电能型-功率型混合储能日前-日内协同滚动调度策略OACSTPCD
Coordinated Day-ahead and Intra-day Rolling Scheduling Strategy for Electricity-Power Hybrid Energy Storage
混合储能可以利用不同类型储能在电量和功率上的不同优势.然而,在滚动优化调度中,电能型储能资源(如电池储能)容易因较短的日内滚动时间窗而限制其削峰填谷的能力;而功率型储能资源(如超级电容)又容易因较长的日前时间窗而影响其平抑风电波动的效果.针对以上两种问题,文中提出一种同时考虑电能型和功率型储能资源的日前-日内协同滚动调度策略.首先,针对电能型储能削峰填谷能力受限的问题,将日内滚动周期扩展到一天中的剩余时间,并将调度范围划分为时间分辨率不同的两个部分,从而使该部分储能资源尽可能参与削峰填谷,同时提升模型的求解效率.然后,针对功率型储能平抑波动能力受限的问题,通过对波动量的极值点统计分析,提出有限时间窗电量约束策略,从而避免该部分储能资源因过度参与削峰填谷而导致能量不足.算例表明,提出的调度策略能够发挥不同储能资源的调度潜力,在削峰填谷的同时平抑风电波动,提升风电消纳能力.
Hybrid energy storage systems can capitalize on the diverse advantages of different types of energy storage in terms of both capacity and power.However,in rolling optimization scheduling,electricity energy storage resources(such as battery storage)can be limited in their ability to perform peak shaving and load leveling due to relatively short intra-day rolling time windows.Conversely,power energy storage resources(such as super-capacitor)may have their effectiveness in mitigating wind power fluctuations compromised by longer day-ahead time windows.To address these two issues,this paper presents a day-ahead and intra-day coordinated rolling scheduling strategy that simultaneously considers both electricity and power energy storage resources.First,to address the limited peak-shaving capacity of electricity energy storage,the intra-day rolling period is extended to cover the remaining duration of a day and the scheduling horizon are divided into two parts with different temporal resolutions.This approach encourages the maximum possible involvement of this type of energy storage resource in peak shaving and load leveling while simultaneously improving the model computational efficiency.Then,to address the constraint on power energy storage resources for mitigating fluctuations,a strategy that imposes energy quantity constraints within a finite time window based on statistical analysis of extreme points of fluctuations is proposed.This strategy prevents the resource from depleting its energy reserves due to excessive participation in peak shaving and load leveling.Case studies demonstrate that the scheduling strategy presented in this paper harnesses the scheduling potential of different energy storage resources,achieving peak shaving and load leveling while effectively dampening wind power fluctuations and enhancing wind power accommodation capacity.
吴永飞;包宇庆
南京师范大学南瑞电气与自动化学院,江苏省南京市 210046
风电消纳储能削峰填谷滚动调度两阶段优化
wind power accommodationenergy storagepeak shaving and load levelingrolling schedulingtwo-stage optimization
《电力系统自动化》 2024 (001)
77-87 / 11
国家自然科学基金资助项目(51707099);江苏省研究生科研与实践创新计划项目(181200003023311). This work is supported by National Natural Science Foundation of China(No.51707099)and Postgraduate Research and Practice Innovation Program of Jiangsu Province(No.181200003023311).
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