Voltage Hierarchical Cooperative Control of Coupled System Using Model Predictive Control and Alternating Direction Method of Multipliers
Yang Hao1, Su Wendong1, Gu Yi2, Zhang Xuan1, Guo Dongbo1, Chang Yiming2
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China; 2. State Grid Liaoning Electric Power Company Shenyang 110006 China
Abstract：In the northern area of China, it’s common that a coupled system consisting of wind power and photovoltaic stations and traditional synchronous generators sends out power through the outward transportation channels. The points of common coupling (PCC) of new energy units, stations and coupled system all need to meet the voltage safety standards, which brings greater challenges to voltage control. In this paper, a hierarchical coordinated voltage structure with system layer and station layer is proposed based on the physical level characteristics of unit-station-system in the coupled system. In order to coordinate all kind of reactive power resources, a dual-mode adaptive switching voltage control strategy for network loss optimization and voltage correction based on model predictive control (MPC) and alternating direction method of multipliers (ADMM) is established. The simulations with the modified IEEE 14 node system and the coupled system in Dalian shows the effectiveness and applicability of the proposed control strategy. Firstly, this paper establishes a hierarchical voltage coordination control structure based on the physical level characteristics of unit-station-system in the coupled system. The structure can reduce the scale and difficulty of the voltage optimization model and protect the privacy of different operating entities. Secondly, an optimal voltage control model by using the rolling time-domain MPC algorithm is proposed to improve the robustness and reliability of the voltage control considering the strong power fluctuations of renewable energy. Next, a switching control framework is designed, which adopts a dual-mode adaptive switching control mode for network loss optimization and voltage correction considering both system security and economic factors. Finally, based on the ADMM method, the voltage control for the system-level and station-level layers are solved in a distributed way, using only voltage information interaction at the interface between the system-level and station-level layers, thereby achieving voltage hierarchical cooperative control. The proposed voltage hierarchical cooperative control strategy compared with another two control strategies (voltage stability control strategy and decentralized voltage control strategy) is simulated in a modified IEEE 14-node coupled system and a coupled system in Dalian. The results demonstrate that with the voltage hierarchical cooperative control and voltage stability control, the voltages at different PCCs in the coupled system can be effectively controlled within a safe range. However, under decentralized voltage control, severe out-of-limit voltage problems occur at some PCCs. For the changes of the network loss, it is found that the coupled system with the proposed control has the lowest average network loss, while with the decentralized voltage control and the voltage stability control, the average network loss is greater. Based on the simulation results, it can be concluded that the proposed voltage control strategy can minimize network losses with meeting the voltage safety requirements for different PCCs in the coupled system. The conclusions of this paper are given as follows: (1) In the designed voltage hierarchical control framework, only the voltage information of common boundary nodes needs to be exchanged between the system layer and the station layer. There is no need for communication with different stations, which can effectively meet the privacy protection between different operating entities. It has great advantages in dealing with the voltage control problem of coupled systems with information barriers. (2) The proposed MPC-ADMM method has good robustness in addressing the problems of out-of-limit voltage caused by the power fluctuations of renewable energy. The adopted distributed method decomposes the complex global voltage optimization control problem into multiple sub-optimization control problems, reducing the optimal model scale and the difficulty of solving the control problems. (3) The proposed control strategy can reliably meet the voltage safety requirements for different PCCs in the coupling system, and effectively reduce the operating network loss, which improves the voltage safety and operating economy of the coupling system, simultaneously.
杨浩, 苏文栋, 谷毅, 张轩, 郭东波, 唱一鸣. 面向耦合系统的交替方向滚动时域电压分层协同优化控制[J]. 电工技术学报, 2023, 38(21): 5846-5861.
Yang Hao, Su Wendong, Gu Yi, Zhang Xuan, Guo Dongbo, Chang Yiming. Voltage Hierarchical Cooperative Control of Coupled System Using Model Predictive Control and Alternating Direction Method of Multipliers. Transactions of China Electrotechnical Society, 2023, 38(21): 5846-5861.
[1] 国家发展改革委员会. 可再生能源发展“十三五”规划[EB/OL]. [2023-07-04]. http://www.nea.gov.cn/135916140_14821175123931n.pdf. [2] 陈泽西, 孙玉树, 张妍, 等. 考虑风光互补的储能优化配置研究[J]. 电工技术学报, 2021, 36(增刊1): 145-153. Chen Zexi, Sun Yushu, Zhang Yan, et al.Research on energy storage optimal allocation considering complementarity of wind power and PV[J]. Transactions of China Electrotechnical Society, 2021, 36(S1): 145-153. [3] 陈国平, 董昱, 梁志峰. 能源转型中的中国特色新能源高质量发展分析与思考[J]. 中国电机工程学报, 2020, 40(17): 5493-5506. Chen Guoping, Dong Yu, Liang Zhifeng.Analysis and reflection on high-quality development of new energy with Chinese characteristics in energy transition[J]. Proceedings of the CSEE, 2020, 40(17): 5493-5506. [4] 刘斌, 张玉琼, 麻林巍, 等. 西北地区源端基地综合能源系统的技术方案设计及优化研究[J]. 中国电机工程学报, 2021, 41(2): 568-581. Liu Bin, Zhang Yuqiong, Ma Linwei, et al.Design and optimization of technical schemes of supply-side base integrated energy systems in northwest China[J]. Proceedings of the CSEE, 2021, 41(2): 568-581. [5] 杨龙杰, 周念成, 胡博, 等. 计及火电阶梯式爬坡率的耦合系统优化调度方法[J]. 中国电机工程学报, 2022, 42(1): 153-164. Yang Longjie, Zhou Niancheng, Hu Bo, et al.Optimal scheduling method for coupled system based on ladder-type ramp rate of thermal power units[J]. Proceedings of the CSEE, 2022, 42(1): 153-164. [6] 黎博, 陈民铀, 钟海旺, 等. 高比例可再生能源新型电力系统长期规划综述[J]. 中国电机工程学报, 2023, 43(2): 555-581. Li Bo, Chen Minyou, Zhong Haiwang, et al.A review of long-term planning of new power systems with large share of renewable energy[J]. Proceedings of the CSEE, 2023, 43(2): 555-581. [7] 崔鹤松, 李雪萍, 黄晟, 等. 模块化多相永磁风力发电机串并联直流海上风电场电压协调控制[J]. 电工技术学报, 2023, 38(4): 925-935. Cui Hesong, Li Xueping, Huang Sheng, et al.Voltage coordinated control strategy for modular multi-phase PMSG-based series-parallel DC connected offshore wind farm[J]. Transactions of China Electrotechnical Society, 2023, 38(4): 925-935. [8] 崔庆雪, 李霞林, 葛磊蛟, 等. 计及时滞的含风电配电网节点电压安全分析[J]. 电工技术学报, 2023, 38(5): 1299-1311. Cui Qingxue, Li Xialin, Ge Leijiao, et al.Analysis on node voltage security of distribution network with wind power considering time delay[J]. Transactions of China Electrotechnical Society, 2023, 38(5): 1299-1311. [9] 王颖, 文福拴, 赵波, 等. 高密度分布式光伏接入下电压越限问题的分析与对策[J]. 中国电机工程学报, 2016, 36(5): 1200-1206. Wang Ying, Wen Fushuan, Zhao Bo, et al.Analysis and countermeasures of voltage violation problems caused by high-density distributed photovoltaics[J]. Proceedings of the CSEE, 2016, 36(5): 1200-1206. [10] Valverde G, Van Cutsem T.Model predictive control of voltages in active distribution networks[J]. IEEE Transactions on Smart Grid, 2013, 4(4): 2152-2161. [11] Yang Hao, Zhang Wen, Chen Jian, et al.Optimal coordinated voltage control of AC/DC power systems for voltage stability enhancement[J]. International Journal of Electrical Power & Energy Systems, 2019, 108: 252-262. [12] 刘洪, 徐正阳, 葛少云, 等. 考虑储能调节的主动配电网有功—无功协调运行与电压控制[J]. 电力系统自动化, 2019, 43(11): 51-58. Liu Hong, Xu Zhengyang, Ge Shaoyun, et al.Coordinated operation of active-reactive power and voltage control for active distribution network considering regulation of energy storage[J]. Automation of Electric Power Systems, 2019, 43(11): 51-58. [13] 杨悦, 陈宇航, 成龙, 等. 考虑节点功率储备与GIN中心性的主动配电网动态集群电压控制[J/OL]. 电网技术, 2023: 1-13[2023-07-04]. DOI:10.13335/j.1000-3673.pst.2022.2520. Yang Yue, Chen Yuhang, Cheng Long, et al. Power reserve and GIN centrality of buses considered dynamic cluster voltage control of active distribution networks[J/OL]. Power System Technology, 2023: 1-13 [2023-07-04]. DOI:10.13335/j.1000-3673.pst.2022.2520. [14] 宋关羽, 于川航, 冀浩然, 等. 考虑量测数据质量的集成储能智能软开关数据驱动电压控制[J]. 电力系统自动化, 2023, 47(6): 90-100. Song Guanyu, Yu Chuanhang, Ji Haoran, et al.Data-driven voltage control of energy storage integrated soft open point considering quality of measurement data[J]. Automation of Electric Power Systems, 2023, 47(6): 90-100. [15] 马庆, 邓长虹. 基于单/多智能体简化强化学习的电力系统无功电压控制方法[J/OL]. 电工技术学报, 2023: 1-13[2023-04-21]. http://kns.cnki.net/kcms/detail/11.2188.TM.20230419.1028.002.html. Ma Qing, Deng Changhong. Single/Multi agent simplified deep reinforcement learning based volt-var control of power system[J/OL]. Transactions of China Electrotechnical Society, 2023: 1-13[2023-04-21]. http://kns.cnki.net/kcms/detail/11.2188.TM.20230419.1028.002.html. [16] 黄大为, 王孝泉, 于娜, 等. 计及光伏出力不确定性的配电网混合时间尺度无功/电压控制策略[J]. 电工技术学报, 2022, 37(17): 4377-4389. Huang Dawei, Wang Xiaoquan, Yu Na, et al.Hybrid timescale voltage/var control in distribution network considering PV power uncertainty[J]. Transactions of China Electrotechnical Society, 2022, 37(17): 4377-4389. [17] Liu Haotian, Wu Wenchuan.Federated reinforcement learning for decentralized voltage control in distribution networks[J]. IEEE Transactions on Smart Grid, 2022, 13(5): 3840-3843. [18] Kou Peng, Liang Deliang, Gao Rong, et al.Decentralized model predictive control of hybrid distribution transformers for voltage regulation in active distribution networks[J]. IEEE Transactions on Sustainable Energy, 2020, 11(4): 2189-2200. [19] 王笑雪, 徐弢, 王成山, 等. 基于MAS的主动配电网分布式电压控制[J]. 中国电机工程学报, 2016, 36(11): 2918-2926. Wang Xiaoxue, Xu Tao, Wang Chengshan, et al.Distributed voltage control in active distribution networks utilizing multiple agent system[J]. Proceedings of the CSEE, 2016, 36(11): 2918-2926. [20] 张志荣, 邱晓燕, 孙旭, 等. 基于ADMM的交直流混合配电网分布式电压优化模型[J]. 电网技术, 2021, 45(11): 4551-4559. Zhang Zhirong, Qiu Xiaoyan, Sun Xu, et al.Distributed voltage optimization model for AC/DC hybrid distribution network based on ADMM[J]. Power System Technology, 2021, 45(11): 4551-4559. [21] Huang Sheng, Wu Qiuwei, Guo Yifei, et al.Distributed voltage control based on ADMM for large-scale wind farm cluster connected to VSC-HVDC[J]. IEEE Transactions on Sustainable Energy, 2020, 11(2): 584-594. [22] 李培帅, 吴在军, 张错, 等. 主动配电网分布式混合时间尺度无功/电压控制[J]. 电力系统自动化, 2021, 45(16): 160-168. Li Peishuai, Wu Zaijun, Zhang Cuo, et al.Distributed hybrid-timescale voltage/var control in active distribution networks[J]. Automation of Electric Power Systems, 2021, 45(16): 160-168. [23] 钟成元, 桂前进, 江千军, 等. 数据驱动的高比例新能源发电集群分布式电压控制[J]. 全球能源互联网, 2022, 5(3): 251-260. Zhong Chengyuan, Gui Qianjin, Jiang Qianjun, et al.Data-driven distributed voltage control for high-penetration renewable power clusters without complete model[J]. Journal of Global Energy Interconnection, 2022, 5(3): 251-260. [24] 国家市场监督管理总局, 国家标准化管理委员会. 风电场接入电力系统技术规定第1部分:陆上风电: GB/T 19963.1—2021[S]. 北京: 中国标准出版社, 2022. [25] 国家质量监督检验检疫总局, 国家标准化管理委员会. 光伏发电站接入电力系统技术规定: GB/T 19964—2012[S]. 北京: 中国标准出版社, 2013. [26] Elia Group.Load and load forecast[DB/OL]. [2023-07-04].https://www.elia.be/en/grid-data/load-and-load-forecasts. [27] Elia Group.Wind power generation[DB/OL]. [2023-07-04].https://www.elia.be/en/grid-data/power-generation/wind-power-generation. [28] Elia Group.Solar power generation[DB/OL]. [2023-07-04].https://www.elia.be/en/grid-data/power-generation/solar-pv-power-generation-data.
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