According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak s...According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak shaving optimization model consisting of three different time scales has been proposed.The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination,generation power,and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power(CSP).At the same time,in order to improve the accuracy of the scheduling results,the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results.The testing results have shown that by optimizing the allocation of scheduling resources in each phase,it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation.The spinning reserve capacity is reduced,and the effectiveness of the peak shaving strategy is verified.展开更多
5G通信基站通常配备光储,数量庞大、功耗可调,是一种优质的电力灵活性调节资源。提出了多类型光储式5G基站集群灵活性资源聚合方法以及参与电网调峰的协同调度策略。首先,分析休眠机制下多类型基站功耗可调特性与计及基站备用电量的储...5G通信基站通常配备光储,数量庞大、功耗可调,是一种优质的电力灵活性调节资源。提出了多类型光储式5G基站集群灵活性资源聚合方法以及参与电网调峰的协同调度策略。首先,分析休眠机制下多类型基站功耗可调特性与计及基站备用电量的储能调节能力。基于极限场景思想,构建了光储式5G基站的灵活性空间量化模型。在此基础上,利用闵可夫斯基和法刻画异构基站柔性资源的时空耦合能量轨迹,得到海量基站集群的灵活性资源聚合可调域。其次,建立了基站集群聚合资源参与电能量市场和辅助服务市场的协同调度优化模型,提出了基于交替方向乘子法(alternating direction method of multipliers, ADMM)的分层分布式基站集群协同优化调度策略,将大规模基站集群调度问题降维分解为统一协同调峰功率响应、聚合功率自治调度和基站集群功率分配3个子问题进行求解。通过算例对比分析可知,所提策略可降低通信基站69.86%的用能成本,为提升通信资源利用率和电力系统灵活调节能力提供了有效手段。展开更多
基金support of the projects Youth Science Foundation of Gansu Province(Source-Grid-Load Multi-Time Interval Optimization Scheduling Method Considering Wind-PV-CSP Combined DC Transmission,No.22JR11RA148)Youth Science Foundation of Lanzhou Jiaotong University(Research on Coordinated Dispatching Control Strategy of High Proportion New Energy Transmission Power System with CSP Power Generation,No.2020011).
文摘According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak shaving optimization model consisting of three different time scales has been proposed.The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination,generation power,and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power(CSP).At the same time,in order to improve the accuracy of the scheduling results,the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results.The testing results have shown that by optimizing the allocation of scheduling resources in each phase,it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation.The spinning reserve capacity is reduced,and the effectiveness of the peak shaving strategy is verified.
文摘5G通信基站通常配备光储,数量庞大、功耗可调,是一种优质的电力灵活性调节资源。提出了多类型光储式5G基站集群灵活性资源聚合方法以及参与电网调峰的协同调度策略。首先,分析休眠机制下多类型基站功耗可调特性与计及基站备用电量的储能调节能力。基于极限场景思想,构建了光储式5G基站的灵活性空间量化模型。在此基础上,利用闵可夫斯基和法刻画异构基站柔性资源的时空耦合能量轨迹,得到海量基站集群的灵活性资源聚合可调域。其次,建立了基站集群聚合资源参与电能量市场和辅助服务市场的协同调度优化模型,提出了基于交替方向乘子法(alternating direction method of multipliers, ADMM)的分层分布式基站集群协同优化调度策略,将大规模基站集群调度问题降维分解为统一协同调峰功率响应、聚合功率自治调度和基站集群功率分配3个子问题进行求解。通过算例对比分析可知,所提策略可降低通信基站69.86%的用能成本,为提升通信资源利用率和电力系统灵活调节能力提供了有效手段。
文摘【目的】在“双碳”目标背景下,解决高风电渗透率系统建设带来的调峰安全性和经济性问题。【方法】采用电池储能系统削峰填谷的解决方案,提出了一种兼顾技术及经济性的锌溴液流电池(zinc-bromine flow battery,ZBB)储能的调峰优化控制方法。根据实际电池装置,对ZBB储能进行结构解析及数学模型构建。考虑调峰技术性效果,以调峰后的负荷曲线标准差最小为目标函数,提出一种考虑调峰效果的储能双向寻优控制策略。在此基础上,依据电网分时(time of use,TOU)电价政策,以技术性及经济性最优为目标函数,提出一种基于TOU电价机制的储能调峰经济模型,得出储能优化功率时序结果。最后,以东北某地区负荷及风电数据为例,对比验证所提策略的有效性。【结果】所提策略相较于原负荷,在日均负荷峰谷差、峰谷差率指标上分别降低了35.973%和34.205%,在调峰经济性优化方面提高了5.582%,且合并缓解了电网弃风消纳问题。【结论】所提策略在达到一定调峰效果的同时,在其全寿命周期内仍保持较好的调峰经济性。