Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 37, Issue 4, Pages 2639-2654Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2021.3130339
Keywords
Planning; Investment; Costs; Transformers; Uncertainty; Maintenance engineering; Generators; Active power distribution network; active network management; expansion planning; local energy market; distribution system operator (DSO)
Categories
Funding
- Iran National Science Foundation (INSF)
- US National Science Foundation (NSF) [CNS-1951847, ICER-2022505, TPWRS-00241-2021]
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This paper presents a new framework for multistage expansion planning in active power distribution networks. The framework considers active network management through clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the costs imposed on the distribution system operator (DSO), while the lower level maximizes social welfare through clearing the local energy market. The implementation of the model on distribution test systems validates its performance in making cost-effective planning decisions.
This paper presents a new framework for multistage expansion planning in active power distribution networks, in which the distribution system operator (DSO) considers active network management by clearing the local energy market at the distribution level. The proposed model is formulated as a bi-level optimization problem, where the upper level minimizes the net present value of the total costs imposed to DSO associated with the investment and maintenance of the network assets as well as the network operation, while the lower level on clearing the local energy market captures the participation of distributed energy resource (DER) owners and demand aggregators to maximize the social welfare. The expansion plans consider the investments in DER owners' assets as well as variety of network assets in which the profitability of DER owners' investment is guaranteed. The Karush-Kuhn-Tucker optimality conditions and the strong duality theory are employed through which the model is converted to a mixed integer linear programming optimization problem. The implementation of the suggested model on the 24-bus and 86-bus distribution test systems validates its performance and efficacy in making cost-effective planning decisions.
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