Data-Driven Resource Planning for Virtual Power Plant Integrating Demand Response Customer Selection and Storage

Battery energy storage (BES) and demand response (DR) are two important resources to increase the operational flexibility of a virtual power plant (VPP) and thus reduce the economic risks that VPP faces in the short-term electricity market. This article develops a data-driven approach for VPP resour...

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Bibliographic Details
Published inIEEE transactions on industrial informatics Vol. 18; no. 3; pp. 1833 - 1844
Main Authors Liang, Huishi, Ma, Jin
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.03.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Customers
Demand response (DR)
Electric power demand
electricity market
Electricity meters
Energy management
Energy storage
Heterogeneity
HVAC
Investment
Load modeling
Planning
Power plants
Pricing
Real-time systems
Renewable energy sources
resource planning
Risk management
smart meter data
Smart meters
Stochastic programming
Uncertainty
virtual power plant (VPP)
Virtual power plants
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Summary:Battery energy storage (BES) and demand response (DR) are two important resources to increase the operational flexibility of a virtual power plant (VPP) and thus reduce the economic risks that VPP faces in the short-term electricity market. This article develops a data-driven approach for VPP resource planning (VRP), in which BES sizing and DR customer selection are optimized synergistically to maximize VPP's profit in the electricity market. Heterogeneity in DR potential across individual customers is considered in the planning framework by utilizing the knowledge learnt from smart meter data. The overall VRP problem is formulated by a risk-managed, multistage stochastic programming framework to address the uncertainties from the intermittent renewable energy sources, load demands, market prices, and DR resources. Case studies compare the VRP results under two market imbalance settlement settings, namely, penalty-charged and penalty-free markets. The results demonstrate that jointly optimizing BES and DR customer selection leveraging the smart meter data can improve the VPP's expected profit under both market settings.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2021.3068402