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Intelligent Building and Building
Energy Efficiency
Shengwei Wang Chair Professor of Building Services Engineering
Building Energy and Automation Research Laboratory, Department of Building
Services Engineering
The Hong Kong Polytechnic University
1
Basic Approaches for Energy Efficient Buildings
建筑节能的基本途径
• Reduced heating/cooling loads /低热负荷/冷负荷
– Building envelope design, passive design, etc. /建筑围护结构设计,
被动式设计,等
• Use of energy efficient and green components and technologies /使用节能和绿色环保的设备与技术
• Optimization of system and technology integration, operation and control
/优化系统和技术集成, 运行及控制
– Life-cycle commissioning, design optimization, control optimization, etc. /
全生命周期的校验,设计优化,控制优化,等。
2
20% to 50% of saving can be achieved according to my local experiences
and experiences of others in Europe and North America !
Steps towards Energy Efficient Buildings
建筑能源效益实现步骤
Make designs proper and correct
正确合理的设计
Optimize designs and selections
对设计和系统选用进行优化
Construct/install systems correctly
正确的系统施工/安装
Ensure systems operate as good as intent
确保系统运行效果达到设计期望
Push systems approach the best
使系统趋于最佳
Design Stage
设计阶段
Construction Stage
施工阶段
Operation Stage
and T&C Stage
运行与 调试测试阶段
3
• Building HVAC System Optimization Tool;
建筑空调系统优化工具
• Package of Online Optimal and Energy Efficient Control and Fault Diagnosis Strategies
实时节能优化控制和故障诊断策略系列
• Building System Online Performance Simulation Test Platform;
建筑系统实时性能模拟实验平台
• BA Control and Diagnosis Strategy Online Test Platform;
BA控制和诊断策略实时测试平台
Technologies and Tools Developed
• Building Level Energy Performance Quick Evaluation and Diagnostic Tool;
建筑整体性能快速评估和诊断工具
• Detailed Evaluation and Diagnostic Tool for A/C and BA systems;
空调和BA系统评估和诊断工具
4
Building Energy Diagnosis Tools
建筑能耗诊断工具
Virtual Test Platforms
仿真实验平台
Optimization Tools
优化工具
Examples of Deliverables (A) / 可达目标示例(A)
For Existing Buildings/既有建筑:
• Building Energy Audit, Building System Evaluation and
Diagnosis
建筑能源系统的评估和诊断
• Building Energy Saving Plan and Strategies
建筑节能方案和策略
• HVAC and Control System Commissioning & Upgrading
空调和控制系统的校验及改造
• Upgrading System Operation and Control Strategies
改进系统运行策略与控制策略
5
For New Buildings/新建建筑:
• Commissioning and Optimization of System Configuration and Selection 校验和优化系统设计和设备选型
• Commissioning and Optimization of Monitoring and Control Instrumentation and Systems 校验和优化监控设备和系统
• Commissioning of HVAC and Control Systems at Construction and T&C Stages 在施工和调试测试阶段校验空调及其控制系统
• Develop Optimal and Energy Efficient Control Strategies 开发优化及節能控制策略
Examples of Deliverables (B) /可达目标示例(B)
6
建筑全生命周期校验及优化
– 环球貿易广场
Building Life-cycle Diagnosis, Commissioning and Optimization
- International Commerce Centre (ICC)
7
Our Roles in ICC Project /我们在项目中的角色
Independent Energy Consultant (Independent Commissioning Agent)
独立的节能顾问(独立的校验代理)
To Develop the HVAC Energy Optimal Control System
开发HVAC节能优化控制系统
490 m
118 F
8
Summary of Energy Benefits/节能效益总计 • 1,000,000 kWh energy consumption is saved due to the modification
on the secondary water loops of Zone 3 & 4 / 改进3、4区二次水环路—节能1百万度
• 2,360,000 kWh , (about 5.1% of annual energy consumption of chillers and cooling towers) of the cooling system can be saving due
to the change from single speed to variable speed using VFD /冷却塔单速运行改为VFD无级变频—节能2.36百万度
• 607,000 kWh , (about 2.8% of annual energy consumption of chillers and cooling towers) of the cooling system will be wasted
when the lowest frequency is limited at 37 Hz / 若冷却塔最低频率定为37Hz,将费能约61万度
• 3, 500,000 kWh (about 7%) of the total energy consumption of HVAC system) can be saved using PolyU control strategies based on
the original design/ 在原设计方案的基础上,采用我们的控制策略节能3.5百万度
Saving by Control Optimization – compared with the
case when the HVAC system operates correctly as the
original design intent. 3.5M per year
优化控制节能 -与HVAC系统按照原设计正常运行比,每年节省约3.5百万度
Saving by Commissioning (Improving the system configuration and selection) – compared with the
original design. About 3.5 M per year
与原设计方案比,校验(改进系统形式及配置) 年节能为3.5百万度
The annual total energy
saving is about 7.0M kWh !
年节能总计约7百万度
9
Contributions in supporting ICC building in getting
HK-BEAM Platinum Certificate 对ICC铂金认证的贡献
Annual Energy Use Reduction By 14.6% to get extra 2 credits
年能耗降低14.6% 得2分
Peak Demand Reduction By 26.9% to get extra 2 credits
峰值负荷减少26.9% 得2分
Optimal Control Strategies “Innovation” for extra 1 credits
“创新项”—优化控制策略 得1分
Grade
评级
Overall
得分率
Performance
性能评价
Platinum 铂金 75% Excellent 优异
Gold 金 65% Very Good 很好
Silver 银 55% Good 较好
Bronze 铜 40% Above average
中等偏上
The overall assessment grade is based
on the percentage of applicable credits
(about 145) gained in 5 categories: site
aspects,material aspects, energy
use,water use , and IAQ (vision 4/04 ).
认证等级根据建筑在:场地,材料,能源,用水以及室内环境质量这五个方面的整体得分率而定.
Gold
金级(72.7%)
5 credits 分 (3.5%)
Platinum
铂金级(76.2%)
H V
A C
A New Hotel Development in Sheung Wan
(Holiday Inn Express)
Independent Energy Consultant (Independent Commissioning Agent)
独立的节能顾问(独立的校验顾问)
To Develop the HVAC Energy Optimal Control System
开发HVAC节能优化控制系统
12
Summary of Energy Benefits/节能效益总计
• Saving contributed by PolyU Commissioning (Improving the system configuration and selection) and Control Optimization – compared with
the case when the HVAC system operates correctly as the original
design intent. About 20% saved annually
设计校验与优化控制节能 -与HVAC系统按照原设计正常运行比,每年节省20%电能。
• Compared with the normal energy use of the hotel group, the overall energy consumption is reduced by over 30% and about 50% lower than what required by current standard.
-建筑总节能超过30%(与常规酒店平均建筑能耗相比)
-建筑总节能超过50%(与当前节能标准要求相比)
Research Areas/研究领域
• Building HVAC&R system dynamic Simulation
建筑空调制冷系统动态模拟
• HVAC&R system Optimal and Energy-Efficient Control
空调制冷系统优化及节能控制
• Building Energy and HVAC&R System Fault Diagnosis
建筑能效及空调制冷系统故障诊断
• IB/BA Integration and Management Technology
IB/BA集成及管理技术
13
14
Interaction between Intelligent Buildings and Smart Grid
- Active Participation of Building to Smart Grid Demand
Response
WEATHER DATA
INTERNAL GAIN
HVAC SYSTEMS OPTIMAL CONTROL STRATEGIES
BUILDING LOAD AGGREGATION
BUILDINGS LOAD PREDICTION
DYNAMIC PRICING
OPTIMAL SETTING Smart Grids
Concept of Interaction between Buildings and Smart Grid
The integration of smart metering system with BAS
Interaction Establishment
Integrated with smart meters and grid information management and
control centre, BASs can provide valuable information (e.g. energy
demand characteristics) for grid optimization.
Grid Dynamic
Pricing Setting
Altered Building
Power Demand
Predictor
Building Power
Demand Predictor
Building Power
Demand Alteration
Potential
Characterization
Pi: the reference power demand prediction of the ith building
Indices Pi
Pi′
Pi′: the altered power demand prediction of the ith building
r
Building Optimal Power
Demand Control
r: the finalized electricity prices
Smart Grid Information Management
and Control Center
Building Automation System
Intelligent Field Devices
(Offline Process)
(Online Process)
(Online Process)
r′: the trial electricity prices
r′
Other
Buildings
Other
Buildings
∑
Interactive Building Power Demand
Management Strategy
Building Power
Alteration
Estimation
Building-
Smart Grid
Interaction
Building Power
Demand
Management
Energy performance assessment and diagnosis
for existing information-poor buildings
既有信息匮乏建筑的能效评估及诊断
Practical constrains in assessing and diagnosing
information-poor buildings
• Insufficient availability of energy use data – Few or no sub-meters are installed
• Poor-quality measurements – Insufficient sensors are installed
– Installed sensors are seldom calibrated/maintained
• Unknown, abnormal operation modes – Occupants’ behaviors : random set-points
– Failures of automatic control: unscheduled operation
Existing methods are not applicable for
information-poor buildings
• Calculation-based methods
– Detail simulation tools: requires too many inputs, skillful
experts and time-consuming
– Simplified methods: insufficient outputs with limited
accuracy and applicability
• Measurement-based methods
– Sufficient end-use data from sub-meters
– Comprehensive BMS platform
– Continuous monitoring of operational performance
Energy balances: useful information is
embodied in buildings and systems
Conditioned
zone
Unconditioned
zone
Heat of “other-consumers”
is dissipated to
unconditioned zone or outside
Electricity
“others” e.g., lift,
exterior lighting
Cooling
Supply
Internal
heat gain
Conductive heat gain
through envelope
Heat gain due
to solar
radiation
Heat gain due
to ventilation
HVAC e.g., chiller,
pump, fan
“internal” e.g., lighting,
plugged load
OthersInternalHVACBuilding EEEE DemandSupply CLCL
Electricity consumption balance Cooling energy balance
Monthly energy performance assessment
based on limited information
Inputs
Monthly electricity
bills
Building design data
Weather data
Short-term field
measurements
Electricity balance
Cooling
demand
Cooling
supply
Cooling energy balance
Optimization algorithm
Outputs
Energy consumptions
of individual systems
Building cooling load
Energy efficiencies of
HVAC system and
main components
EHVAC EInternal
Energy Performance
Calculation
Monthly energy performance indicators can be determined by energy
balance principles in cooling season
22
Optimization algorithm for energy balancing
kWhEEE HVACOthersInternal 401,620
HVACInternalDemand EECL 843,290
SCOPECL HVACSupply
Determine EInternal, EOthers and EHVAC to
minimize relative cooling balance residual: )(5.0 SupplyDemand
SupplyDemand
CLCL
CLCL
Rμ
Outputs: Building energy performance data
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Internal-consumers HVAC system Others-consumers
Energy consumption of individual systems
Cooling
loadSCOP α
Jan 3.09E+06 1.44 38.8%
Feb 2.76E+06 1.40 40.0%
Mar 3.59E+06 1.49 36.8%
Apr 4.97E+06 1.92 33.7%
May 7.15E+06 2.04 33.5%
Jun 7.88E+06 2.09 30.9%
Jul 8.73E+06 2.15 31.5%
Aug 9.18E+06 2.22 32.0%
Sep 8.11E+06 2.14 32.5%
Oct 6.21E+06 2.00 35.2%
Nov 5.75E+06 1.93 34.8%
Dec 3.48E+06 1.57 39.0%
Total 7.09E+07 1.87 34.9%
Performance of HVAC system
24
Main Interface of the developed software tool
25
Inputs of the developed software tool
Envelope Information
HVAC Configuration
Monthly Energy Bills
Outputs of the developed software tool
HVAC consumption Building cooling load Building cooling break down System COP Balance residuals
Outputs of the developed software tool
Summary of Energy performance data
28