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Title: Strategic Behavior of Distributed Energy Resources in Energy and Reserves Co-Optimizing Markets
We consider decentralized scheduling of Distributed Energy Resources (DERs) in a day-ahead market that clears energy and reserves offered by both centralized generators and DERs. Recognizing the difficulty of scheduling transmission network connected generators together with distribution feeder connected DERs that have complex intertemporal preferences and dynamics, we propose a tractable distributed algorithm where DERs self-schedule based on granular Distribution Locational Marginal Prices (DLMPs) derived from LMPs augmented by distribution network costs. For the resulting iterative DER self-scheduling process, we examine the opportunity of DERs to engage in strategic behavior depending on whether DERs do or do not have access to detailed distribution feeder information. Although the proposed distributed algorithm is tractable on detailed real-life network models, we utilize a simplified T&D network model to derive instructive analytical and numerical results on the impact of strategic DER behavior on social welfare loss, and the distribution of costs and benefits to various market participants.
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Award ID(s):
Publication Date:
Journal Name:
2018 IEEE Conference on Decision and Control (CDC), Miami Beach, FL, 2018, pp. 4875-4881. doi: 10.1109/CDC.2018.8619550
Page Range or eLocation-ID:
4875 to 4881
Sponsoring Org:
National Science Foundation
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