| 引用本文: | 周洪伟,宗炫君,邹盛,袁洲茂,梁馨予,窦晓波,俞婧雯.计及云边协同的园区综合能源系统双层能量优化[J].电力自动化设备,2023,43(2): |
| ZHOU Hongwei,ZONG Xuanjun,ZOU Sheng,YUAN Zhoumao,LIANG Xinyu,DOU Xiaobo,YU Jingwen.Two-level energy optimization for community integrated energy system considering cloud-edge collaboration[J].Electric Power Automation Equipment,2023,43(2): |
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| 摘要: |
| 深入挖掘园区综合能源系统内部多能耦合利用以及综合需求响应潜力，对系统内灵活性资源进行储能化建模，并将虚拟储能资源按照参与优化调度的时间尺度进行划分，提出了日前、日内2个阶段的园区综合能源系统优化调度方法，在日前阶段建立了热电协同优化模型，在日内阶段基于日前调度结果建立了电功率快速调整模型。进一步地，为充分发挥综合能源系统中各园区资源的时空互补优势，从多时间尺度、多主体角度提出适用于实时阶段的计及云边协同的综合能源系统双层能量优化方法。基于各园区可再生能源发电和电负荷的最新预测结果，在能量管理云平台建立了满足系统整体运行经济性目标的实时能量优化模型，在边缘控制器利用模型预测控制方法建立了以日内优化结果为参考值的精细化调控模型，并采用交替方向乘子法求解，以实现园区自身利益与综合能源系统总体效益的均衡。仿真结果表明，通过园区间联络线的传输功率协调以及电储能、动态可控负荷的辅助调用，可有效平抑可再生能源出力和电负荷需求的实时波动，提高系统整体运行调控的鲁棒性与有效性。 |
| 关键词: 园区综合能源系统 云边协同 能量优化 模型预测方法 交替方向乘子法 |
| DOI：10.16081/j.epae.202207020 |
| 分类号:TM73;TK01 |
| 基金项目:国网江苏省电力有限公司科技项目(J2021191) |
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| Two-level energy optimization for community integrated energy system considering cloud-edge collaboration |
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ZHOU Hongwei1, ZONG Xuanjun1, ZOU Sheng1, YUAN Zhoumao2, LIANG Xinyu2, DOU Xiaobo2, YU Jingwen2
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1.Economic and Technological Research Institute of State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 210008, China;2.School of Electrical Engineering, Southeast University, Nanjing 210096, China
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| Abstract: |
| Digging into the community integrated energy system internal multi-energy coupling usage and comprehensive response demand potential deeply, the flexible resources inside the system are modeled as the energy storage, and the virtual energy storage resources are divided according to the time scale participating in optimal scheduling, thus the day-ahead and intraday two-stage community integrated energy system optimal scheduling method is proposed. The thermoelectric co-optimization model is built at the day-ahead stage and the electric power rapid adjustment model based on day-ahead scheduling results is built at the intraday stage. Furthermore, in order to give full play to the time and space complementary advantages of the resources among communities in integrated energy system, the two-layer energy optimization method for the integrated energy system considering cloud-edge collaboration is proposed from the perspectives of multi-time scale and multi-agent, which is applicable to the real-time stage. Based on the latest prediction results of renewable energy and electric load in each community, the real-time energy optimization model that meets the overall operation economic goal of system is established on the energy management cloud platform. The refined control model is established in the edge controllers using model predictive control method, which takes the intraday optimal results as the reference values. And the alternating direction method of multipliers is used to solve the problem, so as to realize the balance between the community’s own benefits and the overall benefits of the integrated energy system. The simulative results show that through the transmission power coordination of tie-lines among communities and auxiliary calls for electric energy storage and dynamic controllable load, the real-time fluctuation of renewable energy output and electric load demand can be effectively smoothed, improving the robustness and effectiveness of the system overall operation control. |
| Key words: community integrated energy system cloud-edge collaboration energy optimization model predictive method alternating direction method of multipliers |
