Energy and Economy Energy Modelling Lab. Department of Energy Studies, Energy Systems Division, Ajou...

Energy and Economy

Energy Modelling Lab.Department of Energy Studies,

Energy Systems Division, Ajou University Prof. Suduk Kim

[email protected]

CHP continued…

How Fuel Cells Work? How electrolysis works How Fuel Cells Work (1)

Advantages of Direct FuelCell® (DFC®) stationary power plants

FuelCell Energy’s DFC power plants offer numerous advantages over conventional and alternative power generation sources: Ultra-clean due to their virtual absence of pollutants which supports sustainability

goals, facilitates clean air permitting during installation, and benefits public health throughout the lifecycle of the power plant

Economical because high efficiency reduces fuel costs Reliable baseload power provides continuous electricity and heat around-the-clock On-site distributed generation improves power reliability and energy security Fuel flexible DFCs can be operated on clean natural gas, renewable biogas or

directed biogas Combined heat and power (CHP) further drives economics and efficiency — as

high as 90 percent, depending on the application Avoid investment and maintenance in costly, difficult to site transmission &

distribution (T&D) infrastructure Versatile DFC power plants convert biogas waste disposal problems into ultra-

clean power generation solutions for operations that generate biogas High efficiency minimizes the carbon footprint of DFC plants operating on natural

gas; DFC plants are generally classified as carbon neutral by regulatory bodies when operating on biogas due to its renewable nature

Source: Fuel Cell Energy, also available at http://www.fuelcellenergy.com/why-fuelcell-energy/benefits/

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- the need to have a framework to facilitate the Demand Response in power market- the Importance of the bilateral information exchange

Economics of Smart Grid (Demand Response)

Software CD Design

Hourly Power Consumption Analysis (KEPCO)

--66--

Program Initiation

Main Menu


--88--

Data

Raw Data on Customer Information

KEPCO Affilate Data Points(’05-’09)

NumberCustomer

경기북부 72,923 2,081

충북 60,664 1,271

충남 129,646 3,153

인천 141,233 2,743

전북 47,882 976

제주 14,012 214

전남 100,644 1,965

경기 257,011 5,774

경남 81,056 1,714

강원 48,538 1,193

부산 199,026 4,213

대구 & 경북 124,698 2,940

서울 236,798 5,969

총합계 1,514,131 34,206

Raw Data on Customer Load Profile

KEPCO Affilate Number of Days (’05-’09)

NumberCustomer

경기북부 1,041,137 764

충북 269,208 182

충남 402,621 248

인천 1,723,160 1,209

전북 930,248 630

제주 298,976 230

전남 1,594,857 1,148

경북 123,928 85

경기 5,095,058 3,460

경남 1,516,664 1,055

강원지사 312,906 235

강원 249,733 239

부산 3,668,584 2,291

대구 573,901 370

남서울 & 서울 2,903,737 2,003

총합계 20,704,718 14,149

1. Raw Data Summary

99

Data Cleaning Process

Customer Profile

Data Points(’05-’09)

NumberCustomer

Total 1,514,131 34,206

가공된 고객정보 데이터

Data Points(’05-’09)

NumberCustomer

총합계 435,398 8,645

Load Profile

Number of Days(’05-’09)

NumberCustomer

Total 20,704,718 14,149

가공된 전력부하 데이터

Number of Days(’05-’09)

NumberCustomer

총합계 12,354,287 8,645

# Elimination of Duplicates# Choose in between the period of 2005.01 - 2009.12 # Elimination of Data Recording Error 2005.02.30/31# Final Sample selection in conjunction with load profile

# Elimination of Daily Duplicates# Elimination of Duplicate Errors at the KEPCO Affiliate (South Seoul/Seoul)# Final Sample selection in conjunction with load profile

1010

데이터 현황

분류 1 분류 2 분류 3 코드 기업수 비고

주택용 저압 100 199

일반용

갑

저압 211 87

고압 A 221 2,119

고압 B 231 1

을고압 A 226 844

고압 B 236 7

임시 ( 을 ) 2X8 696

교육용저압 213 3

고압 A 223 16

농사용갑 410 1

병 430 43

3. 모형적용을 위한 고객정보 및 전력부하 데이터 현황 (1)

1111

데이터 현황

분류 1 분류 2 분류 3 코드 기업수 비고

산업용

갑

저압 311 51

고압 A 321 483

고압 B 331 2

을고압 A 721 2,428

고압 B 731 4

병

고압 A 726 1,399

고압 B 736 161

고압 C 746 1

가로등 을 610 35

심야갑 905 16

을 915 68

3. 모형적용을 위한 고객정보 및 전력부하 데이터 현황 (2)

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=> 위 것과 함께 하나로

KSIC ( Korean standard industrial classification) and KEPCO Data

1313

Panel Type of Regression Equation

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Fitted Load Pattern (Chemical Industry C, High Voltage A)

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- Customer Number [726-0305] - Actual and Fitted load pattern

480Hours after Jan. 1st

Simulation Result(Chemical Industry C, High Voltage A)

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- Customer Number [726-0305]- With the 20% Price Increase, following gives the expected impact on power consumption

480Hours after Jan. 1st

Smart Grid Taxonomy—Dividing the System

Source: Leeds, DJ, The Smart Grid in 2010: Market Segments, Applications and Industry Players, GTM Research, 2009

Telco, Manufacturers Companies

Power, Energy Companies

Telco, Energy, Computer, Consultant, Software, Hardware Companies

Taxonomy of Smart Grid: Players

Source: Leeds, DJ, The Smart Grid in 2010: Market Segments, Applications and Industry Players, GTM Research, 2009

Consumer Portal—Future Concept of Energy Management (Costumer Side)

Electric Power Research Institute, Consumer Portal Stakeholder FAQ and Survey, IntelliGrid EPRI, 2005

Costumer portal is “a combination of hardware and software that enables two-way communication between energy service organizations and equipment within the consumers’ premises”

1. Google Power Meter ProjectEight utilities representing over 10 million customers from 3 countries and 6 different US states have become the first partners of the Google PowerMeter project. They are offering these smart meters to their customers to enable them to access detailed information on their home energy use. To assist the utility partners with the integration to Google PowerMeter, the group is also joined by Itron, one of the world's largest meter manufacturers. Here are the first 9 partners:

Glasgow EPBLocation: Glasgow, KentuckyCustomers: 7,000

JEALocation: Northeast FloridaCustomers: 417,000

Reliance EnergyLocation: Mumbai, Delhi & Orissa, IndiaCustomers: 6.8 million

San Diego Gas & Electric ®Location: San Diego County and Southern Orange County, CaliforniaCustomers: 1.4 million

Toronto Hydro–Electric System Limited Location: Toronto, Ontario, CanadaCustomers: 684,000

TXU EnergyLocation: TexasCustomers: 2.2 million

White River Valley Electric CooperativeLocation: Portions of Christian, Douglas, Ozark, Stone and Taney counties in MissouriCustomers: 40,000

Wisconsin Public ServiceLocation: Northeast and Central Wisconsin and an adjacent portion of Upper MichiganCustomers: 450,000

Yello Strom Location: Germany Customers: 1.4 million

EUROPENo Telecom

companiesPower companies Main activities

1 Metering data center, M2M communication network

2 UTILIS’s smart metering, integrated solution with billing systems

3 NES meters, meter management software

4 Management of metering information, reporting, maintenance and support of all devices

5 System to manage the deployment of Linky smart meters

6 T connect Elecktro-Kraft and Jeppo Kraft

ADDAX remote reading electric meters

7 AiMiR system Deployment

8 Low cost PLC Automatic/Remote Meter Reading, Home/Building Automation, Switching and Lighting, HVAC Control

9 Turn-key solutions, services for the BPL/PLC

10 Advanced Automated Meter management (AMM) system solutions

North AmericaNo Telecom companies Power companies

1 Open standards-based, secure wireless network communications

2 Motorola Motorola’s Harmony system

3 Advanced Metering System, Utility of the Future Project

4 Intelligent communications infrastructure, smart meters

5 Motorola Wireless communication systems and services

6 Customer care and Billing, Pecan Street Project

7 Google Smart Meters “Google Powermeter Project”

8 intelligent communication platform , home energy management information and controls

9 Smart metering and Smart Grid engagements

Australia and New Zealand case

No Telecom companies Power companies

1 Turn-key metering, installation of AMM

2 Network infrastructure, communications

3 Advanced metering technology, operational services

No Telecom companies Power companies

1 AiMiR system Deployment

2 Motorola Motorola MOSCAD system

ASIA and South America

Task I : SGMM and KUL

SGMM Architecture and Matrix

6 Levels x 8 Domains

Source: SEI, 2011, SGMM Model Definition: A framework for smart grid transformation

Smart Grid Compass: SurveyFirst 4 sections: Non-Specific Questions on Surveyee

Sections 1 and 2 capture contact information for the responding utility and the person completing the survey.

Section 3 collects key data about the responding organization.

Section 4 collects grid performance data that is used to correlate the impact of increasing smart grid maturity with overall grid performance.

8 Domain-Specific QuestionsSections 5-12 present multiple choice questions

organized by SGMM domain that address each expected characteristic in the model.

Source: SEI, 2011, SGMM Compass Assessment Survey: A survey based assessment of smart grid maturity

KUL : Katholieke Universiteit Leuven, Belgium

Benjamin Dupont, Student Member, IEEE, L. Meeus, and R. Belmans, Fellow, IEEE, Measuring the “Smartness” of the Electricity Grid, 978-1-4244-6840-9/101, IEEE, 2010, http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5558673&isnumber=5558663&tag=1

Ronnie Belmans, SmartGrids A Vision For Intelligent Electrical Grids Serving the Energy

User, CEER Smartgrids, June 29, 2009 SmartGrids A Vision For Intelligent Electrical Grids, Smart Grids

Presentatie, IEEE, 12 mei 2009 SmartGrids SRA 2035, Strategic Research Agenda Update of the SmartGrids

SRA 2007 for the needs by the year 2035, March 2012

Both at the same department!!

Ageing AssetsInstallation wave in European distribution systems in the 60s & 70s-> Replacement wave with business-as-usual approach-> Opportunity for new system architecture and operation schemes

EU SmartGrid Vision Proper Measurement of ‘Smartness’ of SmartGrid will be an essential part!

JRCEU SmartGrid Vision

But JRC has publications onBCA!

Source: SmartGrids SRA 2035: Strategic Research Agenda, Update of the SmartGrids SRA 2007 for the needs by the year 2035, EU, March 2012

Characteristics of SG (EPRI, DOE, KUL)

Source: EPRI, Methodological Approach for Estimating the Benefits and Costs of Smart Grid Demonstration Projects, Final Report, January 2010 U.S. Department of Energy, Smart Grid System Project, January 2009 Dupont, et al, 2010, Measuring the “Smartness” of the Electricity Grid

Characteristics* Dupont. et al .(KUL) DOE EPRI

1Enables informed participation by customers

Advanced Meters

Dynamic Pricing SignalsGrid related signal

Load ManagedCustomers

Customer potalsEnergy Savings

Smart Appliances

Demand Side Management Load Participation

Prosumer

2Accommodates all generation and storage options

Distributed Generation and Storage

PHEVs Load Factor

DER interconnection

3Sell more than kWhs**

New Energy Services Regulatory Policy

Flexibility Open Architecture/Stds

Customer Choice Electric Vehichles Plug-in Electric

Support Mechanisms Venture Capital Ancillary Service

Interoperability Maturity Level Interoperability certification

4Provide power quality for the 21st Century

Required Power Quality

Power Quality

Microgrids

5Optimise assets and operate efficiently

T&D Automation Deferred gneration, project

Dynamic Line Rating

Capacity Factors

Efficiencies

6Operate resiliently to disturbances, attacks and natural disasters***

Advanced Sensors

information Exchange Grid Response Load DER penetration

T&D Reliability (Improvement in reliability and outage restoration)

Standards in telecommunication infrastructure Cyber Security

Outage restoration improvement

Sub total 59 20 46

•*Each characteristics have similar name for each organization, the name of Characteristics are mainly based on Dupont et. Al.•**EPRI and DOE use ‘Enables new products, services and markets’•*** In EPRI, he has two Charateristics for #6, but we integrated those in one because of those similarity.

Task II : BCA

BCA Comparison from Various ReportsBenefits (EPRI 2010)

BCA REPORTS

EPRI 2004 EPRI 2011 FERC 2006 FSC 2008 IEE 2011

Economic

Improved Asset Utilization

Optimized Generator Operation

Deferred Generation Capacity Investments X X X

Reduced Ancillary Service Cost X X X

Reduced Congestion Cost X X

T&D Capital Savings

Deferred Transmission Capacity Investments X X X X

Deferred Distribution Capacity Investments X X X X

Reduced Equipment Failures X X

T&D O&M Savings

Reduced T&D Equipment Maintenance Cost X X

Reduced T&D Operations Cost X X X

Reduced Meter Reading Cost X X X X

Theft Reduction Reduced Electricity Theft

Energy Efficiency Reduced Electricity Losses X X

Electricity Cost Savings Reduced Electricity Cost X X X X

Reliability

Power Interruptions

Reduced Sustained Outages X X X X X

Reduced Major Outages X X X X X

Reduced Restoration Cost X X X X X

Power QualityReduced Momentary Outages X X X X

Reduced Sags and Swells X X

Environmental Air EmissionsReduced CO2 Emissions X X X X

Reduced SOx, NOx, and PM-10 Emissions X X

Security Energy SecurityReduced Oil Usage (not monetized) X

Reduced Wide-scale Blackouts X X

Source:

EPRI_2004 Power Delivery System of The Future: A Preliminary Estimate of Costs and Benefits (EPRI 1011001)

EPRI_2010 Methodological Approach for Estimating the Benefits and Costs of Smart Grid Demonstration Projects (EPRI 1020342)

EPRI_2011a Estimating the Costs and Benefits of the Smart Grid: A Preliminary Estimate of the Investment Requirements and the Resultant Benefits of a Fully Functioning Smart Grid (EPRI 1022519)

FERC_2006 Assessment of Demand Response & Advanced Metering (AD-06-2-000)

FSC_2008 Benefit-Cost Analysis of Advanced Metering and Time Based Pricing

IEE_2011 The Costs and Benefits of Smart Meters for Residential Customers

국내 BCA 사례 ( 한국전력 , 2011.7)

고객측면의 BCA 결과

Utilities 측면의 BCA 결과

Source: AMI 구축과 RTP 시행에 따른 경제성 분석 , 기획본부 , 경영연구소 , 한국전력 , 2011.7

Previous Researches

Source: EPRI 1020342, Methodological Approach for Estimating the Benefits and Costs of Smart Grid Demonstration Projects, January 2010

Other BCA ResearchesFSC, 2007, Benefit-Cost Analysis for Advanced Metering and Time-Based Pricing, Stephen S. George, Michael Wiebe, Workshop, Freeman Sullivan & Co., November 13, 2007 - (Short, ppt)

FSC, 2008, Benefit-Cost Analysis for Advanced Metering and Time-Based Pricing, Stephen S. George, Josh Bode, Michael Wiebe, Freeman Sullivan & Co., Jan., 2008 - (Full Document)

ESC, 2002a, Installing Interval Meters for Electricity Customers – Costs and Benefits - Position Paper, November 2002

ESC, 2002b, Installing Interval Meters for Electricity Customers – Costs and Benefits - Position Paper, November 2002, pp. 79-87

ESC, 2002c, Installing Interval Meters for Electricity Customers – Costs and Benefits - Position Paper, November 2002, pp 62-66

ESC, 2002d, Installing Interval Meters for Electricity Customers – Costs and Benefits - Position Paper, November 2002, pp.62-66

ESC, 2002e, Installing Interval Meters for Electricity Customers – Costs and Benefits - Position Paper, November 2002, pg. 85

CRA and Impaq Consulting, 2005, Advanced Interval Meter Communications Study, Draft Report, 23 December 2005, pg. 60.

Institute for Electric Efficiency, 2010, “ Utility Scale Smart Meter Deployment, Plans and Proposal (September, 2010)

IEE, 2011, The Costs and Benefits of Smart Meters for Residential Customers, IEE Whitepaper, Institute for Electric Efficiency July 2011

Greentech Media report, 2011, “ Smart Grid HAN Strategy Report 2011: Technologies, Market Forecast, and Leading Players, “2011

EPRI, 2004, “Power Delivery System of the Future: A Preliminary Estimate of Costs and Benefits,” Palo Alto, CA: 1011001.

EPRI, 2008, “Characterizing and Quantifying the Societal Benefits Attributable to Smart Metering Investments,” Palo Alto, CA: 1017006.

EPRI, 2008, “The Green Grid: Energy Savings and Carbon Emissions Reductions Enabled by a Smart Grid,” Palo Alto, CA: 1016905.

EPRI, 2010, “Methodological Approach for Estimating the Benefits and Costs of Smart Grid Demonstration Projects,” Palo Alto, CA: 1020342.

EPRI, 2011, “Estimating the Costs and Benefits of the Smart Grid: A Preliminary Estimate of the Investment Requirements and the Resultant Benefits of a Fully Functioning Smart Grid,” Palo Alto, CA: 1022519.

The Brattle Group , 2008, “Transforming America’s Power Industry: The Investment Challenge 2010- 2030,” prepared by The Brattle Group for The Edison Foundation, November 2008.

Federal Energy Regulatory Commission(FERC), 2006, Assessment of Demand Response and Advanced Metering, Staff Report, February 2006

Federal Energy Regulatory Commission(FERC),2008, Assessment of Demand Response and Advanced Metering, Staff Report, December 2008

Federal Energy Regulatory Commission(FERC), 2009, A National Assessment of Demand Response Potential, Staff Report, June 2009

Federal Energy Regulatory Commission(FERC), 2010, National Action Plan on Demand Response, Docket No. AD09-10, June 17, 2010

JRC, 2012, Guidelines for conducting a cost-benefit analysis of Smart Grid projects

Modern Grid Initiative, http://www.netl.doe.gov/moderngrid.

Task III : JRC & DOE, EPRI

EPRI: The Concept of BenefitDefinition: an impact (of a Smart Grid project) that has value to a firm, a household, or society in general.

Types: Four fundamental categories of benefits Economic – reduced costs, or increased production at

the same cost, that result from improved utility system efficiency and asset utilization

Reliability and Power Quality – reduction in interruptions and power quality events

Environmental – reduced impacts of climate change and effects on human health and ecosystems due to pollution

Security and Safety – improved energy security (i.e., reduced oil dependence); increased cyber security; and reductions in injuries, loss of life and property damage

Perspectives: Three basic groups of beneficiaries Utilities are the suppliers of power and include electric

utilities that generate power as well as the transmission and the load serving entities that deliver it (and integrated utilities that do all three)

Customers are the end-users or consumers of electricity Society in general is the recipient of externalities of the

Smart Grid – effects on the public or society at large – which can be either positive or negative in nature.


Precision: represents the level ofprecision in the estimated magnitudes of these benefits and costs. A reasonable way of characterizing the general level of precision is to use broad categories such as:

1. Modest level of uncertainty in quantitative estimates and/or in monetization (the project might specify percentile values)

2. Significant uncertainty in quantitative estimates and/or in how to monetize

3. Highly uncertain4. Cannot be quantified

Map Functions to Benefits (EPRI)


Utility

Utility

Consumer

Society

Ten-Step Approach for Cost-Benefit Analysis (EPRI)


JRC Application of BCA (InovGrid)

Source: JRC, 2012, Guidelines for conducting a cost-benefit analysis of Smart Grid projects

Step 2 Identify Functionalities

Step 1: Identify Project and Its Technologies

Step 3 Map each functionality to standardized benefit

Step 4-5: Quantify Benefit

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Characterization Module Screenshots (Example: Phase I)

INITIAL APPROACH TO QUANTIFY AND MONETIZE BENEFITS


Table C-2

In general,Benefit = Baseline - Project

Benefit Calculation Input Data

Optional Inputs: Alternative Formula of Benefit Calculation (usually more detailed) can be conducted at the right hand corner of new row of data input. Default: Default Input for Benefit Calculation

Baseline ~2016, Project 2012-2016

Cost Representation (Too Simple Process!)

1. Yearly Cost Input: the capital cost for each year along the project year

2. Amortized Cost Input: Initial and final year of spending, Total capital cost, and

Interest rate Yearly amortized cost is calculated

Amortized Cost

Yearly Cost

Task I,II,III and Comparison and Proposition

Relationships Among the Tasks

EPRI

DOE

SGCT

JRCBCA

SEISGMM

Tool Kit DevelopmentTASK III

EU SmartGrid Enhancement

Smartness

Performance Mesurement

Smartness, MaturityTASK I

EPRI Guideline

BCA-Benefit Cost AnalysisTASK II

Other Tool Kit Development Experiences of EML

Wind (REVAP v0.9) & PV

Solar - REVAP v0.9

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KNOC(Korea National Oil Comapany)

Energy and Economy Energy Modelling Lab. Department of Energy Studies, Energy Systems Division, Ajou...

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