Low-Carbon Optimization of Electric and Heating Integrated Energy System with Flexible Resource Participation
Pan Chao1, Fan Gongbo1, Wang Jinpeng1, Xu Xiaodong1, Meng Tao2
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology of Ministry of Education Northeast Electric Power University Jilin 132012 China; 2. Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd Changchun 130021 China
Abstract:The modern energy system is in the low-carbon transition stage. However, due to the randomness and volatility of renewable energy, it is difficult to integrate into the grid and the low-carbon process is limited. Integrated Energy Systems (IES) focus on meeting the demand for interaction between supply and demand. In recent years, increasingly resources on the load and energy storage side have begun to participate in the low-carbon operation of the system, but the resource synergy advantage has not been fully utilized, and there is a lack of analysis on the flow and transfer of carbon emissions in IES. To solve these problems, this paper proposes a low carbon optimization model of electric and heating integrated energy system considering the participation of flexible resources, analyzes the improvement effect of multiple flexible resources response on the comprehensive benefits of the system, and visually presents the flow process of electric thermal carbon emissions topologically, promoting the efficient consumption of low carbon energy in IES. First, analyze the industrial load regulation mechanism of differentiated layout in the regional power grid, and establish the model of cogeneration unit, electric heating equipment, electric/thermal energy storage and controllable load in the electric-thermal coupling system based on the urban energy grid. Then, a comprehensive benefit model is built with economic cost, wind and solar usage and carbon emissions as indicators, and a carbon emission flow topology is proposed to describe the carbon emission flow information attached to the energy flow. Finally, the electric-thermal coupling energy system is simulated to obtain the regulatory results of flexible resources and carbon emission flow information in different resource allocation scenarios. In this model, the improvement effect of flexible resource participation response on the comprehensive benefits of the system is analyzed from the perspective of economy and low carbon, and a more comprehensive evaluation model is formed by visualizing the flow process of electric and thermal carbon emissions through topology. In the IEEE 33 node distribution network and 45 node heat network coupling system, different scenarios are divided according to the flexible resource composition for simulation. The results show that under the collaborative regulation of resources on the load storage side, compared with the scenario without flexible resources, the economic cost is increased by about 8.1%, the wind and solar usage rate is increased by 7.9%, and the carbon emissions are reduced by 10.8%. Through the reasonable conversion of energy storage operation mode, the power supply burden of traditional high carbon emission power supply units is reduced. The participation of industrial controllable loads has effectively expanded the flexible resources, reducing the peak valley difference by 17%, further promoting the consumption of solar energy and reducing carbon emissions. The topology analysis of carbon flow in typical periods of the operation cycle shows that the carbon emission topology of wind and solar energy in IES can be extended to more load nodes in the system through the storage and redistribution of low carbon and excess energy, and the reasonable electricity production transfer of industrial users, thus reducing the node carbon emission intensity and the total carbon emissions in the operation cycle. The following conclusions can be drawn from the simulation analysis: (1) The flexible resource model can describe the adjustment characteristics of energy storage and the industry specific industrial load regulation characteristics, and can make policy based on the resource type. (2) By optimizing the flexible resource operation scheme, the benefits of IES in terms of economy, wind and solar usage rate and carbon emissions can be improved, and diversified optimization schemes can be provided within feasible areas. The carbon emission flow model adopted can accurately describe the carbon emission flow process of IES in the operation cycle. (3) Through flexible resource control, it can promote the penetration of low-carbon energy in IES, reduce the use of energy-intensive energy, and help achieve the economic operation of the system in a low-carbon environment.
潘超, 范宫博, 王锦鹏, 徐晓东, 孟涛. 灵活性资源参与的电热综合能源系统低碳优化[J]. 电工技术学报, 2023, 38(6): 1633-1647.
Pan Chao, Fan Gongbo, Wang Jinpeng, Xu Xiaodong, Meng Tao. Low-Carbon Optimization of Electric and Heating Integrated Energy System with Flexible Resource Participation. Transactions of China Electrotechnical Society, 2023, 38(6): 1633-1647.
[1] 余晓丹, 徐宪东, 陈硕翼, 等. 综合能源系统与能源互联网简述[J]. 电工技术学报, 2016, 31(1): 1-13. Yu Xiaodan, Xu Xiandong, Chen Shuoyi, et al.A brief review to integrated energy system and energy internet[J]. Transactions of China Electrotechnical Society, 2016, 31(1): 1-13. [2] 张大海, 贠韫韵, 王小君, 等. 考虑广义储能及光热电站的电热气互联综合能源系统经济调度[J]. 电力系统自动化, 2021, 45(19): 33-42. Zhang Dahai, Yun Yunyun, Wang Xiaojun, et al.Economic dispatch of integrated electricity-heat-gas energy system considering generalized energy storage and concentrating solar power plant[J]. Automation of Electric Power Systems, 2021, 45(19): 33-42. [3] 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. Zhang Tao, Guo Yuetong, Li Yihong, et al.Optimization scheduling of regional integrated energy systems based on electric-thermal-gas integrated demand response[J]. Power System Protection and Control, 2021, 49(1): 52-61. [4] 王典, 潘超, 鹿丽, 等. 计及风-光时序相关特性的源-储并网阶段式规划策略[J]. 东北电力大学学报, 2020, 40(4): 1-10. Wang Dian, Pan Chao, Lu Li, et al.Source-storage staged planning strategy considering wind-photovoltaic timing related characteristics[J]. Journal of Northeast Electric Power University, 2020, 40(4): 1-10. [5] Giannitrapani A, Paoletti S, Vicino A, et al.Optimal allocation of energy storage systems for voltage control in LV distribution networks[J]. IEEE Transactions on Smart Grid, 2017, 8(6): 2859-2870. [6] 姜海洋, 杜尔顺, 朱桂萍, 等. 面向高比例可再生能源电力系统的季节性储能综述与展望[J]. 电力系统自动化, 2020, 44(19): 194-207. Jiang Haiyang, Du Ershun, Zhu Guiping, et al.Review and prospect of seasonal energy storage for power system with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2020, 44(19): 194-207. [7] Xiao Hao, Pei Wei, Dong Zuomin, et al.Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel[J]. CSEE Journal of Power and Energy Systems, 2018, 4(2): 155-167. [8] 滕云, 孙鹏, 罗桓桓, 等. 计及电热混合储能的多源微网自治优化运行模型[J]. 中国电机工程学报, 2019, 39(18): 5316-5324, 5578. Teng Yun, Sun Peng, Luo Huanhuan, et al.Autonomous optimization operation model for multi-source microgrid considering electrothermal hybrid energy storage[J]. Proceedings of the CSEE, 2019, 39(18): 5316-5324, 5578. [9] 张雨曼, 刘学智, 严正, 等. 光伏-储能-热电联产综合能源系统分解协调优化运行研究[J]. 电工技术学报, 2020, 35(11): 2372-2386. Zhang Yuman, Liu Xuezhi, Yan Zheng, et al.Decomposition-coordination based optimization for PV-BESS-CHP integrated energy systems[J]. Transactions of China Electrotechnical Society, 2020, 35(11): 2372-2386. [10] 李振坤, 岳美, 胡荣, 等. 计及分布式电源与可平移负荷的变电站优化规划[J]. 中国电机工程学报, 2016, 36(18): 4883-4893, 5112. Li Zhenkun, Yue Mei, Hu Rong, et al.Optimal planning of substation considering distributed generation and shiftable loads[J]. Proceedings of the CSEE, 2016, 36(18): 4883-4893, 5112. [11] 孙建军, 张世泽, 曾梦迪, 等. 考虑分时电价的主动配电网柔性负荷多目标优化控制[J]. 电工技术学报, 2018, 33(2): 401-412. Sun Jianjun, Zhang Shize, Zeng Mengdi, et al.Multi-objective optimal control for flexible load in active distribution network considering time-of-use tariff[J]. Transactions of China Electrotechnical Society, 2018, 33(2): 401-412. [12] 彭春华, 刘兵, 左丽霞, 等. 计及分类需求响应的孤岛微网并行多目标优化调度[J]. 电力系统保护与控制, 2019, 47(5): 60-68. Peng Chunhua, Liu Bing, Zuo Lixia, et al.Parallel multi-objective optimal dispatch of island micro-grid considering load classified demand response[J]. Power System Protection and Control, 2019, 47(5): 60-68. [13] 王昀, 谢海鹏, 孙啸天, 等. 计及激励型综合需求响应的电-热综合能源系统日前经济调度[J]. 电工技术学报, 2021, 36(9): 1926-1934. Wang Yun, Xie Haipeng, Sun Xiaotian, et al.Day-ahead economic dispatch for electricity-heating integrated energy system considering incentive integrated demand response[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1926-1934. [14] 许健, 刘念, 于雷, 等. 计及重要负荷的工业光伏微电网储能优化配置[J]. 电力系统保护与控制, 2016, 44(9): 29-37. Xu Jian, Liu Nian, Yu Lei, et al.Optimal allocation of energy storage system of PV microgrid for industries considering important load[J]. Power System Protection and Control, 2016, 44(9): 29-37. [15] 国网吉林经研院2020年清洁能源大省战略下灵活性负荷技术特性研究[R].国网吉林经研院2020年清洁能源大省战略下灵活性负荷技术特性研究[R]. 长春: 国家电网吉林电力经济技术研究院, 2021. [16] 陈亚爱, 林演康, 王赛, 等. 基于滤波分配法的混合储能优化控制策略[J]. 电工技术学报, 2020, 35(19): 4009-4018. Chen Yaai, Lin Yankang, Wang Sai, et al.Optimal control strategy of hybrid energy storage based on filter allocation method[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4009-4018. [17] Tahir M F, Chen Haoyong, Mehmood K, et al.Integrated energy system modeling of china for 2020 by incorporating demand response, heat pump and thermal storage[J]. IEEE Access, 2019, 7: 40095-40108. [18] 周长城, 马溪原, 郭祚刚, 等. 面向工程应用的用户级综合能源系统规划[J]. 电工技术学报, 2020, 35(13): 2843-2854. Zhou Changcheng, Ma Xiyuan, Guo zuogang, et al. User-level integrated energy system planning for engineering applications[J]. Transactions of China Electrotechnical Society, 2020, 35(13): 2843-2854. [19] 孙国强, 王文学, 吴奕, 等. 辐射型电-热互联综合能源系统快速潮流计算方法[J]. 中国电机工程学报, 2020, 40(13): 4131-4142. Sun Guoqiang, Wang Wenxue, Wu Yi, et al.Fast power flow calculation method for radiant electric-thermal interconnected integrated energy system[J]. Proceedings of the CSEE, 2020, 40(13): 4131-4142. [20] Rosen M A, Kleme J.Allocating carbon dioxide emissions from cogeneration systems: descriptions of selected output-based methods[J]. Clean. Prod, 2008, 16(2): 171-177. [21] Cheng Yaohua, Zhang Ning, Wang Yi, et al.Modeling carbon emission flow in multiple energy systems[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 3562-3574. [22] Huang Xianzheng, Xu Zhaofeng, Sun Yong, et al.Heat and power load dispatching considering energy storage of district heating system and electric boilers[J]. Journal of Modern Power Systems and Clean Energy, 2018, 6(5): 992-1003. [23] Bramerdorfer G.Multiobjective electric machine optimization for highest reliability demands[J]. CES Transactions on Electrical Machines and Systems, 2020, 4(2): 71-78. [24] 王嵘冰, 徐红艳, 郭军. 自适应的非支配排序遗传算法[J]. 控制与决策, 2018, 33(12): 2191-2196. Wang Rongbing, Xu Hongyan, Guo Jun.Adaptive non-dominated sorting genetic algorithm[J]. Control and Decision, 2018, 33(12): 2191-2196. [25] 张绍平. 分布式电源在配电网中的优化配置研究[D]. 南昌: 南昌大学, 2021. [26] 张义志. 考虑多能网络的综合能源系统最优能流计算和恢复重构方法研究[D]. 北京: 北京交通大学, 2018. [27] 崔杨, 陈志, 严干贵, 等. 基于含储热热电联产机组与电锅炉的弃风消纳协调调度模型[J]. 中国电机工程学报, 2016, 36(15): 4072-4081. Cui Yang, Chen Zhi, Yan Gangui, et al.Coordinated wind power accommodating dispatch model based on electric boiler and CHP with thermal energy storage[J]. Proceedings of the CSEE, 2016, 36(15): 4072-4081. [28] 许周, 孙永辉, 谢东亮, 等. 计及电/热柔性负荷的区域综合能源系统储能优化配置[J]. 电力系统自动化, 2020, 44(2): 53-59. Xu Zhou, Sun Yonghui, Xie Dongliang, et al.Optimal configuration of energy storage for integrated region energy system considering power/thermal flexible load[J]. Automation of Electric Power Systems, 2020, 44(2): 53-59. [29] 陈寒, 唐忠, 鲁家阳, 等. 基于CVaR量化不确定性的微电网优化调度研究[J]. 电力系统保护与控制, 2021, 49(5): 105-115. Chen Han, Tang Zhong, Lu Jiayang, et al.Research on optimal dispatch of a microgrid based on CVaR quantitative uncertainty[J]. Power System Protection and Control, 2021, 49(5): 105-115. [30] 黄伟, 柳思岐, 叶波. 考虑源-荷互动的园区综合能源系统站-网协同优化[J]. 电力系统自动化, 2020, 44(14): 44-53. Huang Wei, Liu Siqi, Ye Bo.Station-network cooperative optimization of integrated energy system for park considering source-load interaction[J]. Automation of Electric Power Systems, 2020, 44(14): 44-53. [31] 刁涵彬, 李培强, 王继飞, 等. 考虑电/热储能互补协调的综合能源系统优化调度[J]. 电工技术学报, 2020, 35(21): 4532-4543. Diao Hanbin, Li Peiqiang, Wang Jifei, et al.Optimal dispatch of integrated energy system considering complementary coordination of electric/thermal energy storage[J]. Transactions of China Electrotechnical Society, 2020, 35(21): 4532-4543. [32] Cheng Yaohua, Zhang Ning, Zhang Baosen, et al.Low-carbon operation of multiple energy systems based on energy-carbon integrated prices[J]. IEEE Transactions on Smart Grid, 2020, 11(2): 1307-1318.