Power flow models and calculation methods applied in integrated energy systems

doi:10.3969/j.issn.2097-0706.2023.10.009

Abstract

Abstract:

Multi-energy flow analysis is a crucial and fundamental link for the state estimation，security analysis and optimal regulation of an integrated energy system（IES）. To study the mutual conversion and coupling of electric power，gas，thermal power and cold energy with power flow analysis，two main research directions of integrated energy system power flow analysis are compared. The first one is to calculate the system's operating state，including steady-state and dynamic power flow，based on known parameters under a certain operating condition.On this basis， the second one considers the impact of uncertain parameters on system operation，and study the uncertain power flow through probabilistic power flow analysis.The research progress made in multi-energy hybrid flow and limitations of current decoupling methods are pointed out，and the optimal power flow solution and its applications are summarized. The results show that the multi-energy steady-state flow calculation is relatively mature，but the dynamic power flow model mostly solved by the differential method lacks accuracy and solution efficiency.Uncertainty power flow requires highly on data and cannot balance computing accuracy and efficiency.The optimal power flow model mainly focuses on single-objective optimization，while seldom considers multiple objectives or uncertain factors.Finally，the limitations of hybrid energy power flow calculation in terms of its model constraints and algorithm complexity are proposed，and its prospects are made.

Key words: integrated energy system, power grid power flow model, steady-state flow, dynamic flow, combined heating and power, power to heat, power to gas, gas turbine, lithium bromide refrigerator, energy hub model

CLC Number:

TM744：TK01

WU Dongye, YANG Di, JIN Xu, HONG Wenpeng, YE Shaoyi, ZHAO Xiaoming. Power flow models and calculation methods applied in integrated energy systems[J]. Integrated Intelligent Energy, 2023, 45(10): 70-81.

Figures/Tables 3

Fig.1

Table 1

Table 2

References 68

[1]	张沈习, 王丹阳, 程浩忠, 等. 双碳目标下低碳综合能源系统规划关键技术及挑战[J]. 电力系统自动化, 2022, 46(8):189-207.
	ZHANG Shenxi, WANG Danyang, CHENG Haozhong, et al. Key technologies and challenges of low-carbon integrated energy system planning for carbon emission peak and carbon neutrality[J]. Automation of Electric Power Systems, 2022, 46(8):189-207.
[2]	孙宏斌, 潘昭光, 郭庆来. 多能流能量管理研究:挑战与展望[J]. 电力系统自动化, 2016, 40(15):1-8,16.
	SUN Hongbin, PAN Zhaoguang, GUO Qinglai. Energy management for multi-energy flow:Challenges and prospects[J]. Automation of Electric Power Systems, 2016, 40(15):1-8,16.
[3]	ZHU M, XU C, DONG S, et al. An integrated multi-energy flow calculation method for electricity-gas-thermal integrated energy systems[J]. Protection and Control of Modern Power Systems, 2021,(6):1-12.
[4]	黎静华, 黄玉金, 张鹏. 综合能源系统多能流潮流计算模型与方法综述[J]. 电力建设, 2018, 39(3):1-11. doi: DOI： 10.3969/j.issn.1000－7229.2018.03.001
	LI Jinghua, HUANG Yujin, ZHANG Peng. Review of multi-energy flow calculation model and method in integrated energy system[J]. Electric Power Construction, 2018, 39(3):1-11. doi: DOI： 10.3969/j.issn.1000－7229.2018.03.001
[5]	陈思宇, 柴庆宣, 李延松, 等. 综合能源系统潮流及最优潮流计算模型与方法综述[J]. 热力发电, 2020, 49(7):1-12,20.
	CHEN Siyu, CHAI Qingxuan, LI Yansong, et al. Models and methods of power flow and optimal power flow calculation for integrated energy system:A review[J]. Thermal Power Generation, 2020, 49(7):1-12,20.
[6]	GUO S, SONG G, LI M, et al. Multi-objective bi-level quantity regulation scheduling method for electric-thermal integrated energy system considering thermal and hydraulic transient characteristics[J]. Energy Conversion and Management, 2022, 253:115147. doi: 10.1016/j.enconman.2021.115147
[7]	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.
[8]	陈皓勇, 李明, 邱明, 等. 时变能量网络建模与分析[J]. 中国科学:技术科学, 2019, 49(3):243-254.
	CHEN Haoyong, LI Ming, QIU Ming, et al. Modeling and analysis of time-varying energy network[J]. Scientia Sinica (Technologica), 2019, 49(3):243-254.
[9]	MAN L, WANG T, PAN X, et al. State estimation for integrated energy system containing electricity,heat and gas[C]// 2018 2nd IEEE Conference on Energy Internet and Energy System Integration(EI2).IEEE, 2018:1-6.
[10]	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.
[11]	丁曦, 姜威, 郭创新, 等. 考虑需求响应的电/热/气云储能优化配置策略[J]. 电力建设, 2022, 43(3):83-99. doi: 10.12204/j.issn.1000-7229.2022.03.010
	DING Xi, JIANG Wei, GUO Chuangxin, et al. Optimal configuration of electricity-heat-gas cloud energy storage considering demand response[J]. Electric Power Construction, 2022, 43(3):83-99. doi: 10.12204/j.issn.1000-7229.2022.03.010
[12]	TAN H, YAN W, REN Z, et al. A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response[J]. Energy, 2022, 239:121875. doi: 10.1016/j.energy.2021.121875
[13]	BLOESS A, SCHILL W P, ZERRAHN A. Power-to-heat for renewable energy integration:A review of technologies,modeling approaches,and flexibility potentials[J]. Applied Energy, 2018, 212:1611-1626. doi: 10.1016/j.apenergy.2017.12.073
[14]	KANG L G, WANG J Z, YUAN X X, et al. Research on energy management of integrated energy system coupled with organic Rankine cycle and power to gas[J]. Energy Conversion and Management, 2023, 287:117117. doi: 10.1016/j.enconman.2023.117117
[15]	秦文萍, 逯瑞鹏, 高蒙楠, 等. 计及大规模新能源接入的电-气耦合综合能源系统稳定性评估[J]. 电网技术, 2020, 44(5):1880-1891.
	QIN Wenping, LU Ruipeng, GAO Mengnan, et al. Stability assessment of electro-gas coupled integrated energy system considering large-scale new energy access[J]. Power System Technology, 2020, 44(5):1880-1891.
[16]	黄雨佳, 孙秋野, 王睿, 等. 面向综合能源系统的静态电压稳定性分析[J]. 中国电机工程学报, 2019, 39(S1):44-53.
	HUANG Yujia, SUN Qiuye, WANG Rui, et al. Static voltage stability analysis for integrated energy system[J]. Proceedings of the CSEE, 2019, 39(S1):44-53.
[17]	汪洋子, 陈茜. 计及冷、热、电联产的气电互联网络最优调度[J]. 电力系统保护与控制, 2019, 47(3):168-175.
	WANG Yangzi, CHEN Xi. Optimal dispatch for the integrated electrical and natural gas network with combined cooling, heat and power plant[J]. Power System Protection and Control, 2019, 47(3):168-175.
[18]	GEIDL M, KOEPPEL G, FAVRE-PERROD P, et al. Energy hubs for the future[J]. IEEE Power and Energy, 2006, 5(1):24-30.
[19]	MOHAMMADI M, NOOROLLAHI Y, MOHAMMADI-IVATLOO B, et al. Energy hub:From a model to a concept—A review[J]. Renewable and Sustainable Energy Reviews, 2017, 80:1512-1527. doi: 10.1016/j.rser.2017.07.030
[20]	徐宪东, 贾宏杰, 靳小龙, 等. 区域综合能源系统电/气/热混合潮流算法研究[J]. 中国电机工程学报, 2015, 35(14):3634-3642.
	XU Xiandong, JIA Hongjie, JIN Xiaolong, et al. Study on hybrid heat-gas-power flow algorithm for integrated community energy system[J]. Proceedings of the CSEE, 2015, 35(14):3634-3642.
[21]	李哲, 李俊杰, 周念成, 等. 基于多能源协同的微能网群能源转供优化模型[J]. 南方电网技术, 2021, 15(1):89-98.
	LI Zhe, LI Junjie, ZHOU Niancheng, et al. An optimal energy transfer model based on multi-energy collaboration in micro-energy network group[J]. Southern Power System Technology, 2021, 15(1):89-98.
[22]	LI R, WEI W, MEI S, et al. Participation of an energy hub in electricity and heat distribution markets:An MPEC approach[J]. IEEE Transactions on Smart Grid, 2018, 10(4):3641-3653. doi: 10.1109/TSG.5165411
[23]	吴琼, 吴彦琪, 任洪波, 等. 基于双向耦合的综合能源系统电热联合潮流计算[J]. 热力发电, 2021, 50(4):14-22.
	WU Qiong, WU Yanqi, REN Hongbo, et al. Power flow calculation of combined electric and thermal for integrated energy system based on two-way coupling[J]. Thermal Power Generation, 2021, 50(4):14-22.
[24]	CORREA-POSADA C M, SANCHEZ-MARTIN P. Security-constrained optimal power and natural-gas flow[J]. IEEE Transactions on Power Systems, 2014, 29(4):1780-1787. doi: 10.1109/TPWRS.2014.2299714
[25]	刘洪, 赵晨晓, 葛少云, 等. 基于精细化热网模型的电热综合能源系统时序潮流计算[J]. 电力系统自动化, 2021, 45(4):63-72.
	LIU Hong, ZHAO Chenxiao, GE Shaoyun, et al. Sequential power flow calculation of power-heat integrated energy system based on refined heat network model[J]. Automation of Electric Power Systems, 2021, 45(4):63-72.
[26]	ZHU M, XU C, DONG S, et al. An integrated multi-energy flow calculation method for electricity-gas-thermal integrated energy systems[J]. Protection and Control of Modern Power Systems, 2021, 6(1):1-12. doi: 10.1186/s41601-020-00173-9
[27]	QU L, OUYANG B, YUAN Z, et al. Steady-state power flow analysis of cold-thermal-electric integrated energy system based on unified power flow model[J]. Energies, 2019, 12(23):4455. doi: 10.3390/en12234455
[28]	LEI Y, CHEN X, JIANG K, et al. A novel methodology for electric-thermal mixed power flow simulation and transmission loss analysis in multi-energy micro-grids[J]. Frontiers in Energy Research, 2021, 8:620259. doi: 10.3389/fenrg.2020.620259
[29]	ABEYSEKERA M, WU J, JENKINS N, et al. Steady state analysis of gas networks with distributed injection of alternative gas[J]. Applied Energy, 2016, 164:991-1002. doi: 10.1016/j.apenergy.2015.05.099
[30]	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
[31]	LIU X, WU J, JENKINS N, et al. Combined analysis of electricity and heat networks[J]. Applied Energy, 2016, 162:1238-1250. doi: 10.1016/j.apenergy.2015.01.102
[32]	陈厚合, 张鹏, 姜涛, 等. 基于灵敏度分析的综合能源系统运行安全性的研究[J]. 电力自动化设备, 2019, 39(8):95-103.
	CHEN Houhe, ZHANG Peng, JIANG Tao, et al. Security analysis based on sensitivity analysis for integrated electric and gas energy system[J]. Electric Power Automation Equipment, 2019, 39(8):95-103.
[33]	徐晶, 徐科, 王世举, 等. 基于分立求解的电气耦合综合能源系统多能流联合计算方法[J]. 电力系统及其自动化学报, 2022, 34(1):114-120.
	XU Jin, XU Ke, WANG Shiju, et al. Multi-energy flow calculation method for integrated electricity-gas system based on discrete solution[J]. Proceedings of the CSU-EPSA, 2022, 34(1):114-120.
[34]	卫志农, 仲磊磊, 薛溟枫, 等. 基于数据驱动的电-热互联综合能源系统线性化潮流计算[J]. 电力自动化设备, 2019, 39(8):31-37.
	WEI Zhinong, ZHONG Leilei, XUE Mingfeng, et al. Linearization flow calculation for integrated electricity-heat energy system based on data-driven[J]. Electric Power Automation Equipment, 2019, 39(8):31-37.
[35]	孙宏宇, 张沛超, 杜炜, 等. 基于功率守恒原理的电热联合系统潮流计算方法[J]. 电力自动化设备, 2020, 40(11):54-62.
	SUN Hongyu, ZHANG Peichao, DU Wei, et al. Power flow calculation method of integrated electricity and heat system based on power conservation principle[J]. Electric Power Automation Equipment, 2020, 40(11):54-62.
[36]	陈彬彬, 孙宏斌, 吴文传, 等. 综合能源系统分析的统一能路理论(三):稳态与动态潮流计算[J]. 中国电机工程学报, 2020, 40(15):4820-4831.
	CHEN Binbin, SUN Hongbin, WU Wenchuan, et al. Energy circuit theory of integrated energy system analysis (III):Steady and dynamic energy flow calculation[J]. Proceedings of the CSEE, 2020, 40(15):4820-4831.
[37]	李卫东, 马俊, 胡幸集, 等. 城市综合能源网统一前推回代能流计算方法[J]. 电力自动化设备, 2022, 42(9):1-8.
	LI Weidong, MA Jun, HU Xingji, et al. Unified energy flow calculation of back/forward sweep method in urban integrated energy system[J]. Electric Power Automation Equipment, 2022, 42(9):1-8.
[38]	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, CHEN 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.
[39]	李昊飞, 瞿凯平, 余涛. 低碳动态电——气最优能流的加速凸分散优化求解[J]. 电力系统自动化, 2019, 43(12):85-93,103.
	LI Haofei, QU Kaiping, YU Tao. Optimization method of accelerated convex decentralization for low-carbon dynamic optimal gas-power flow[J]. Automation of Electric Power Systems, 2019, 43(12):85-93,103.
[40]	YAO S, GU W, LU S, et al. Dynamic optimal energy flow in the heat and electricity integrated energy system[J]. IEEE Transactions on Sustainable Energy, 2020, 12(1):179-190. doi: 10.1109/TSTE.5165391
[41]	QIN X, SUN H, SHEN X, et al. A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources[J]. Applied Energy, 2019, 251:113270. doi: 10.1016/j.apenergy.2019.05.073
[42]	FANG J, ZENG Q, AI X, et al. Dynamic optimal energy flow in the integrated natural gas and electrical power systems[J]. IEEE Transactions on Sustainable Energy, 2017, 9(1):188-198. doi: 10.1109/TSTE.2017.2717600
[43]	张惠智, 程志韬, 贾嵘, 等. 考虑天然气动态特性的电-气综合能源系统经济优化调度[J]. 电网技术, 2021, 45(4):1304-1311.
	ZHANG Huizhi, CHENG Zhitao, JIA Rong, et al. Economic optimization of electric-gas integrated energy system considering dynamic characteristics of natural gas[J]. Power System Technology, 2021, 45(4):1304-1311.
[44]	王梦雪, 赵浩然, 刘春阳, 等. 基于叠加原理的综合能源系统动态潮流追踪及碳熵分析[J/OL]. 电力系统自动化:1-18(2023-03-28)[2023-05-29]. http://kns.cnki.net/kcms/detail/32.1180.TP.20230328.0903.002.html.
	WANG Mengxue, ZHAO Haoran, LIU Chunyang, et al. Dynamic energy flow tracking and carbon entropy analysis of integrated energy system based on superposition principle[J/OL]. Automation of Electric Power Systems:1-18(2023-03-28)[2023-05-29]. http://kns.cnki.net/kcms/detail/32.1180.TP.20230328.0903.002.html.
[45]	BORKOWSKA B. Probabilistic load flow[J]. IEEE Transactions on Power Apparatus and Systems, 1974(3):752-759.
[46]	LI H, HOU K, XU X, et al. Probabilistic energy flow calculation for regional integrated energy system considering cross-system failures[J]. Applied Energy, 2022, 308:118326. doi: 10.1016/j.apenergy.2021.118326
[47]	YANG L, ZHAO X, PENG S, et al. Probabilistic power and mass flow analysis for integrated electricity and heating networks[J]. Journal of Energy Engineering, 2018, 144(4):04018041. doi: 10.1061/(ASCE)EY.1943-7897.0000555
[48]	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.
	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.
[49]	HU Y, LIAN H, BIE Z, et al. Unified probabilistic gas and power flow[J]. Journal of Modern Power Systems and Clean Energy, 2017, 5(3):400-411. doi: 10.1007/s40565-017-0284-1
[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]	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.
[52]	黎晨阳. 基于概率多能流的区域综合能源系统能源网络随机规划方法研究[D]. 上海: 上海交通大学, 2020
	LI Chenyang. Stochastic energy network planning of regional integrated energy systems based on probabilistic multi-energy flow[D]. Shanghai: Shanghai Jiao Tong University, 2020.
[53]	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 probablistic 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.
[54]	万黎, 袁荣湘. 最优潮流算法综述[J]. 继电器, 2005(11):80-87.
	WAN Li, YUAN Rongxiang. A summary of optimal power flow[J]. Relay, 2005(11):80-87.
[55]	蒲愿, 程浩忠, 宋毅, 等. 计及多能耦合的区域综合能源系统最优能流计算[J]. 电测与仪表, 2022, 59(9):8-15.
	PU Yuan, CHENG Haozhong, SONG Yi, et al. Calculation of optimal energy flow in a regional integrated energy system considering multi-energy coupling[J]. Electrical Measurement & Instrumentation, 2022, 59(9):8-15.
[56]	刘述欣, 戴赛, 胡林献, 等. 电热联合系统最优潮流研究[J]. 电网技术, 2018, 42(1):285-290.
	LIU Shuxin, DAI Sai, HU Linxian, et al. Study on optimal power flow of combined electro-thermal system[J]. Power System Technology, 2018, 42(1):285-290.
[57]	于东立, 曹军, 屠聪为, 等. 考虑线性化网络约束的电-热多能源系统最优能量流分析[J]. 中国电机工程学报, 2019, 39(7):1933-1944.
	YU Dongli, CAO Jun, TU Congwei, et al. Optimal energy flow of combined electrical and heating multi-energy system considering the linear network constraints[J]. Proceedings of the CSEE, 2019, 39(7):1933-1944.
[58]	SAYED A R, WANG C, BI T, et al. Optimal power-gas flow of integrated electricity and natural gas system:A sequential MISOCP approach[C]// 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2).IEEE, 2019:283-288.
[59]	PANG Y, ZHU S, DENG D, et al. Machine learning based optimal energy flow calculation for integrated electric-gas systems[C]// 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2).IEEE, 2021:1590-1595.
[60]	刘明凯, 王占山, 邢彦丽. 基于强化多目标差分进化算法的电-气互联系统最优潮流计算[J]. 电工技术学报, 2021, 36(11):2220-2232.
	LIU Mingkai, WANG Zhanshan, XING Yanli. Enhanced multi-objective differential evolutionary algorithm based optimal power flow calculation for integrated electricity and gas systems[J]. Transactions of China Electrotechnical Society, 2021, 36(11):2220-2232.
[61]	DU W, YANG Z, HE G, et al. Optimal power flow calculation of combined electricity-heat power system based on alternating direction method of multipliers[C]// 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia).IEEE, 2019:122-127.
[62]	杨梅, 周喜超, 魏强, 等. 考虑经济效益目标的源网荷储综合能源系统动态最优能流优化研究[J]. 综合智慧能源, 2022, 44(11):63-69. doi: 10.3969/j.issn.2097-0706.2022.11.009
	YANG Mei, ZHOU Xichao, WEI Qiang, et al. Study on dynamic optimal energy flow of a source-network-load-storage integrated energy system considering its economic benefit[J]. Integrated Intelligent Energy, 2022, 44(11):63-69. doi: 10.3969/j.issn.2097-0706.2022.11.009
[63]	MOEINI-AGHTAIE M, ABBASPOUR A, FOTUHI-FIRUZABAD M, et al. A decomposed solution to multiple-energy carriers optimal power flow[J]. IEEE Transactions on Power Systems, 2013, 29(2):707-716. doi: 10.1109/TPWRS.2013.2283259
[64]	许康平, 王程, 毕天姝. 基于气网动态代理模型的电-气综合能源系统最优能流计算[J]. 中国电机工程学报, 2023, 43(9):3415-3429.
	XU Kangping, WANG Cheng, BI Tianshu. Optimal energy flow calculation of integrated electric-gas systems based on gas network dynamic surrogate model[J]. Proceedings of the CSEE, 2023, 43(9):3415-3429.
[65]	LIU H, YANG L, SHEN X, et al. A data-driven warm start approach for convex relaxation in optimal gas flow[J]. IEEE Transactions on Power Systems, 2021, 36(6):5948-5951. doi: 10.1109/TPWRS.2021.3107201
[66]	闫新刚. 区域综合能源系统供能能力研究[D]. 天津: 天津大学, 2018.
	YAN Xingang. Research on total supply capability of district integrated energy system[D]. Tianjin: Tianjin University, 2018.
[67]	林威, 靳小龙, 穆云飞, 等. 区域综合能源系统多目标最优混合潮流算法[J]. 中国电机工程学报, 2017, 37(20):5829-5839.
	LIN Wei, JIN Xiaolong, MU Yunfei, et al. Multi-objective optimal hybrid power flow algorithm for integrated local area energy system[J]. Proceedings of the CSEE, 2017, 37(20):5829-5839.
[68]	WANG J, WANG C, LIANG Y, et al. Data-driven chance-constrained optimal gas-power flow calculation:A Bayesian nonparametric approach[J]. IEEE Transactions on Power Systems, 2021, 36(5):4683-4698. doi: 10.1109/TPWRS.2021.3065465

计算类型		特性	解决问题	数学模型	研究方法	优点	缺点
确定性潮流	稳态	长时间尺度，运行状态稳定	求解多系统、多能源耦合模型	代数方程	统一法	总迭代次数少	易出现维数过大，计算繁琐等问题
	稳态	长时间尺度，运行状态稳定	求解多系统、多能源耦合模型	代数方程	分解法	计算灵活简便	对耦合复杂系统收敛性差
	动态	短时间尺度，运行状态时变	偏微分方程线性化	偏微分方程	差分法	简化了偏微分计算	对大规模问题求解方程数多，计算量大
不确定性潮流	概率潮流	发电出力与能源负荷波动	求解系统状态变量统计特征	随机因素的概率分布模型	模拟法：蒙特卡罗模拟	计算精度高	计算效率低，处理复杂
					解析法：半不变量法	计算效率高	精度低，收敛不稳定
					近似法：点估计法	对低阶估计有较高的精度与效率	对高阶多不确定性因素估计精度与效率低

属性	经典法	人工智能法
适用范围	简单中小规模问题	复杂大规模问题
求解维数	低	高
初值要求	高	低
计算速度	较快	较慢
目标函数与约束条件	连续可微	可以不连续
结果稳定性	较好	较差