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

beswwang@polyu.edu.hk

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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。

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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

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• 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

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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

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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)

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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)

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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

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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

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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

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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

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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

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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

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Main Interface of the developed software tool

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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

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