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Clustering in DR A primary step in DR implementation is the detailed knowledge of customer potential through customer aggregation and characterization of demand clusters. Customers whose demand follow the day-ahead or real-time prices are the

  1. Clustering in DR A primary step in DR implementation is the detailed knowledge of customer potential through customer aggregation and characterization of demand clusters. Customers whose demand follow the day-ahead or real-time prices are the ones who are more suitable for DR programs selection from the view point of both customer and supplier Clustering provides typical load pattern of each customer class which can be used for choosing DSM program, tariff structure etc. Moreover demand characterization provides an effective tool to estimate the potential demand reduction, loss of service cost and impact of DR programs on demand. 19 / 26

  2. DR in Smart Grid Technology advancements in smart grid facilitates deployment of DR Early detection : Smart grid enables utilities to detect and respond to load increases early by calling a DR event. Improved Communication : Smart grid promises to increase the efficacy of DR by streamlining the notification process and providing real-time information to customers Accurate and Easy Verification : Smart grid enables utilities to measure and verify customers’ curtailment during a DR event Automation Systems : An automated DR would automatically detect the need to shed load, send signals to participants, and control all devices that use electricity Demand Response Markets : Smart grid creates a market for energy efficiency by enabling large energy users to reduce consumption when pricing rates are higher. 20 / 26

  3. DR in Smart Grids contd... Direct load control Load management Interruptible Incentive DR load control based Porgrames Demand side Market Energy bidding based Conservation Demand side management Capacity Strategic Time of market load growth use Ancillary Price Real time Flexible load services based pricing shaping Critical peak pricing 21 / 26

  4. Enabling Technologies It can be broadly captured under following heads- Advanced metering - Advanced Meter Reading (AMR) and Advanced Metering Infrastructure (AMI). Most essential feature of AMI is availability of continuous and automatic bidirectional communication link. Communication - Local Area Network(LAN) for communication within consumer’s premise and between the premise and nearest data aggregators, while Wide Area Network (WAN) for collection of data from aggregators spread over wide area. Meter data management - collecting, organizing and processing data for various applications e.g. billing customer load profiling etc. Control - Control of consumption. Home automation systems, home area network (HAN), In-home Displays (IHDs) 22 / 26

  5. Popular DR programs Some programs from US and Europe. New York ISO : Reliability based and Economic based DR programs. ISO England, USA : Incentive based DR. Pennsylvania Jersey Maryland (PJM, USA): Economic and Emergency DR programs. Electric Reliability Council of Texas (ERCOT, USA) : Emergency Response service. Nordic Market - apart from similar economic and reliability based DR programs it also has grid tariffs for effective price based also included. 23 / 26

  6. DR Standards Energy inter-operation version 1.0 -information and communication model developed by OASIS for the coordination purpose between any two parties in power system OpenADR 2.0 - extension of OpenADR 1.0. It had two profiles. First one is OpenAdr2.0a, to support basic DR services in low-end embedded devices while second one is OpenADR2.0b, to support DR for high-end embedded devices. It’s communication is based on the principle of VTN (virtual top node) and VEN (virtual end node). Smart Energy profile 2.0 - specification for different energy transaction in smart grid domain e.g. communication smart meters, energy management systems, electric vehicles. 24 / 26

  7. Practical Challenges Following are the major challenges faced in the implementation of a DR program. operational time-scale at which it should be incorporated into the system proper tariff and regulation policies cost recovery and profit for economic sustainability automation of different systems reliability of supply and privacy of usage for sensitive customers base line problem mainly in incentive based DR programs security and privacy for both customers and utility 25 / 26

  8. DR in Indian Context Demand response is in its nascent stages in India. Its benefits will mirror those seen in Western countries, such as reduced electricity blackouts, reduced electricity costs, offsetting the need to build supply resource and the ability to integrate electric vehicles and renewable energy sources. Regulatory framework also needs to be in place for implementation of DR strategies. It is necessary to identify the appropriate consumers to be roped in for DR to ensure the success of the program due to large diversity. Consumer awareness and maintaining transparency with them must be a priority to win their confidence and ensure acceptance of the DR program. The electrical distribution network must be strengthened to ensure reliability in operations. To cater to the diverse needs of the consumers, a variety of DR modules need to be prepared. 26 / 26

  9. Review of Demand Response Under Smart Grid Paradigm V. S. K. Murthy Balijepalli, Vedanta Pradhan, S. A. Khaparde and R. M. Shereef Panel Session on Smart Grid 2011 IEEE PES International Conference on Innovative Smart Grid Technologies 2 nd December, 2011, Kerala, India Presented by: Vedanta Pradhan I. I. T. Bombay

  10. Outline • Introduction 1 • Motivation and Benefits 2 • Literature Review 3 • Challenges in DR implementation 4 • Conclusions 5

  11. Outline • Introduction 1 • Motivation and Benefits 2 • Literature Review 3 • Challenges in DR implementation 4 • Conclusions 5

  12. Introduction • Definition: According to Federal Energy Regulatory Commission Demand Response (DR) is defined as: “ Changes in electric usage by demand-side resources from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized. ”

  13. DR Classification Motivation Method Load Response Price Response  Direct Load Control Trigger Criteria  Critical Peak Pricing Reliability  Curtailable Load  Demand Bidding  Interruptible Load  Time-of-Use Pricing  Direct Load Control  Critical Peak Pricing Economic  Curtailable Load  Real-time Pricing  Demand Bidding

  14. • Introduction 1 • Motivation and Benefits 2 • Literature Review 3 • Challenges in DR implementation 4 • Conclusions 5

  15. DR Benefits Network & Retailer/ System Operation Distributor  Spot price volatility risk Customer reduction Market  Deferred need for T&D infrastructure  Managing network constraints  End users affecting market Renewables  Savings in electricity bills  Market power mitigation  Incentives  Overall electricity  Performance payments price reduction  More penetration of renewable resources

  16. Motivation Advancement of ICT and automation Ample DR potential

  17. • Introduction 1 • Motivation and Benefits 2 • Literature Review 3 • Challenges in DR implementation 4 • Conclusions 5

  18. Literature Review • DR concepts • DR frameworks • DR frameworks and models directly directly applicable applicable to to wholesale retail markets markets Class A Class C Class B

  19. • DR concepts • DR frameworks • DR frameworks and models directly directly applicable applicable to to wholesale retail markets markets Class A Class C Class B

  20. The importance of an active demand side in the electricity industry- H. Fraser, Nov. 2001 • Market based model; effective DR mechanisms; vary consumption according to hourly prices Demand side management: Benefits and challenges – G. Strbac, Dec. 2008 • Review of DSM techniques; challenges; dynamic pricing Behaviour modification – S. Braithwait, May 2010 A comparison of system response for different types of real-time pricing – A. K. David, Y. Z. Li, 1991 • Consumer categories SR, LR, RW; system disturbances; spot pricing and day-ahead pricing; consumer response

  21. Demand response and market performance in power economics – D. Yang, Y. Chen, 2009 • Demand interaction with power flows; adverse effect on price on some node; congestion on some corridor; market gaming A summary of demand response in electricity markets - M.H. Albadi, E.F. El- Saadany, Nov. 2008 • Definition, classification, potential benefits, cost components; indices used for DR measurement; utilities experience with DR programs ; effect on electricity prices. Framework for the incorporation of demand side in a competitive electricity market - G. Strbac, E. D. Farmer and B. J. Cory, May 1996 • Redistributable demand; Demand Side Bidding; cost minimization problem; limits on generation and demand reduction; diversity in load redistribution

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