that set is output.

In drawing up the priority list, decisions are made as to the most desirable controls. The

following is a possible list of control aims that could be used to draw up a priority list. They refer

to the network shown in Figure 2.1 and are listed in descending order of preference. Generators

1 and 2 are taken to be synchronous and generator 3 to be asynchronous.

1. Maximise generator 1 active power export



4. Minimise generator 1 reactive power import

5. Minimise generator 2 reactive power import

6. Minimise compensator reactive power import

7. Minimise time controllable load is disconnected

8. Maximise voltage setting for OLTCs


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The order of preference would be established from the ancillary service contracts between the

network operator and the owners of the devices.

In selecting a set of controls, the control-scheduling algorithm also needs to take account of the

number of changes in control setting that it makes. In doing this, the type of device under control

needs to be considered. For instance, too many changes to the set point of an AVC relay will

cause mechanical wear in the OLTC, shortening its life. This is a less important issue for an

automatic voltage regulator of a synchronous machine, but would still need to be taken into

account.

The control settings also need to take account of generators such as wind turbines that have

fluctuating output power.

2.4.2 Optimal Power Flow

In general, the following sources of control may be available for managing the voltage and flowprofiles of active distribution networks:

Control limits e.g. OLTC maximum number of tap steps

Reactive power compensators

Embedded generators

Controllable loads

The choice of controls will depend on

Objective of the optimisation and cost associated with each of the controls

Operating conditions defined by the network topology and loading

Location and magnitudes of violated voltage and/or flow limits and

Effectiveness of each control source in eliminating specific violations and its cost


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This problem belongs to the class of general Optimal Power Flow problems. The main idea of

an OPF applied in the context of active distribution networks would to minimise the total cost of

available control actions while satisfying voltage and thermal constraints and determining the

value of the corresponding controls applied (GiP DiP , cQ and kT ).

This problem, for each individual settlement period t, may be stated mathematically as follows:

Objective function

),,,(,,,

ijiDiGiTQPP

TQPPMinimiseCDiGi

(2.2)

Subject to:

),,( TVPPPPP injiDiGiLiGi =+ (2.3)

),,( TVQQQQQQ in jiDiGiLiCGi =++ (2.4)

max

ijij SS (2.5)

max

ii

min

iVVV (2.6)

maxmin

Gi

cur

GiGi PPP (2.7)

max

cc

min

c QQQ

max

kk

min

k TTT (2.9)

)(GiGi

PfQ = (2.10)

)( DiDi PgQ = (2.11)

Where,

LiLi Q,P Active and reactive load at node i, at time t


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GiGi Q,P Active and reactive generation at node i, at time t

GiGi QP , Active and reactive generation curtailment/increase at node i, at time t

(if possible)

DiDiQP , Active and reactive demand curtailment/increase at node i, at time t (if

possible)

cQ Reactive power absorbed by a reactive compensator, at time t

inji

inji Q,P Active and reactive power injection at node i, at time t

kTTap setting of the tap-changer k, at time t

ijS Load flows of the branch ij, at time t

max

ijS Maximum control load flow in branch ij, at time t

i Voltage angle at node i, at time t

iV Voltage at node i, at time t

The objective function (Equation 2.2) minimises the total cost of control actions. It is envisaged

that exercising each of the available control actions may be associated with some cost. For

example, there is likely to be some cost associated with constraining generators in order to

manage the voltage and flows in the network. The costing should be based on some form of the

opportunity cost which would form a base for the cost of contracts curtailment. This may be in

the form of fees associated with the exercise of the options. Nodal power balance equations are

represented by Equation 2.3 and 2.4.

The optimisation is also subject to the branch thermal constraint (Equation 2.5) and network

voltage limits (Equation 2.6). The maximum

Documents

Active Management of Distribtion Networks.pdf