考虑可再生能源接入的综合能源系统规划评述与展望

doi:10.12204/j.issn.1000-7229.2020.12.001

电力建设 ›› 2020, Vol. 41 ›› Issue (12): 3-13.doi: 10.12204/j.issn.1000-7229.2020.12.001

考虑可再生能源接入的综合能源系统规划评述与展望

潘尔生¹, 宋毅¹, 原凯¹, 郭玥¹, 程浩忠², 张沈习²

1.国网经济技术研究院有限公司,北京市 102209
2.电力传输与功率变换控制教育部重点实验室(上海交通大学),上海市 200240

收稿日期:2020-08-10 出版日期:2020-12-01 发布日期:2020-12-04
作者简介:潘尔生(1964),男,硕士,教授级高级工程师,国务院特殊津贴专家,主要从事电力行业规划、电网规划设计、电网建设、技术经济、工程可研等领域研究工作;|宋毅(1977),男,博士,高级工程师,主要从事能源互联网、综合能源系统与配电网规划设计、仿真分析与综合评价等研究工作;|原凯(1989),男,博士,高级工程师,主要从事能源互联网、综合能源系统与配电网建模仿真、规划设计、综合评价等研究工作|郭玥(1989),女,硕士,高级工程师,主要从事能源互联网与配电网规划设计、综合评价等研究工作;|程浩忠(1962),男,博士,教授,博士生导师,主要研究方向为电力系统规划、电压稳定、综合能源系统;|张沈习(1988),男,博士,副研究员,硕士生导师,主要研究方向为电力系统规划、综合能源系统。
基金资助:
国家自然科学基金项目(U1966206);国家自然科学基金项目(51907123)

Review and Prospect of Integrated Energy System Planning Considering the Integration of Renewable Energy

PAN Ersheng¹, SONG Yi¹, YUAN Kai¹, GUO Yue¹, CHENG Haozhong², ZHANG Shenxi²

1. State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209,China
2. Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education(Shanghai Jiao Tong University), Shanghai 200240, China

Received:2020-08-10 Online:2020-12-01 Published:2020-12-04
Supported by:
National Natural Science Foundation of China(U1966206);National Natural Science Foundation of China(51907123)

摘要/Abstract

摘要：

建设多能耦合的综合能源系统是解决可再生能源消纳问题的有效途径之一。可再生能源的接入大大增强了综合能源系统的不确定性,如何合理分析并应对不确定性带来的影响是综合能源系统规划研究中的重要课题。文章首先总结了可再生能源接入下综合能源系统的典型结构。然后,梳理了综合能源系统多能负荷预测方法和多能流分析技术的研究成果,进一步从能源站规划、能源网络规划和站网联合规划3个方面归纳总结了考虑可再生能源接入的综合能源系统规划研究进展。最后,从可再生能源消纳新场景探索、考虑可再生能源接入的多能流分析技术、考虑多重不确定性的综合能源系统规划和考虑多能需求侧管理的综合能源系统规划4个角度展望了未来可能的研究方向。

关键词: 综合能源系统, 规划, 可再生能源, 不确定性

Abstract:

The integrated energy system is an effective approach to accommodate renewable energy. Meanwhile, the integration of renewable energy increases the uncertainties of integrated energy systems. To reasonably analyze and deal with the impact of uncertainty is an important issue in the study of integrated energy system planning. Firstly, this paper introduces the typical configuration of integrated energy systems with penetration of renewable energy. Then, current research on multi-energy forecasting methods and technologies of multi-energy flow analysis are illustrated. Furthermore, this paper summarizes the research on integrated energy system planning considering the integration of renewable energy, including energy station planning, energy network planning and joint planning of station and network. At last, the future study directions are prospected from the aspects of new scenes of accommodating renewable energy, multi-energy flow analysis technologies and integrated energy system planning considering multiple uncertainties or multi-energy demand-side management.

Key words: integrated energy system, planning, renewable energy, uncertainties

中图分类号:

TM715

潘尔生, 宋毅, 原凯, 郭玥, 程浩忠, 张沈习. 考虑可再生能源接入的综合能源系统规划评述与展望[J]. 电力建设, 2020, 41(12): 3-13.

PAN Ersheng, SONG Yi, YUAN Kai, GUO Yue, CHENG Haozhong, ZHANG Shenxi. Review and Prospect of Integrated Energy System Planning Considering the Integration of Renewable Energy[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(12): 3-13.

图/表 5

图1 典型综合能源系统结构

Fig.1 Typical structure of the integrated energy system

表1 三种负荷预测思路对比

Table 1 Comparison among three load forecasting methods

表2 综合能源系统节点分类

Table 2 Node types of integrated energy systems

表3 概率多能流计算方法对比

Table 3 Comparison among calculation methods of probabilistic multi-energy flow

表4 综合能源系统规划模型求解策略

Table 4 Solving strategies of the planning model of integrated energy system

参考文献 92

[1]	杨经纬, 张宁, 王毅, 等. 面向可再生能源消纳的多能源系统: 述评与展望[J]. 电力系统自动化, 2018,42(4):11-24.
	YANG Jingwei, ZHANG Ning, WANG Yi, et al. Multi-energy system towards renewable energy accommodation: Review and prospect[J]. Automation of Electric Power Systems, 2018,42(4):11-24.
[2]	吴建中. 欧洲综合能源系统发展的驱动与现状[J]. 电力系统自动化, 2016,40(5):1-7.
	WU Jianzhong. Drivers and state-of-the-art of integrated energy systems in Europe[J]. Automation of Electric Power Systems, 2016,40(5):1-7.
[3]	王伟亮, 王丹, 贾宏杰, 等. 能源互联网背景下的典型区域综合能源系统稳态分析研究综述[J]. 中国电机工程学报, 2016,36(12):3292-3306. doi: 10.13334/j.0258-8013.pcsee.152858 URL
	WANG Weiliang, WANG Dan, JIA Hongjie, et al. Review of steady-state analysis of typical regional integrated energy system under the background of energy Internet[J]. Proceedings of the CSEE, 2016,36(12):3292-3306.
[4]	LI Z K, KHREBTOVA T, ZHAO N, et al. Bi-level service restoration strategy for active distribution system considering different types of energy supply sources[J]. IET Generation, Transmission & Distribution, 2020,14(19):4186-4194.
[5]	ZHANG Z Y, ZHANG Y, HUANG Q, et al. Market-oriented optimal dispatching strategy for a wind farm with a multiple stage hybrid energy storage system[J]. CSEE Journal of Power and Energy Systems, 2018,4(4):417-424. doi: 10.17775/CSEEJPES URL
[6]	SAMAD T, KOCH E, STLUKA P. Automated demand response for smart buildings and microgrids: The state of the practice and research challenges[J]. Proceedings of the IEEE, 2016,104(4):726-744. doi: 10.1109/JPROC.2016.2520639 URL
[7]	WANG Y, CHEN Q X, ZHANG N, et al. Conditional residual modeling for probabilistic load forecasting[J]. IEEE Transactions on Power Systems, 2018,33(6):7327-7330. doi: 10.1109/TPWRS.2018.2868167 URL
[8]	MARRA F, YANG G Y, FAWZY Y T, et al. Improvement of local voltage in feeders with photovoltaic using electric vehicles[J]. IEEE Transactions on Power Systems, 2013,28(3):3515-3516. doi: 10.1109/TPWRS.2013.2248959 URL
[9]	郭祚刚, 雷金勇, 马溪原, 等. 大规模综合能源系统电-气-热多能潮流建模与计算方法[J]. 电力系统及其自动化学报, 2019,31(10):96-102.
	GUO Zuogang, LEI Jinyong, MA Xiyuan, et al. Modeling and calculation methods for multi-energy flows in large-scale integrated energy system containing electricity, gas, and heat[J]. Proceedings of the CSU-EPSA, 2019,31(10):96-102.
[10]	骆柏锋, 穆云飞, 赵波, 等. 基于统一潮流模型的电-气耦合综合能源系统静态灵敏度分析[J]. 电力系统自动化, 2018,42(13):29-35.
	LUO Bofeng, MU Yunfei, ZHAO Bo, et al. Static sensitivity analysis of integrated electricity and gas system based on unified power flow model[J]. Automation of Electric Power Systems, 2018,42(13):29-35.
[11]	刘涤尘, 马恒瑞, 王波, 等. 含冷热电联供及储能的区域综合能源系统运行优化[J]. 电力系统自动化, 2018,42(4):113-120, 141.
	LIU Dichen, MA Hengrui, WANG Bo, et al. Operation optimization of regional integrated energy system with CCHP and energy storage system[J]. Automation of Electric Power Systems, 2018,42(4):113-120, 141.
[12]	李正茂, 张峰, 梁军, 等. 含电热联合系统的微电网运行优化[J]. 中国电机工程学报, 2015,35(14):3569-3576. doi: 10.13334/j.0258-8013.pcsee.2015.14.011 URL
	LI Zhengmao, ZHANG Feng, LIANG Jun, et al. Optimization on microgrid with combined heat and power system[J]. Proceedings of the CSEE, 2015,35(14):3569-3576.
[13]	LI Z M, XU Y. Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes[J]. Applied Energy, 2018,210:974-986. doi: 10.1016/j.apenergy.2017.08.197 URL
[14]	易文飞, 俞永增, 张艺伟, 等. 基于p-中位模型的区域综合能源系统能源站优化规划[J]. 电力系统自动化, 2019,43(4):107-113.
	YI Wenfei, YU Yongzeng, ZHANG Yiwei, et al. P-median model based optimal planning of energy station for regional integrated energy systems[J]. Automation of Electric Power Systems, 2019,43(4):107-113.
[15]	王李龑, 许强, 黄开艺, 等. 计及新能源及负荷不确定性的多能微网系统两阶段随机规划方法[J]. 电力建设, 2020,41(4):100-108.
	WANG Liyan, XU Qiang, HUANG Kaiyi, et al. A two-stage stochastic programming method for multi-energy microgrid system considering the uncertainty of new energy and load[J]. Electric Power Construction, 2020,41(4):100-108.
[16]	CLEGG S, MANCARELLA P. Integrated electrical and gas network flexibility assessment in low-carbon multi-energy systems[J]. IEEE Transactions on Sustainable Energy, 2016,7(2):718-731. doi: 10.1109/TSTE.2015.2497329 URL
[17]	程浩忠, 李隽, 吴耀武, 等. 考虑高比例可再生能源的交直流输电网规划挑战与展望[J]. 电力系统自动化, 2017,41(9):19-27.
	CHENG Haozhong, LI Jun, WU Yaowu, et al. Challenges and prospects for AC/DC transmission expansion planning considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017,41(9):19-27.
[18]	张涌新, 沈弘, 马静. 综合能源系统负荷特性分析及应用研究[J]. 电力建设, 2018,39(9):18-29.
	ZHANG Yongxin, SHEN Hong, MA Jing. Load characteristic analysis and application research on integrated energy system[J]. Electric Power Construction, 2018,39(9):18-29.
[19]	赵峰, 孙波, 张承慧. 基于多变量相空间重构和卡尔曼滤波的冷热电联供系统负荷预测方法[J]. 中国电机工程学报, 2016,36(2):399-406.
	ZHAO Feng, SUN Bo, ZHANG Chenghui. Cooling, heating and electrical load forecasting method for CCHP system based on multivariate phase space reconstruction and Kalman filter[J]. Proceedings of the CSEE, 2016,36(2):399-406.
[20]	VAGHEFI A, JAFARI M A, BISSE E, et al. Modeling and forecasting of cooling and electricity load demand[J]. Applied Energy, 2014,136:186-196.
[21]	史佳琪, 谭涛, 郭经, 等. 基于深度结构多任务学习的园区型综合能源系统多元负荷预测[J]. 电网技术, 2018,42(3):698-707.
	SHI Jiaqi, TAN Tao, GUO Jing, et al. Multi-task learning based on deep architecture for various types of load forecasting in regional energy system integration[J]. Power System Technology, 2018,42(3):698-707.
[22]	翟晶晶, 吴晓蓓, 王力立. 基于径向基函数神经网络的综合能源系统多元负荷短期预测[J]. 电力需求侧管理, 2019,21(4):23-27, 34.
	ZHAI Jingjing, WU Xiaobei, WANG Lili. Multiple short-term load forecasting in integrated energy system based on RBF-NN model[J]. Power Demand Side Management, 2019,21(4):23-27, 34.
[23]	栗然, 孙帆, 丁星, 等. 考虑多能时空耦合的用户级综合能源系统超短期负荷预测方法[J]. 电网技术, 2020,44(11):4121-4131.
	LI Ran, SUN Fan, DING Xing, et al. Ultra short-term load forecasting method for user-level integrated energy system considering spatio-temporal coupling of multi-energy[J]. Power System Technology, 2020,44(11):4121-4131.
[24]	田浩含, 撖奥洋, 于立涛, 等. 基于GRA-LSTM神经网络的区域综合能源系统多元负荷短期预测模型[J]. 广东电力, 2020,33(5):44-51.
	TIAN Haohan, HAN Aoyang, YU Litao, et al. Research on multi-load short-term forecasting model of regional integrated energy system based on GRA-LSTM neural network[J]. Guangdong Electric Power, 2020,33(5):44-51.
[25]	乔彦哲, 颜宁, 马少华, 等. 考虑多能互补的综合能源系统联合规划及发展综述[J]. 电器与能效管理技术, 2019(19):15-22.
	QIAO Yanzhe, YAN Ning, MA Shaohua, et al. Summary of joint planning and development of integrated energy system considering multi-energy complementarity[J]. Electrical & Energy Management Technology, 2019(19):15-22.
[26]	LI Z, WANG C F, LI B W, et al. Probability-interval-based optimal planning of integrated energy system with uncertain wind power[J]. IEEE Transactions on Industry Applications, 2020,56(1):4-13.
[27]	YANG H Z, LI M L, JIANG Z Y, et al. Multi-time scale optimal scheduling of regional integrated energy systems considering integrated demand response[J]. IEEE Access, 2020,8:5080-5090.
[28]	袁智勇, 赵懿祺, 郭祚刚, 等. 面向能源互联网的综合能源系统规划研究综述[J]. 南方电网技术, 2019,13(7):1-9.
	YUAN Zhiyong, ZHAO Yiqi, GUO Zuogang, et al. Research summary of integrated energy systems planning for energy Internet[J]. Southern Power System Technology, 2019,13(7):1-9.
[29]	YU Y, ZHANG T Y, DU Y Z, et al. Energy hub model for energy management in energy Internet[J]. The Journal of Engineering, 2019,2019(9):5432-5438.
[30]	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.
[31]	王伟亮, 王丹, 贾宏杰, 等. 考虑天然气网络状态的电力-天然气区域综合能源系统稳态分析[J]. 中国电机工程学报, 2017,37(5):1293-1305.
	WANG Weiliang, WANG Dan, JIA Hongjie, et al. Steady state analysis of electricity-gas regional integrated energy system with consideration of NGS network status[J]. Proceedings of the CSEE, 2017,37(5):1293-1305.
[32]	WANG Y, ZHANG N, KANG C Q, et al. Standardized matrix modeling of multiple energy systems[J]. IEEE Transactions on Smart Grid, 2019,10(1):257-270.
[33]	FANG J K, ZENG Q, AI X M, et al. Dynamic optimal energy flow in the integrated natural gas and electrical power systems[J]. IEEE Transactions on Sustainable Energy, 2018,9(1):188-198.
[34]	PAMBOUR K A, BOLADO-LAVIN R, DIJKEMA G P J. An integrated transient model for simulating the operation of natural gas transport systems[J]. Journal of Natural Gas Science and Engineering, 2016,28:672-690. doi: 10.1016/j.jngse.2015.11.036 URL
[35]	CHACZYKOWSKI M. Transient flow in natural gas pipeline :The effect of pipeline thermal model[J]. Applied Mathematical Modelling, 2010,34(4):1051-1067. doi: 10.1016/j.apm.2009.07.017 URL
[36]	DE WOLF D, SMEERS Y. The gas transmission problem solved by an extension of the simplex algorithm[J]. Management Science, 2000,46(11):1454-1465.
[37]	顾伟, 陆帅, 王珺, 等. 多区域综合能源系统热网建模及系统运行优化[J]. 中国电机工程学报, 2017,37(5):1305-1316.
	GU Wei, LU Shuai, WANG Jun, et al. Modeling of the heating network for multi-district integrated energy system and its operation optimization[J]. Proceedings of the CSEE, 2017,37(5):1305-1316.
[38]	姚帅, 顾伟, 张雪松, 等. 热网特性对于综合能源系统超短期调度的影响[J]. 电力系统自动化, 2018,42(14):83-90.
	YAO Shuai, GU Wei, ZHANG Xuesong, et al. Effect of heating network characteristics on ultra-short-term scheduling of integrated energy system[J]. Automation of Electric Power Systems, 2018,42(14):83-90.
[39]	YAO Shuai, GU Wei, LU Shuai, et al. A transient thermodynamic model of district heating network for operational optimization of the energy integration system [C]//2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). Beijing, China: IEEE, 2017: 1-6.
[40]	BENONYSSON A. Dynamic modelling and operational optimization of district heating systems, dissertation[D]. Copenhagen, Denmark:Technical University of Denmark, 1991.
[41]	LI Z G, WU W C, SHAHIDEHPOUR M, et al. Combined heat and power dispatch considering pipeline energy storage of district heating network[J]. IEEE Transactions on Sustainable Energy, 2016,7(1):12-22. doi: 10.1109/TSTE.2015.2467383 URL
[42]	WANG Y R, YOU S J, ZHANG H, et al. Thermal transient prediction of district heating pipeline: Optimal selection of the time and spatial steps for fast and accurate calculation[J]. Applied Energy, 2017,206:900-910.
[43]	ZENG Q, FANG J K, LI J H, et al. Steady-state analysis of the integrated natural gas and electric power system with bi-directional energy conversion[J]. Applied Energy, 2016,184:1483-1492.
[44]	LIU W J, LI P Y, YANG W T, et al. Optimal energy flow for integrated energy systems considering gas transients[J]. IEEE Transactions on Power Systems, 2019,34(6):5076-5079. doi: 10.1109/TPWRS.59 URL
[45]	PAN Z G, GUO Q L, SUN H B. Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow[J]. Applied Energy, 2016,167:230-243. doi: 10.1016/j.apenergy.2015.10.095 URL
[46]	MARTINEZ-MARES A, FUERTE-ESQUIVEL C R. A unified gas and power flow analysis in natural gas and electricity coupled networks[J]. IEEE Transactions on Power Systems, 2012,27(4):2156-2166. doi: 10.1109/TPWRS.2012.2191984 URL
[47]	孙国强, 陈霜, 卫志农, 等. 计及相关性的电-气互联系统概率最优潮流[J]. 电力系统自动化, 2015,39(21):11-17.
	SUN Guoqiang, CHEN Shuang, WEI Zhinong, et al. Probabilistic optimal power flow of combined natural gas and electric system considering correlation[J]. Automation of Electric Power Systems, 2015,39(21):11-17.
[48]	HU Y, LIAN H R, BIE Z H, et al. Unified probabilistic gas and power flow[J]. Journal of Modern Power Systems and Clean Energy, 2017,5(3):400-411.
[49]	WANG Z, ALVARADO F L. Interval arithmetic in power flow analysis[J]. IEEE Transactions on Power Systems, 1991,7(3):1341-1349.
[50]	张儒峰, 姜涛, 李国庆, 等. 基于最大熵原理的电-气综合能源系统概率能量流分析[J]. 中国电机工程学报, 2019,39(15):4430-4441.
	ZHANG Rufeng, JIANG Tao, LI Guoqing, et al. Maximum entropy based probabilistic energy flow calculation for integrated electricity and natural gas systems[J]. Proceedings of the CSEE, 2019,39(15):4430-4441.
[51]	陈璨, 吴文传, 张伯明, 等. 考虑光伏出力相关性的配电网概率潮流[J]. 电力系统自动化, 2015,39(9):41-47.
	CHEN Can, WU Wenchuan, ZHANG Boming, et al. Probabilistic load flow of distribution network considering correlated photovoltaic power output[J]. Automation of Electric Power Systems, 2015,39(9):41-47.
[52]	CHEN Y, WEN J Y, CHENG S J. Probabilistic load flow method based on nataf transformation and Latin hypercube sampling[J]. IEEE Transactions on Sustainable Energy, 2013,4(2):294-301.
[53]	HU X Y, ZHAO X, FENG X X. Probabilistic-interval energy flow analysis of regional integrated electricity and gas system considering multiple uncertainties and correlations[J]. IEEE Access, 2019,7:178209-178223. doi: 10.1109/Access.6287639 URL
[54]	WIDEN J, SHEPERO M, MUNKHAMMAR J. Probabilistic load flow for power grids with high PV penetrations using copula-based modeling of spatially correlated solar irradiance[J]. IEEE Journal of Photovoltaics, 2017,7(6):1740-1745. doi: 10.1109/JPHOTOV.2017.2749004 URL
[55]	XIE Z Q, JI T Y, LI M S, et al. Quasi-Monte Carlo based probabilistic optimal power flow considering the correlation of wind speeds using copula function[J]. IEEE Transactions on Power Systems, 2018,33(2):2239-2247.
[56]	胡枭, 尚策, 程浩忠, 等. 综合能源系统能流计算方法述评与展望[J]. 电力系统自动化, 2020,44(18):179-191.
	HU Xiao, SHANG Ce, CHENG Haozhong, et al. Review and prospect of calculation method for energy flow in integrated energy system[J]. Automation of Electric Power Systems, 2020,44(18):179-191.
[57]	刘宇, 高山, 杨胜春, 等. 电力系统概率潮流算法综述[J]. 电力系统自动化, 2014,38(23):127-135. doi: 10.7500/AEPS20131014017 URL
	LIU Yu, GAO Shan, YANG Shengchun, et al. Review on algorithms for probabilistic load flow in power system[J]. Automation of Electric Power Systems, 2014,38(23):127-135. doi: 10.7500/AEPS20131014017 URL
[58]	CHEN S, WEI Z N, SUN G Q, et al. Multi-linear probabilistic energy flow analysis of integrated electrical and natural-gas systems[J]. IEEE Transactions on Power Systems, 2017,32(3):1970-1979. doi: 10.1109/TPWRS.2016.2597162 URL
[59]	车玉龙, 吕晓琴, 王晓茹, 等. 含非正态分布概率潮流计算的改进型两点估计法[J]. 电力自动化设备, 2019,39(12):128-133.
	CHE Yulong, LÜ Xiaoqin, WANG Xiaoru, et al. Improved two point estimation method for probabilistic power flow calculation with non-normal distribution[J]. Electric Power Automation Equipment, 2019,39(12):128-133.
[60]	ZENG B, ZHU X, CHEN C, et al. Unified probabilistic energy flow analysis for electricity-gas coupled systems with integrated demand response[J]. IET Generation, Transmission & Distribution, 2019,13(13):2697-2710.
[61]	陈胜, 卫志农, 孙国强, 等. 电-气混联综合能源系统概率能量流分析[J]. 中国电机工程学报, 2015,35(24):6331-6340.
	CHEN Sheng, WEI Zhinong, SUN Guoqiang, et al. Probabilistic energy flow analysis in integrated electricity and natural-gas energy systems[J]. Proceedings of the CSEE, 2015,35(24):6331-6340.
[62]	杨家豪. 区域综合能源系统冷-热-电-气概率多能流计算[J]. 电网技术, 2019,43(1):74-83.
	YANG Jiahao. Probabilistic multi-energy flow calculation for regional integrated energy system containing cooling, heating, electricity and gas[J]. Power System Technology, 2019,43(1):74-83.
[63]	曾博, 胡强, 刘裕, 等. 考虑需求响应复杂不确定性的电-气互联系统动态概率能流计算[J]. 中国电机工程学报, 2020,40(4):1161-1171, 1408.
	ZENG Bo, HU Qiang, LIU Yu, et al. Dynamic probabilistic energy flow calculation for interconnected electricity-gas system considering complex uncertainties of demand response[J]. Proceedings of the CSEE, 2020,40(4):1161-1171, 1408.
[64]	HU Y, LIAN H R, BIE Z H, et al. Unified probabilistic gas and power flow[J]. Journal of Modern Power Systems and Clean Energy, 2017,5(3):400-411.
[65]	廖星星, 吴奕, 卫志农, 等. 基于GMM及多点线性半不变量法的电-热互联综合能源系统概率潮流分析[J]. 电力自动化设备, 2019,39(8):55-62.
	LIAO Xingxing, WU Yi, WEI Zhinong, et al. Probabilistic power flow analysis of integrated electricity-heat energy system based on GMM and multi-point linear cumulant methond[J]. Electric Power Automation Equipment, 2019,39(8):55-62.
[66]	黎晨阳, 张沈习, 程浩忠, 等. 计及相关性的电-气互联区域综合能源系统概率多能流计算[J]. 电力系统自动化, 2020,44(21):42-49.
	LI Chenyang, ZHANG Shenxi, CHENG Haozhong, et al. Correlation-based probabilistic multi-energy flow calculation of regional integrated energy system with combined electricity and natural gas[J]. Automation of Electric Power Systems, 2020,44(21):42-49.
[67]	DING T, LI X, LI F X, et al. Interval radial power flow using extended DistFlow formulation and Krawczyk iteration method with sparse approximate inverse preconditioner[J]. IET Generation, Transmission & Distribution, 2015,9(14):1998-2006.
[68]	TANG K J, DONG S F, ZHU C Z, et al. Affine arithmetic-based coordinated interval power flow of integrated transmission and distribution networks[J]. IEEE Transactions on Smart Grid, 2020,11(5):4116-4132. doi: 10.1109/TSG.5165411 URL
[69]	ZHANG C, CHEN H Y, GUO M L, et al. DC power flow analysis incorporating interval input data and network parameters through the optimizing-scenarios method[J]. International Journal of Electrical Power & Energy Systems, 2018,96:380-389.
[70]	伍惠铖, 王淳, 刘宽, 等. 电-热综合能源系统能流的区间计算算法[J]. 电网技术, 2019,43(1):91-99.
	WU Huicheng, WANG Chun, LIU Kuan, et al. An interval energy flow calculation method for integrated electro-thermal energy system[J]. Power System Technology, 2019,43(1):91-99.
[71]	QIAO Z, GUO Q L, SUN H B, et al. An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power[J]. Applied Energy, 2017,201:343-353.
[72]	赵霞, 胡潇云, 杨仑, 等. 考虑参数不确定性的区域电-气联合系统的概率-模糊能流评估[J]. 电力自动化设备, 2019,39(2):135-142.
	ZHAO Xia, HU Xiaoyun, YANG Lun, et al. Probabilistic-possibilistic energy flow evaluation of regional electricity-gas integrated system considering parameter uncertainties[J]. Electric Power Automation Equipment, 2019,39(2):135-142.
[73]	郭创新, 王惠如, 张伊宁, 等. 面向区域能源互联网的"源-网-荷"协同规划综述[J]. 电网技术, 2019,43(9):3071-3080.
	GUO Chuangxin, WANG Huiru, ZHANG Yining, et al. Review of “source-grid-load” co-planning orienting to regional energy Internet[J]. Power System Technology, 2019,43(9):3071-3080.
[74]	管霖, 陈鹏, 唐宗顺, 等. 考虑冷热电存储的区域综合能源站优化设计方法[J]. 电网技术, 2016,40(10):2934-2943.
	GUAN Lin, CHEN Peng, TANG Zongshun, et al. Integrated energy station design considering cold and heat storage[J]. Power System Technology, 2016,40(10):2934-2943.
[75]	张磊. 综合能源系统中热电联产机组的定容选址[D]. 长沙: 湖南大学, 2018.
	ZHANG Lei. Siting and sizing of CHP unit in integrated energy system[D]. Changsha: Hunan University, 2018.
[76]	胡源, 别朝红, 李更丰, 等. 天然气网络和电源、电网联合规划的方法研究[J]. 中国电机工程学报, 2017,37(1):45-54.
	HU Yuan, BIE Zhaohong, LI Gengfeng, et al. Integrated planning of natural gas network and composite power system[J]. Proceedings of the CSEE, 2017,37(1):45-54.
[77]	雷霞, 唐文左, 李逐云, 等. 考虑区域综合能源系统优化运行的配电网扩展规划[J]. 电网技术, 2018,42(11):3459-3470.
	LEI Xia, TANG Wenzuo, LI Zhuyun, et al. Distribution network expansion planning considering optimal operation of regional integrated energy system[J]. Power System Technology, 2018,42(11):3459-3470.
[78]	张浩禹, 邱晓燕, 周晟锐, 等. 基于机会约束目标规划的多电-气互联综合能源系统分布式优化模型[J]. 电力建设, 2020,41(7):82-91.
	ZHANG Haoyu, QIU Xiaoyan, ZHOU Shengrui, et al. Distributed optimal dispatch based on chance constrained goal programming for multi-area integrated electricity-natural gas energy systems[J]. Electric Power Construction, 2020,41(7):82-91.
[79]	史昭娣, 王伟胜, 黄越辉, 等. 考虑决策相关随机规划的光热电站容量配置[J/OL]. 中国电机工程学报, (2020-05-27)[2020-07-01]. http://kns.cnki.net/kcms/detail/11.2107.TM.20200526.1453.006.html.
	ZHANG Haoyu, QIU Xiaoyan, ZHOU Shengrui, et al. Capacity optimization of concentrating solar power plant based on decision-dependent stochastic programming[J/OL]. Proceedings of the CSEE,(2020-05-27) [2020-07-01]. http://kns.cnki.net/kcms/detail/11.2107.TM.20200526.1453.006.html.
[80]	朱兰, 王吉, 唐陇军, 等. 计及电转气精细化模型的综合能源系统鲁棒随机优化调度[J]. 电网技术, 2019,43(1):116-126.
	ZHU Lan, WANG Ji, TANG Longjun, et al. Robust stochastic optimal dispatching of integrated energy systems considering refined power-to-gas model[J]. Power System Technology, 2019,43(1):116-126.
[81]	王一家, 董朝阳, 徐岩, 等. 利用电转气技术实现可再生能源的大规模存储与传输[J]. 中国电机工程学报, 2015,35(14):3586-3595. doi: 10.13334/j.0258-8013.pcsee.2015.14.013 URL
	WANG Yijia, DONG Zhaoyang, XU Yan, et al. Enabling large-scale energy storage and renewable energy grid connectivity: A power-to-gas approach[J]. Proceedings of the CSEE, 2015,35(14):3586-3595.
[82]	刘天琪, 曾红, 何川, 等. 考虑电转气设备和风电场协同扩建的气电互联综合能源系统规划[J]. 电力自动化设备, 2019,39(8):144-151.
	LIU Tianqi, ZENG Hong, HE Chuan, et al. Planning of integrated gas and electricity system considering coordinated expansion of power-to-gas facilities and wind farms[J]. Electric Power Automation Equipment, 2019,39(8):144-151.
[83]	高滢, 王芃, 薛友, 等. 计及需求侧管理的电-气集成能源系统协同规划[J]. 电力系统自动化, 2018,42(13):3-11.
	GAO Ying, WANG Peng, XUE You, et al. Collaborative planning of integrated electricity-gas energy systems considering demand side management[J]. Automation of Electric Power Systems, 2018,42(13):3-11.
[84]	黄武靖, 张宁, 董瑞彪, 等. 多能源网络与能量枢纽联合规划方法[J]. 中国电机工程学报, 2018,38(18):5425-5437.
	HUANG Wujing, ZHANG Ning, DONG Ruibiao, et al. Coordinated planning of multiple energy networks and energy hubs[J]. Proceedings of the CSEE, 2018,38(18):5425-5437.
[85]	周贤正, 陈玮, 郭创新. 考虑供能可靠性与风光不确定性的城市多能源系统规划[J]. 电工技术学报, 2019,34(17):3672-3686.
	ZHOU Xianzheng, CHEN Wei, GUO Chuangxin. An urban multi-energy system planning method incorporating energy supply reliability and wind-photovoltaic generators uncertainty[J]. Transactions of China Electrotechnical Society, 2019,34(17):3672-3686.
[86]	李哲, 王成福, 梁军, 等. 计及风电不确定性的电-气-热综合能源系统扩展规划方法[J]. 电网技术, 2018,42(11):3477-3487.
	LI Zhe, WANG Chengfu, LIANG Jun, et al. Expansion planning method of integrated energy system considering uncertainty of wind power[J]. Power System Technology, 2018,42(11):3477-3487.
[87]	王祺, 王承民, 谢宁, 等. 混合CVaR-IGDT的区域综合能源系统扩展规划模型[J]. 电网技术, 2020,44(2):505-515.
	WANG Qi, WANG Chengmin, XIE Ning, et al. A hybrid CVaR-IGDT expansion planning model for regional integrated energy system[J]. Power System Technology, 2020,44(2):505-515.
[88]	QIU J, DONG Z Y, ZHAO J H, et al. Multi-stage flexible expansion co-planning under uncertainties in a combined electricity and gas market[J]. IEEE Transactions on Power Systems, 2015,30(4):2119-2129. doi: 10.1109/TPWRS.2014.2358269 URL
[89]	于波, 孙恒楠, 项添春, 等. 综合能源系统规划设计方法[J]. 电力建设, 2016,37(2):78-84. doi: 10.3969/j.issn.1000-7229.2016.02.011 URL
	YU Bo, SUN Hengnan, XIANG Tianchun, et al. Planning design method of integrated energy system[J]. Electric Power Construction, 2016,37(2):78-84. doi: 10.3969/j.issn.1000-7229.2016.02.011 URL
[90]	HAMDY M, PALONEN M, HASAN A. Implementation of Pareto-archive NSGA-II algorithms to a nearly-zero-energy building optimization problem, [C]// First Building Simulation and Optimization Conference, September 10-11, 2012. Loughborough, UK: 181-188.
[91]	WANG H Z, ZHANG R Q, PENG J C, et al. GPNBI-inspired MOSFA for Pareto operation optimization of integrated energy system[J]. Energy Conversion and Management, 2017,151:524-537. doi: 10.1016/j.enconman.2017.09.005 URL
[92]	王丹, 孟政吉, 贾宏杰, 等. 面向新型城镇的能源互联系统规划关键技术研究及展望[J]. 电力系统自动化, 2019,43(14):16-28.
	WANG Dan, MENG Zhengji, JIA Hongjie, et al. Research and prospect of key technologies for energy interconnection system planning for new-type towns[J]. Automation of Electric Power Systems, 2019,43(14):16-28.

考虑可再生能源接入的综合能源系统规划评述与展望

Review and Prospect of Integrated Energy System Planning Considering the Integration of Renewable Energy

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