面向电力系统调度需求的负荷资源调控技术研究综述A review of load resource scheduling and control geared to the needs of power system scheduling
蒙志全,楼贤嗣,时涵,谢云云,郭晓蕊,孙飞飞
MENG Zhiquan,LOU Xiansi,SHI Han,XIE Yunyun,GUO Xiaorui,SUN Feifei
摘要(Abstract):
为了实现碳中和目标下的能源转型,以风电、光伏为代表的新能源将成为未来电力系统的主要电源。然而,高比例可再生能源的接入在带来高不确定性的同时降低了系统惯性,传统电力系统的调节资源无法满足未来电力系统的调度需求,需要从“源随荷动”传统模式向“源荷互动”协同模式转变。为此,对面向电力系统调度需求的负荷资源调控技术进行了综述。从电网运行调度的角度阐述了将可控负荷纳入电网运行调度的必要性,并从调度响应时间、调度响应方式、用户用电特点、能量传递方向、聚合商平台特点等5个方面对可控负荷进行分类。针对可控负荷接入对电力系统调度的影响,分别从建模技术、调度形式及调度架构方面进行分析。结合我国当前电力系统发展情况,提出了可控负荷资源参与电网运行调度的建议与展望。
In order to realize the energy transformation under the goal of carbon neutrality,new energy represented by wind power and photovoltaic power will serve as the main power supply for the future power system. However,the access of high-proportion renewable energy brings about high uncertainty and undermines system inertia,so much so that the scheduling resources of the traditional power system can no longer meet the scheduling demand of the future power system. Hence,a transformation from“the source changes with load”to“the interaction between source and load”. Therefore,this paper summarizes the load resource scheduling methods geared for power system scheduling. Firstly,from the perspective of power grid operation scheduling,the necessity of bringing controllable load into power grid operation scheduling is expounded,and controllable load is classified from five aspects:dispatching response time,dispatching response mode,users' power consumption characteristics,energy transfer direction and load aggregator platform. Then,the influence of controllable load access on power system scheduling is analyzed from the aspects of modeling technology,scheduling form and scheduling architecture. Finally,combined with the current development of power system in China,the suggestion and prospect of controllable load resources participating in power grid operation scheduling are put forward.
关键词(KeyWords):
可再生能源;源荷互动;运行调度;可控负荷;调控技术
renewables;interaction between source and load;operation and dispatching;controllable load;dispatching technology
基金项目(Foundation): 国网浙江省电力有限公司科技项目(B311JY21000K)
作者(Author):
蒙志全,楼贤嗣,时涵,谢云云,郭晓蕊,孙飞飞
MENG Zhiquan,LOU Xiansi,SHI Han,XIE Yunyun,GUO Xiaorui,SUN Feifei
参考文献(References):
- [1]中国青年报.中国工程院:我国有望2027年实现碳达峰,2060年前实现碳中和[EB/OL].(2022-3-31)[2022-4-10].https://baijiahao.baidu.com/s?id=1728807657056462932&wfr=spider&for=pc.
- [2]王成山,李鹏,于浩.智能配电网的新形态及其灵活性特征分析与应用[J].电力系统自动化,2018,42(10):13-21.
- [3]卓振宇,张宁,谢小荣,等.高比例可再生能源电力系统关键技术及发展挑战[J].电力系统自动化,2021,45(9):171-191.
- [4] MCPHERSON M,STOLL B.Demand response for variable renewable energy integration:A proposed approach and its impacts[J].Energy,2020:117205.
- [5]宁剑,江长明,张哲,等.可调节负荷资源参与电网调控的思考与技术实践[J].电力系统自动化,2020,44(17):1-8.
- [6]苗红.全球可再生能源现状及展望[J].世界环境,2017(2):65-67.
- [7] AL-MULLA A,ELSHERBINI A.Demand management through centralized control system using power line communication for existing buildings[J].Energy Conversion&Management,2014,79:477-486.
- [8] DAN W,GE S,JIA H,et al.A demand response and battery storage coordination algorithm for providing microgrid tie-line smoothing services[J].IEEE Transactions on Sustainable Energy,2014,5(2):476-486.
- [9] JU L,LI H,ZHAO J,et al. Multi-objective stochastic scheduling optimization model for connecting a virtual power plant to wind-photovoltaic-electric vehicles considering uncertainties and demand response[J].Energy Conversion&Management,2016,128:160-177.
- [10]陆凌蓉,文福拴,薛禹胜,等.计及可入网电动汽车的电力系统机组最优组合[J].电力系统自动化,2011,35(21):16-20.
- [11]陈风,林镜涛.考虑用户需求差异的源-车-储微电网优化调度方法[J].浙江电力,2020,39(11):51-60.
- [12]葛晓琳,郝广东,夏澍,等.考虑规模化电动汽车与风电接入的随机解耦协同调度[J].电力系统自动化,2020,44(4):54-62.
- [13]华光辉,李晨,张勇,等.考虑温控负荷聚合功率不确定性的楼宇微网鲁棒优化[J].电力建设,2021,42(4):59-68.
- [14]王会继.考虑温控负荷灵活性的电力系统优化调度模型[D].北京:华北电力大学,2021.
- [15]王成山,武震,李鹏.分布式电能存储技术的应用前景与挑战[J].电力系统自动化,2014,38(16):1-8.
- [16]金迪,潘郁,周家华,等.考虑高渗透率光伏接入的分布式储能优化配置[J].浙江电力,2020,39(3):68-74.
- [17]吴彬锋,傅颖,陈扬哲,等.考虑紧急备用与光伏出力不确定性的微电网分布式储能规划方法[J].浙江电力,2021,40(9):32-40.
- [18]夏榆杭,刘俊勇,冯超,等.计及需求响应的虚拟发电厂优化调度模型[J].电网技术,2016,40(6):1666-1674.
- [19]周亦洲,孙国强,黄文进,等.多区域虚拟电厂综合能源协调调度优化模型[J].中国电机工程学报,2017,37(23):6780-6790.
- [20]徐辉,焦扬,蒲雷,等.计及不确定性和需求响应的风光燃储集成虚拟电厂随机调度优化模型[J].电网技术,2017,41(11):3590-3597.
- [21]宋艺航,谭忠富,李欢欢,等.促进风电消纳的发电侧、储能及需求侧联合优化模型[J].电网技术,2014,38(3):610-615.
- [22]张腾飞,田书,郭成威.考虑可控负荷的光热电站和风电系统调度策略[J/OL].电力系统及其自动学报:1-8[2021-11-23].
- [23]鞠立伟,秦超,吴鸿亮,等.计及多类型需求响应的风电消纳随机优化调度模型[J].电网技术,2015,39(7):1839-1846.
- [24]央视财经.双第一!风电、太阳能发电装机占比超25%,我国新能源发电进入平价阶段[EB/OL].(2021-11-21)[2022-4-10]. https://baijiahao. baidu. com/s? id=1717024308241877052&wfr=spider&for=pc.
- [25]北京日报客户端.浙江调整分时电价:最大峰谷差率超50%[EB/OL].(2021-10-13)[2022-4-10].https://baijiahao.baidu.com/s?id=1713477244070610025&wfr=spider&for=pc.
- [26]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.
- [27]王彩霞,时智勇,梁志峰,等.新能源为主体电力系统的需求侧资源利用关键技术及展望[J].电力系统自动化,2021,45(16):37-48.
- [28] CHEN Z,WU L,FU Y.Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization[J].IEEE Transactions on Smart Grid,2012,3(4):1822-1831.
- [29]于雷,汤庆峰,张建华.基于负荷资源分类建模和启发式策略的家居型微电网优化运行[J].电网技术,2015,39(8):2180-2187.
- [30]高勇,彭志炜,刘斌,等.主动配电网柔性负荷优化调控研究综述[J].新型工业化,2019,9(4):27-34.
- [31]孙玲玲,高赐威,谈健,等.负荷聚合技术及其应用[J].电力系统自动化,2017,41(6):159-167.
- [32]刘小聪,王蓓蓓,李扬,等.计及需求侧资源的大规模风电消纳随机机组组合模型[J].中国电机工程学报,2015,35(14):3714-3723.
- [33]刘萌,梁雯,张岩,等.计及空调负荷群控制的源-荷协同优化调度模型[J].电网技术,2017,41(4):1230-1238.
- [34]艾欣,周树鹏,陈政琦,等.多随机因素下含可中断负荷的电力系统优化调度模型与求解方法研究[J].中国电机工程学报,2017,37(8):2231-2242.
- [35]侯慧,徐焘,肖振锋,等.计及可调控负荷的发用电一体化综合优化调度[J].电网技术,2020,44(11):4294-4304.
- [36]孙晓明,王玮,苏粟,等.基于分时电价的电动汽车有序充电控制策略设计[J].电力系统自动化,2013,37(1):191-195.
- [37]邱晓燕,沙熠,宁雪姣,等.大规模风电接入的智能电网多类型柔性负荷分级优化调度[J].高电压技术,2016,42(7):2084-2091.
- [38]陈健,张维桐,张逸成,等.考虑不同空调负荷特性的微网双层优化调度[J].电网技术,2018,42(5):1424-1431.
- [39]于汀,刘广一,蒲天骄,等.计及柔性负荷的主动配电网多源协调优化控制[J].电力系统自动化,2015,39(9):95-100.
- [40]杨秀,傅广努,刘方,等.考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究[J].电网技术,2022,46(2):699-714.
- [41]何沁蔓,刘晓峰,王琦,等.计及用电满意度优先级划分的负荷聚合商调度策略研究[J].电网技术,2021,45(7):2666-2675.
- [42] ALAHYARI A,EHSAN M,MOUSAVIZADEH M S.A hybrid storage-wind virtual power plant(VPP)participation in the electricity markets:A self-scheduling optimization considering price,renewable generation,and electric vehicles uncertainties[J].Journal of Energy Storage,2019,25:100812.
- [43] LIANG R H,LIAO J H.A Fuzzy-optimization approach for generation scheduling with wind and solar energy systems[J].IEEE Transactions on Power Systems,2007,22(4):1665-1674.
- [44]晏开封,张靖,何宇,等.基于机会约束的微电网混合整数规划优化调度[J].电力科学与工程,2021,37(2):17-24.
- [45]白牧可,王越,唐巍,等.基于区间线性规划的区域综合能源系统日前优化调度[J].电网技术,2017,41(12):3963-3970.
- [46] YX A,WG B,QW C,et al.Robust MPC-based bidding strategy for wind storage systems in real-time energy and regulation markets[J]. International Journal of Electrical Power&Energy Systems,124:106361.
- [47] LIN W,ZHU J,YUAN Y,et al.Robust optimization for island partition of distribution system considering load forecasting error[J].IEEE Access,2019,7:64247-64255.
- [48] HU B,WU L,MARWALI M.On the robust solution to SCUC with load and wind uncertainty correlations[J].IEEE Transactions on Power Systems,2014,29(6):2952-2964.
- [49]隋鑫,卢盛阳,苏安龙,等.计及风电和柔性负荷的核电多目标优化调度研究[J].中国电机工程学报,2019,39(24):7232-7241.
- [50]胡佳怡,严正,王晗.考虑清洁电力共享的社区电能日前优化调度[J].电网技术,2020,44(1):61-70.
- [51]朱永胜,王杰,瞿博阳,等.采用基于分解的多目标进化算法的电力环境经济调度[J].电网技术,2014,38(6):1577-1584.
- [52] YUAN X,ZHANG B,WANG P,et al. Multi-objective optimal power flow based on improved strength Pareto evolutionary algorithm[J].Energy,2017,122:70-82.
- [53] HOU H,XUE M,XU Y,et al.Multiobjective joint economic dispatching of a microgrid with multiple distributed generation[J].Energies,2018,11(12):3264.
- [54]马燕峰,谢家荣,赵书强,等.考虑园区综合能源系统接入的主动配电网多目标优化调度[J/OL].电力系统自动化:1-16[2022-03-02].
- [55]刘故帅,肖异瑶,贺禹强,等.考虑新能源类型的电力系统多目标并网优化方法[J].电力系统保护与控制,2017,45(10):31-37.
- [56]陈亮,顾雪平,贾京华.基于病毒进化改进NSGA-Ⅱ算法的扩展黑启动多目标优化[J].电力系统保护与控制,2014,42(2):35-42.
- [57]李凌昊,邱晓燕,张楷,等.考虑多负荷聚集商参与的系统日前-日内分层优化调度策略[J].电力建设,2019,40(12):70-79.
- [58]陈永椿,董萍,伍子东,等.计及需求响应的微网现货市场运行策略[J].电网技术,2019,43(12):4558-4568.
- [59]宋艺航,王秀丽,匡熠,等.含风电和电动汽车的VPP现货市场投标鲁棒优化模型[J].电力工程技术,2020,39(3):120-127.
- [60]马春艳,董春发,吕志鹏,等.计及随机因素的商业型虚拟发电厂短期交易与优化运行策略[J].电网技术,2016,40(5):1543-1549.
- [61] ZHOU Y,WEI Z,SUN G,et al.Four-level robust model for a virtual power plant in energy and reserve markets[J].Generation,Transmission&Distribution,IET,2019,13(11):2036-2043.
- [62]张高,王旭,蒋传文,等.采用双层优化调度的虚拟电厂经济性分析[J].电网技术,2016,40(8):2295-2301.
- [63]陈美福,夏明超,陈奇芳,等.主动配电网源-网-荷-储协调调度研究综述[J].电力建设,2018,39(11):109-118.
- [64]高红均,刘俊勇.考虑不同类型DG和负荷建模的主动配电网协同规划[J].中国电机工程学报,2016,36(18):4911-4922.
- [65]谢航,朱燕梅,马光文,等.水风光混合能源短期互补协调调度策略研究[J].水力发电,2021,47(9):100-105.
- [66]苏海锋,胡梦锦,梁志瑞.基于时序特性含储能装置的分布式电源规划[J].电力自动化设备,2016,36(6):56-63.
- [67]彭春华,温泽之,孙惠娟,等.计及风电置信风险的源网协调多目标优化调度[J].电力自动化设备,2021,41(1):69-78.
- [68] TINDEMANS SH,TROVATO V,STRBAC G.Decentralized control of thermostatic Loads for flexible demand response[J]. IEEE Transactions on Control Systems Technology,2015,23(5):1685-1700.
- [69] NOLAN S,O’MALLEY M. Challenges and barriers to demand response deployment and evaluation[J]. Applied Energy,2015,152:1-10.
- [70]张宁,胡兆光,周渝慧,等.考虑需求侧低碳资源的新型模糊双目标机组组合模型[J].电力系统自动化,2014,38(17):25-30.
- [71]唐杰,吕林,叶勇,等.多时间尺度下主动配电网源-储-荷协调经济调度[J].电力系统保护与控制,2021,49(20):53-64.
- [72]沙熠,邱晓燕,宁雪姣,等.协调储能与柔性负荷的主动配电网多目标优化调度[J].电网技术,2016,40(5):1394-1399.
- [73]梁子鹏,陈皓勇,王勇超,等.含电动汽车的微网鲁棒经济调度[J].电网技术,2017,41(8):2647-2658.
- [74]张鹏,李春燕,张谦.基于需求响应调度容量上报策略博弈的电网多代理系统调度模式[J].电工技术学报,2017,32(19):170-179.
- [75]朱兰,刘伸,唐陇军,等.充放电不确定性响应建模与电动汽车代理商日前调度策略[J].电网技术,2018,42(10):3305-3317.
- [76]卢志刚,杨宇,耿丽君,等.基于Benders分解法的电热综合能源系统低碳经济调度[J].中国电机工程学报,2018,38(7):1922-1934.
- [77] JIANG Q Y,ZHOU B R,ZHANG M Z.Parallel augment Lagrangian relaxation method for transient stability constrained unit commitment[J]. IEEE Transactions on Power Systems,2013,28(2):1140-1148.
- [78]张吉昂,王萍,程泽.采用混沌粒子群-内点法联合算法的多目标发电调度[J].电网技术,2021,45(2):613-621.
- [79]徐豪,张孝顺,余涛.非理想通信网络条件下的经济调度鲁棒协同一致性算法[J].电力系统自动化,2016,40(14):15-24.
- [80]瞿凯平,黄琳妮,余涛,等.碳交易机制下多区域综合能源系统的分散调度[J].中国电机工程学报,2018,38(3):11.
- [81] HE C,LEI W,LIU T,et al.Robust co-optimization scheduling of electricity and natural gas systems via ADMM[J].IEEE Transactions on Sustainable Energy,2016,8(2):658-670.
- 可再生能源
- 源荷互动
- 运行调度
- 可控负荷
- 调控技术
renewables - interaction between source and load
- operation and dispatching
- controllable load
- dispatching technology