NDLI: Layered stochastic approach for residential demand response based on real-time pricing and incentive mechanism

Content Provider	IET Digital Library
Author	Wang, Zhanle Paranjape, Raman Chen, Zhikun Zeng, Kai
Abstract	This paper proposes a layered stochastic optimization approach for residential demand response (DR) under real-time pricing (RTP) and an incentive-based mechanism, which contains three steps. In the first layer, an independent system operator (ISO) announces day-ahead RTP to a residential load aggregator (RLA). The RLA predicts individual household loads (step 1) and aggregates the loads to minimize electrical cost (step 2). In the second layer, the RLA announces incentives to homes, and home energy management systems (EMS) control the loads to maximize the reward in real-time (step 3). In Step 1, probability based individual load prediction models are developed. In Step 2, a stochastic optimization model is developed to aggregate controllable loads of residential consumers. In Step 3, an incentive-based mechanism is proposed, based on which, a real-time load control model for individual homes is developed to benefit the RLA and homeowners. A highly efficient real-time control algorithm for home EMS is developed. The case studies show that, with 10% controllable energy integration, the peak demand is reduced by 17.5% and the energy cost of the controllable loads is reduced by 28%. The proposed mechanism can effectively aggregate many individual residential controllable loads to participate in an electricity market.
Starting Page	423
Ending Page	431
Page Count	9
ISSN	17518687
Volume Number	14
e-ISSN	17518695
Issue Number	Issue 3, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/14/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2019.1135
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-11-28
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	10% Controllable Energy Integration Aggregates Building Management System Day-ahead RTP Demand Side Management Distributed Power Generation Domestic Appliances Energy Cost Energy Management System Home EMS Home Energy Management System Incentive Mechanism Incentive-based Mechanism Incentives Independent System Operator Individual Homes Individual Residential Controllable Load Layered Stochastic Approach Layered Stochastic Optimisation Approach Load Forecasting Load Regulation Optimisation Optimisation Technique Peak Demand Power Market Power System Control Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Pricing Probability Probability-based Individual Load Prediction Model Real-time Control Algorithm Real-time Load Control Model Real-time Pricing Residential Consumers Residential Demand Response Residential Load Aggregator RLA Statistics Step 1 Stochastic Linearised SCUC Stochastic Optimisation Model
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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