Optimal Scheduling of Regional Integrated Energy Systems Under Two-Stage Power to Gas
-
摘要:
针对区域综合能源系统的弃风弃光问题和经济成本最优问题，提出一种考虑电转气（P2G）两阶段模型的区域综合能源系统优化调度方法. 首先，以电-气-热-储-氢耦合的区域综合能源系统作为研究对象，建立系统各设备模型及P2G两环节模型；接着，在相关功率约束条件下建立系统优化调度模型；在此基础上，引入激励型电力需求侧响应，采用混合整数规划YALMIP函数对其优化，得到优化后负荷曲线，通过改变可转移负荷的用电时间以提升系统的经济性；再次，以日运行成本最小为优化目标，使用混合整数线性规划方法求解优化调度方案，并计算相应的成本；最后，结合某一地区的历史数据，利用本文所提出的优化调度方法求解电-气-热-储-氢耦合区域综合能源系统的优化调度结果，并开展不同季节、是否含P2G环节、是否考虑需求侧响应影响因素下的技术经济分析，验证了该方法的合理性和有效性. 研究结果表明：考虑两阶段P2G环节后，冬、夏季系统弃风弃光量均大幅减少，经济成本分别减少32.62%和61.64%；考虑需求侧响应后，冬季系统经济成本减少比例进一步提升至33.69%.
Abstract:Aiming at wind and light abandonment and economic cost optimization in regional integrated energy systems, an optimal scheduling method of regional integrated energy systems considering power to gas (P2G) two-stage model is proposed. First, the regional integrated energy system with electricity-gas-heat-storage-hydrogen coupling is regarded as the research object, and the equipment models and two-stage P2G models of the system are established. Secondly, the optimal scheduling model of the system is established under the relevant power constraints. On this basis, the incentive response from power demand side is introduced, and the load curve is optimized with the mixed integer programming YALMIP function. The system economy is improved by changing the power consumption time of the transferable load. Finally, the mixed integer linear programming method is used to solve the optimal scheduling solution and the costs under the objective of minimizing the daily operation cost. According to the historical data of a certain area, the presented optimization scheduling method is adopted to obtain optimization scheduling results for the integrated energy systems in this electricity-gas-heat-storage-hydrogen coupling area, and the rationality and effectiveness of this method are verified by technical and economic analysis in terms of different seasons, P2G stages and demand side response. The results show that after under the two-stage P2G, the amount of abandoned wind and light is greatly reduced in winter and summer, and the economic cost is reduced by 32.62% and 61.64%, respectively; when introducing the demand side response, the proportion of system economic cost reduction in winter is further increased to 33.69%.
-
Key words:
- multi-energy coupling /
- integrated energy system /
- P2G /
- demand side response /
- optimal scheduling /
- economic analysis
-
图 1 “电-气-热-储-氢”区域综合能源系统结构
Figure 1. Integrated energy system structure of electricity-gas-heat-storage-hydrogen coupling area
图 5 冬季典型日风光出力预测数据
Figure 5. Predicted normal output data of wind turbine and photovoltaic system in winter
图 11 冬季典型日电负荷需求响应前、后对比
Figure 11. Comparison of normal daily electric load demands in winter before and after introducing response
表 2 不同场景下的系统运行成本
Table 2. Operating costs in different scenarios
元 场景 购电成本 购气成本 购氢成本 弃风成本 弃光成本 总成本 1 557.5 5863.6 1079.6 1099.4 56.6 8656.7 2 401.0 5420.8 0 10.7 0 5832.5 3 0 3025.6 1079.6 1426.6 207.7 5739.5 4 0 2152.3 0 49.5 0 2201.8 
下载: 导出CSV
表 3 冬季不同场景下的系统运行成本
Table 3. Operating costs in different scenarios in winter
元 场景 购电成本 购气成本 购氢成本 弃风成本 弃光成本 补贴成本 总成本 节省成本/% 1 557.5 5863.6 1079.6 1099.4 56.6 0 8656.7 2 401.0 5420.8 0 10.7 0 0 5832.5 32.62 5 22.6 5152.3 0 17.7 0 547.8 5740.4 33.69
下载: 导出CSV
-
[1] 贾宏杰,王丹,徐宪东,等. 区域综合能源系统若干问题研究[J]. 电力系统自动化,2015,39(7): 198-207.JIA Hongjie, WANG Dan, XU Xiandong, et al. Research on some key problems related to integrated energy systems[J]. Automation of Electric Power Systems, 2015, 39(7): 198-207. [2] 邵成成,王锡凡,王秀丽,等. 多能源系统分析规划初探[J]. 中国电机工程学报,2016,36(14): 3817-3829.SHAO Chengcheng, WANG Xifan, WANG Xiuli, et al. Analysis and programming of multiple energy systems[J]. Proceedings of the Chinese Society for Electrical Engineering, 2016, 36(14): 3817-3829. [3] LIU J, LI J, YAO X. The economic effects of the development of the renewable energy industry in China[J]. Energies, 2019, 12(9): 1808.1-1808.18. doi: 10.3390/en12091808 [4] 许东,谢梦华. 综合能源系统规划现状分析[J]. 低碳世界,2019,9(7): 87-89. [5] 黎静华,朱梦姝,陆悦江,等. 综合能源系统优化调度综述[J]. 电网技术,2021,45(6): 2256-2272. doi: 10.13335/j.1000-3673.pst.2021.0020LI Jinghua, ZHU Mengshu, LU Yuejiang, et al. A review of optimal scheduling for integrated energy systems[J]. Power System Technology, 2021, 45(6): 2256-2272. doi: 10.13335/j.1000-3673.pst.2021.0020 [6] 施泉生,丁建勇,晏伟,等. 基于能量流含P2G电-热系统风电消纳优化运行[J]. 太阳能学报,2021,42(5): 394-400.SHI Quansheng, DING Jianyong, YAN Wei, et al. Optimized operation of wind power consumption based on energy flow with P2G electro-thermal system[J]. Acta Energiae Solaris Sinica, 2021, 42(5): 394-400. [7] 张涛,郭玥彤,李逸鸿,等. 计及电气热综合需求响应的区域综合能源系统优化调度[J]. 电力系统保护与控制,2021,49(1): 52-61. doi: 10.19783/j.cnki.pspc.200167ZHANG Tao, GUO Yuetong, LI Yihong, et al. Optimization scheduling of regional Integrated energy System with integrated electric-thermal demand Response[J]. Protection and Control of Power Systems, 2021, 49(1): 52-61. doi: 10.19783/j.cnki.pspc.200167 [8] 刘志坚,刘瑞光,梁宁,等. 含电转气的微型能源网日前经济优化调度策略[J]. 电工技术学报,2020,35(增2): 535-543.LIU Zhijian, LIU Ruiguang, LIANG Ning, et al. Day-ahead optimal economic dispatching strategy for micro energy-grid with P2G[J]. Transactions of China Electrotechnical Society, 2020, 35(S2): 535-543. [9] 邓逸天,王宇辉,黄景光,等. 考虑需求响应的含P2G电-气综合能源系统优化调度[J]. 智慧电力,2020,48(12): 8-13,32.DENG Yitian, WANG Yuhui, HUANG Jingguang, et al. Optimal dispatch of integrated electricity-gas system with power to gas considering demand response[J]. Smart Power, 2020, 48(12): 8-13,32. [10] GAHLEITNER STATIONARY G. Hydrogen from renewable electricity: an international review of power-to-gas pivot plants for stationary applications[J]. International Journal of Hydrogen Energy, 2013, 38(5): 2039-2061. doi: 10.1016/j.ijhydene.2012.12.010 [11] 降国俊,崔双喜,樊小朝,等. 考虑电转氢气过程及综合需求响应的电-氢-气综合能源系统协调优化运行[J]. 可再生能源,2021,39(1): 88-94.JIANG Guojun, CUI Shuangxi, FAN Xiaochao, et al. Coordinated and optimized operation of electric-hydrogen-gas integrated energy system considering the process of power to hydrogen and comprehensive demand response[J]. Renewable Energy, 2021, 39(1): 88-94. [12] 吴锋棒. 风光氢储综合能源系统优化配置[J]. 山东化工,2020,49(16): 135-136, 138.WU Fengbang. Optimal configuration of wind-solar hydrogen storage integrated energy system[J]. Shandong Chemical Industry, 2020, 49(16): 135-136, 138. [13] 王成山,王丹,李立浧,等. 需求侧智慧能源系统关键技术分析[J]. 中国工程科学,2018,20(3): 132-140. doi: 10.15302/J-SSCAE-2018.03.019WANG Chengshan, WANG Dan, LI Liying, et al. Analysis of key technologies of demand-side smart energy systems[J]. Strategic Study of Chinese Academy of Engineering, 2018, 20(3): 132-140. doi: 10.15302/J-SSCAE-2018.03.019 [14] WANG B, WANG Q, WEI Y, et al. Role of renewable energy in China’s energy security and climate change mitigation: an index decomposition analysis[J]. Renewable and Sustainable Energy Reviews, 2018, 90: 187-194. doi: 10.1016/j.rser.2018.03.012 [15] 王磊,姜涛,宋丹,等. 基于灵活热电比的区域综合能源系统多目标优化调度[J]. 电力系统保护与控制,2021,49(8): 151-159.WANG Lei, JIANG Tao, SONG Dan, et al. Multi-objective optimization scheduling of regional integrated energy system based on flexible thermoelectric ratio[J]. Power System Protection and Control, 2021, 49(8): 151-159. [16] 王海云,杨宇,于希娟,等. 基于需求侧响应的电热综合能源系统风电消纳低碳经济调度[J]. 燕山大学学报,2021,45(2): 142-152.WANG Haiyun, YANG Yu, YU Xijuan, et al. Low carbon economic dispatching of wind power consumption in electric and thermal integrated energy system based on demand side response[J]. Journal of Yanshan University, 2021, 45(2): 142-152. [17] 陈琦,李红伟,周海林. 考虑风电消纳的电-热综合能源系统经济运行研究[J]. 中国测试,2022,48(1): 116-121.CHEN Qi, LI Hongwei, ZHOU Hailin . Considering wind power given electrical and thermal energy system economic operation research[J]. China Test, 2022, 48(1): 116-121. [18] 王珂,姚建国,姚良忠,等. 电力柔性负荷调度研究综述[J]. 电力系统自动化,2014,38(20): 127-135.WANG Ke, YAO Jianguo, YAO Liangzhong, et al. Review of flexible power load scheduling[J]. Automation of Electric Power Systems, 2014, 38(20): 127-135. [19] 符杨,蒋一鎏,李振坤,等. 计及可平移负荷的微网经济优化调度[J]. 中国电机工程学报,2014,34(16): 2612-2620.FU Yang, JIANG Yiliu, LI Zhenkun, et al. Economic optimal scheduling of micro-grid considering translatable loading[J]. Proceedings of the Chinese Society for Electrical Engineering, 2014, 34(16): 2612-2620. [20] 何舜,郑毅,蔡旭,等. 微网能源系统的滚动优化管理[J]. 电网技术,2014,38(9): 2349-2355.HE Shun, ZHENG Yi, CAI Xu, et al. Rolling optimization management of micro grid energy system[J]. Power Grid Technology, 2014, 38(9): 2349-2355. [21] 何舜,郑毅,蔡旭,等. 基于荷-储型微网的需求侧管理系统运行优化[J]. 电力系统自动化,2015,39(19): 15-20.HE Shun, ZHENG Yi, CAI Xu, et al. Operation optimization of demand-side management system based on load-storage microgrid[J]. Automation of Electric Power Systems, 2015, 39(19): 15-20. -
下载:
点击查看大图
计量
- 文章访问数: 195
- HTML全文浏览量: 123
- PDF下载量: 43
- 被引次数: 0