考虑高维不确定性的热电联产虚拟电厂优化调度

基于狄利克雷过程混合模型和变分推断算法建立了风电出力-光伏出力-电负荷-热负荷高维数据驱动不确定模糊集,在此基础上提出了考虑高维不确定性的热电联产虚拟电厂(CHP-VPP)两阶段随机鲁棒优化调度策略。两阶段中第1和第2阶段分别以日前和实时市场收益最大为目标函数,考虑各机组运行、功率平衡、市场交易和网络结构等多种约束,开发了加速列与约束生成(AC&CG)算法来对此优化调度问题进行求解。结果表明：所提出的随机鲁棒优化方法实现了CHP-VPP经济性和鲁棒性的均衡;模糊集中不确定边界值与CHP-VPP总收益呈负相关,随着不确定边界值的增大,系统的总收益降低,鲁棒性增加。     

计及风光不确定性的新能源虚拟电厂多时间尺度优化调度

针对中国西北地区新能源消纳问题,该文聚合风力发电、光伏发电、光热电站、电储能装置组成虚拟电厂（VPP）,提出一种基于鲁棒随机优化理论的新能源虚拟电厂多时间尺度优化调度策略。首先对风力发电、光伏发电、光热电站与电储能装置进行数学描述,在此基础上建立VPP多时间尺度优化调度模型。在日前调度层中,以VPP运行效益最大为目标,依据风光日前预测出力建立日前优化调度模型;在时前调度层中,以VPP运行成本最小为目标,根据风光时前预测出力建立时前调度修正模型。同时,为了衡量风电、光伏发电出力不确定性对系统的运行影响,建立VPP随机优化调度模型。仿真结果验证该模型可提高运行效益与新能源消纳能力。     

考虑需求响应和风险规避的虚拟电厂最优调度

合理考虑能源生产和消耗过程中的不确定因素对于提升虚拟电厂调度策略的有效性和经济性具有重要意义。提出一种考虑需求响应和风险规避的虚拟电厂（VPP）二阶段优化调度策略。第1阶段的日前市场中VPP基于随机参数和确定性参数制定日前竞标策略,与市场运营机构签订双边合同;第2阶段通过实时市场价格VPP调整机组出力,同时承担多重不确定性因素所导致的调度决策风险,并采用CVaR表征VPP运营商的收益与风险之间的关系。仿真结果验证了所提方法的有效性。     

考虑需求响应的风光燃储集成虚拟电厂双层随机调度优化模型

为促进以风光为代表的分布式能源发电并网,文章集成了风电、光伏发电、燃气轮机、储能系统和激励型需求响应为虚拟电厂,引入两阶段优化理论克服风光不确定性,建立VPP双层随机调度优化模型。首先,介绍了VPP的基本结构,建立了电源出力模型和需求响应模型。然后,建立了虚拟电厂双层调度优化模型:在上层模型中,根据风电和光伏发电日前预测结果,制定日前调度计划;在下层模型中,根据WPP和PV的实际输出,修正日前调度计划,形成最终VPP调度方案。最后算例分析表明:所提模型能够衔接日前调度和时前调度,降低系统缺电惩罚成本,提升VPP运营收益。储能系统能够利用自身充放电特性配合VPP内部风电和光伏发电出力,有利于平缓系统净负荷曲线。PBDR能够引导用户侧配合VPP发电调度,削峰作用弱于IBDR,而填谷作用强于IBDR。同时引入ESSs和DR后,VPP运营收益达到最高,表明ESSs和DR具有协同优化效应。     

考虑碳循环利用的农村虚拟电厂运行效益均衡分配优化模型

农村地区土地面积辽阔、资源丰富,分布式能源的发展潜力巨大。将垃圾发电、燃气碳捕集设备和电转气设备与农村的各种分布式能源聚合成考虑碳循环利用的农村虚拟电厂,并以最大化运营收益和最小化碳排放量为目标,构建虚拟电厂低碳调度优化模型。采用基于纳什谈判的效益分配策略,构建虚拟电厂运行效益均衡分配模型,并通过风险、效益和碳减排三维因子来确定各主体的利益分配因子。算例结果表明,本文所提运行优化模型和效益分配策略可互补利用农村多种分散式资源,有利于推进农村能源结构低碳转型。     

双碳目标下考虑风光不确定性的综合能源系统规划研究

可再生能源大规模并网,使配电系统及各类负荷运行稳定性降低。文章研究了可再生能源发电的不确定性综合能源系统（Integrated Energy System,IES）优化调度问题。首先,构建考虑风光不确定性的综合能源模型,采用不确定区间表达风机和光伏出力的不确定性;其次,利用鲁棒转换,可以将相关不确定性的问题转变成确定性多目标的优化问题进行求解;然后,以经济性与环境性为目标建立能源平衡与供应约束,并采用粒子群算法进行求解;最后,以某地园区的数据为基础进行仿真验证,证明了所提规划方法能够充分的考虑到风光不确定性,极大地提高系统的经济性,同时有效降低系统的碳排量,具有一定合理性和实用性。     

基于随机鲁棒优化的虚拟电厂灵活调峰投标策略

为量化分析虚拟电厂的灵活调峰能力,文章提出虚拟电厂参与能量、备用和灵活调峰市场的最优投标策略,建立虚拟电厂参与主辅市场的联合出清模型。基于场景的随机优化刻画实时电价的不确定性,提出一种随机鲁棒优化方法,控制新能源出力随机性引起的运行成本。基于实际虚拟电厂的数值仿真表明,虚拟电厂能够有效提供灵活调峰服务,随机鲁棒优化为刻画虚拟电厂所面临的多重不确定性提供理论方法。     

考虑风电不确定性的交直流混联系统同质化能量函数模型

交直流混联电网是电网发展的新形态,如何有效保障交直流混联系统安稳运行是重大而紧迫的国家需求。文章针对含大规模风电的交直流混联系统稳定性问题,提出考虑风电波动不确定性的交直流混联弱送端系统同质化能量函数模型。首先,研究含大规模风电的交直流混联弱送端系统潮流方程;其次,建立含风电的交直流混联系统支路暂态势能函数模型,研究交直流混联系统功角稳定机理,建立基于同质化能量函数模型;在此基础上,提出基于同质化能量函数的电力系统稳定性评估模型,并推导交直流混联系统稳定性判据;最后,以北方某区域交直流混联系统为仿真算例,验证所提模型的有效性,为含大规模新能源的交直流混联系统的稳定性控制提供理论依据。     

计及分布式储能的虚拟电厂优化调度

分布式储能是虚拟电厂的优质可调节资源。为提高含分布式储能的虚拟电厂收益,构建了虚拟电厂中柴油发电机和风光可再生能源机组的模型;分别建立了并网型储能与用户侧储能两种分布式储能的运行约束条件;基于日前市场分时电价对虚拟电厂资源进行了优化调度算例分析。研究结果表明,受需量约束的限制,用户侧储能的收益能力不如并网型储能;不同需量约束将影响用户侧储能为虚拟电厂进行电价套利的能力;用户侧储能的个数越多,虚拟电厂的总收益越少。     

考虑风电场景缩减的多区域综合能源系统容量配置

以冷-热-电联供为核心的综合能源系统(IES)能有效提高能源利用率和供能灵活性。文章针对大规模风电接入对IES规划和运行的影响,提出了一种考虑风电场景缩减的多区域综合能源系统容量配置方法。采用混合度量的改进k-means算法对风电历史数据进行聚类,判定聚类场景数目和聚类中心;在充分考虑热网损耗和延迟效应的基础上,建立包含热网管道、节点、换热器的详细热网模型;通过热网连接多个区域综合能源系统,建立以系统年投资成本、运行成本和弃风惩罚成本之和最小为目标函数的多区域综合能源系统容量配置模型。仿真结果表明,该模型能大幅降低设备配置容量和系统运行费用,提高风电消纳率。     

Modelling and analysis of resource scheduling in restructured power systems considering wind energy uncertainty

Concerns over rapid transformation of global climate patterns resulted in wide deployment of renewable energy sources especially wind energy. However, intermittent nature of wind energy makes resource scheduling aspect of system operator more complex. The emerging deregulation policies have added to the complexity of scheduling problem. Therefore, treating and scheduling of wind energy on deterministic basis would result in non-optimal energy dispatch and increased operation cost over scheduling horizon. This paper focuses on optimal scheduling methodology of wind energy in day ahead market (DAM) considering expected costs due to wind uncertainty in real time (RT) spot market under deregulated market structure. This paper introduces various possible costs, namely, spot market compensation cost, additional reserve cost and rescheduling cost applicable to deviation in scheduled power from DAM to spot market. The costs can be derived from front-end information of DAM, historical and statistical estimate of RT market conditions. The effectiveness of proposed methodology is examined using IEEE 30 bus system with thermal and wind energy generators. In addition, sensitivity analysis is performed to examine the effect of incentive margin on DAM scheduling. Simulation results are presented, discussed and affirmed the effectiveness of proposed scheduling methodology.     

A dynamic risk aversion model for virtual energy plant considering uncertainties and demand response

To full use clean energy to meet load demand of electrical and thermal, the paper proposed a novel concept of virtual energy plant (VEP) including wind power plant (WPP), photovoltaic power generation (PV), combined heat and power generation (CHP), solar collectors (SC), electric boiler (EB), heat storage tank (HSK), and incentive‐based demand response (IBDR). Firstly, the basic structure of VEP is designed, including three subsystems, namely, electricity, heating, and energy storage. Then, a basic scheduling model is constructed under the objective of maximizing operating revenue without considering uncertainty. Thirdly, the conditional value at risk (CVaR) method and the robust optimization theory are used to handle the uncertainty factors in objective functions and condition constraints, and the risk aversion scheduling model is proposed. Finally, industrial park group in northern China are chosen, for example, analysis results show (1) VEP could convert the abandoned clean energy, use HSK to store heating energy during the valley load period, and supply heating energy in the peak period to obtain the excess economic benefits. (2) Lower‐prediction accuracy will amplify the uncertainty risk, when the robust β∈[0.8,0.825]&(0.925,1], the increase of confidence level β will lead to larger increase in CVaR. Especially when β∈(0.925,1), decision makers are extremely disgusted with the risks brought by the uncertainty factors, and correspondingly, the output of clean energy becomes minimum. (3) When the capacity ratio of HSK, EB and the electricity price of peak, valley are lower than 3, the values of revenue, VaR and CVaR change faster, but the ratios are larger than 3, the values change slower, which indicates that the scale of HSK capacity needs to be properly controlled to optimize the use of clean energy, and price‐based demand response could improve the operation profit while controlling risk properly. In general, the proposed scheduling model can maximize the use of clean energy to obtain economic benefits while rationally controlling risks.     

An equilibrium pricing model for wind power futures

Generation from wind power plants is intermittent and affects profits of wind power generators and conventional generators alike. Currently, generators have limited options for transferring the resulting wind-related volume risks. The European Energy Exchange (EEX) recently introduced exchange-traded wind power futures to address this market imperfection. We propose a stylized equilibrium pricing model featuring two representative agents and analyze equilibrium prices as well as the mechanics behind risk premia for wind power futures. We calibrate and simulate stochastic models for wind power generation, power prices, electricity demand, as well as other relevant sources of uncertainty and use the resulting scenarios to conduct a case study for the German market; analyzing prices, hedging effectiveness, and risk premia. Our main result suggests that wind generators are willing to pay an insurance premium to conventional generators to reduce their risks. We conduct a thorough sensitivity analysis to test the influence of model parameters and find that our results on risk premia hold for a broad range of reasonable inputs.     

UPFC setting to avoid active power flow loop considering wind power uncertainty

The active power loop flow (APLF) may be caused by impropriate network configuration, impropriate parameter settings, and/or stochastic bus powers. The power flow controllers, e.g., the unified power flow controller (UPFC), may be the reason and the solution to the loop flows. In this paper, the critical existence condition of the APLF is newly integrated into the simultaneous power flow model for the system and UPFC. Compared with the existing method of alternatively solving the simultaneous power flow and sensitivity-based approaching to the critical existing condition, the integrated power flow needs less iterations and calculation time. Besides, with wind power fluctuation, the interval power flow (IPF) is introduced into the integrated power flow, and solved with the affine Krawcyzk iteration to make sure that the range of active power setting of the UPFC not yielding the APLF. Compared with Monte Carlo simulation, the IPF has the similar accuracy but less time.     

Hydrogen energy storage systems to improve wind power plant efficiency considering electricity tariff dynamics

One of the limitations of the efficiency of renewable energy sources is the stochastic nature of generation; consequently, it is necessary to use high-capacity energy storage systems such as hydrogen storage for its integration into existing power networks. At the same time, electricity market tariffs for large enterprises change during the day. Therefore, it can be assumed that storing energy during cheaper hours and usage in more expensive hours allows increasing the efficiency of renewable energy sources. Evaluation of the economic efficiency of an energy storage system requires simulation with a step of at least 1 h for several years since the use of averaged production volume and averaged electricity tariffs will not allow obtaining an adequate to the task accuracy. A simulation model and software have been implemented to perform simulations and calculate the economic efficiency of a wind turbine with and without a hydrogen storage device. The methodology has been approved on three-year real data of wind speeds and electricity tariffs in the Novosibirsk region and Krasnodar Territory (Russian Federation).     

基于风电不确定性模糊量化的综合能源系统规划方法研究

综合能源系统是能源结构转型与发展过程中的关键环节,也是高比例可再生能源并网型能源互联网的具体实现。由于多种能源耦合以及可再生能源不确定性等因素的影响,综合能源系统规划设计对经济性和环保性提出了更高要求。文章提出了考虑风电不确定性的综合能源系统能源供给单元容量协调规划决策方法。首先结合风电不确定性集合的区间数量化方法,建立了基于直觉模糊集的风电不确定性量化模型;然后通过对电力系统、热力系统、天然气系统的能源供给单元经济成本和环境成本进行分析,提出考虑风电不确定性的综合能源系统能源供给单元容量协调规划决策模型及求解方法,最大限度降低综合能源系统经济成本和环境成本,提高风电的并网容量;最后通过算例仿真验证了所提规划方法的正确性和有效性。