Bi-level stackelberg game-based distribution system expansion planning model considering long-term renewable energy contracts
-
Published:2023-12
Issue:1
Volume:8
Page:
-
ISSN:2367-2617
-
Container-title:Protection and Control of Modern Power Systems
-
language:en
-
Short-container-title:Prot Control Mod Power Syst
Author:
Gao Hongjun, Wang Renjun, He ShuaijiaORCID, Wang Zeqi, Liu Junyong
Abstract
AbstractWith the deregulation of electricity market in distribution systems, renewable distributed generations (RDG) are being invested in by third-party social capital, such as distributed generations operators (DGOs) and load aggregators (LAs). However, their arbitrary RDG investment and electricity trading behavior can bring great challenges to distribution system planning. In this paper, to reduce distribution system investment, a distribution system expansion planning model based on a bi-level Stackelberg game is proposed for the distribution system operator (DSO) to guide this social capital to make suitable RDG investment. In the proposed model, DSO is the leader, while DGOs and LAs are the followers. In the upper level, the DSO determines the expansion planning scheme including investments in substations and lines, and optimizes the variables provided for followers, such as RDG locations and contract prices. In the lower level, DGOs determine the RDG capacity and electricity trading strategy based on the RDG locations and contract prices, while LAs determine the RDG capacity, demand response and electricity trading strategy based on contract prices. The capacity information of the DRG is sent to the DSO for decision-making on expansion planning. To reduce the cost and risk of multiple agents, two long-term renewable energy contracts are introduced for the electricity trading. Conditional value-at-risk method is used to quantify the RDG investment risk of DGOs and LAs with different risk preferences. The effectiveness of the proposed model and method is verified by studies using the Portugal 54-bus system.
Funder
National Science Foundation of China Sichuan Science and Technology Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Safety, Risk, Reliability and Quality
Reference23 articles.
1. Gao, H., Wang, R., Liu, Y., Wang, L., Xiang, Y., & Liu, J. (2020). Data-driven distributionally robust joint planning of distributed energy resources in active distribution network. IET Generation, Transmission and Distribution, 14(9), 1653–1662. 2. Roy Ghatak, S., Sannigrahi, S., & Acharjee, P. (2020). Multiobjective framework for optimal integration of solar energy source in three-phase unbalanced distribution network. IEEE Transactions on Industry Applications, 56(3), 3068–3078. 3. Ehsan, A., & Yang, Q. (2019). Coordinated investment planning of distributed multi-type stochastic generation and battery storage in active distribution networks. IEEE Transactions on Sustainable Energy, 10(4), 1813–1822. 4. He, Y., Yang, N., Dong, B., Ding, L., Qin, T., Huang, Y., & Chen, C. (2019). Incremental distribution network source-load collaborative planning method considering uncertainty and multi-agent game. Proceedings CSEE, 39(09), 2689–2702. 5. Munoz-Delgado, G., Contreras, J., & Arroyo, J. M. (2019). Distribution system expansion planning considering non-utility-owned DG and an independent distribution system operator. IEEE Transactions on Power Systems, 34(4), 2588–2597.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|