Optimal Bi-Level Bidding and Dispatching Strategy Between Active Distribution Network and Virtual Alliances Using Distributed Robust Multi-Agent Deep Reinforcement Learning

The deregulated active distribution network (ADN) would incorporate numerous autonomous stakeholders, including some emerging distributed virtual alliances (DVAs) like virtual microgrids and virtual power plants. Those DVAs would autonomously participate in energy market trading through bidding amon...

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Bibliographic Details
Published in:IEEE transactions on smart grid Vol. 13; no. 4; pp. 2833 - 2843
Main Authors: Zhu, Ziqing, Chan, Ka Wing, Xia, Shiwei, Bu, Siqi
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.07.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Active distribution network
Algorithms
bidding strategy
Costs
Decision analysis
Deregulation
Dispatching
Distributed generation
distributed virtual alliance
Dynamic programming
Heuristic algorithms
Indexes
Load modeling
Machine learning
Markov processes
Multiagent systems
Optimization
Real-time systems
reinforcement learning
Robustness
Uncertainty
Virtual power plants
ISSN:1949-3053, 1949-3061
Online Access:Get full text
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Summary:The deregulated active distribution network (ADN) would incorporate numerous autonomous stakeholders, including some emerging distributed virtual alliances (DVAs) like virtual microgrids and virtual power plants. Those DVAs would autonomously participate in energy market trading through bidding among themselves and dispatching conducted by the ADN. In this paper, the optimal bidding and dispatching model for DVAs and ADN in the day-ahead market is first developed as a stochastic dynamic programming model with the risk of misconduct considered, and then re-formulated as a Markov Decision Process to be solved by a new Distributed Robust Multi-Agent Deep Deterministic Policy Gradient algorithm based on the concept of robust Nash equilibrium (RNE). This algorithm is a fully distributed online optimization that would converge to RNE. It is an effective risk-averse method to obtain the optimal bidding strategies of DVAs and the optimal dispatching decisions of distribution system operator (DSO). Its high computational performance is demonstrated in the case studies, and the strategic decisions of DVAs and DSO are thoroughly analyzed.
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2022.3164080