基于改进两阶段鲁棒优化的主动配电网经济调度

针对多源配电网运行面临的供电电压不合格和运行经济性欠优的问题,该文提出了基于改进两阶段鲁棒优化的主动配电网经济调度策略。首先,量化分析了全电驱动的移动式储能(mobile energy storage,MES)的时空转移特性,评估了基于变频空调的建筑虚拟储能(virtual energy storage,VES)的调节能力,建立统一的多类型储能模型。进而,考虑预测误差,通过离散不确定域,改进现有的鲁棒优化方法,获得更加精确的"最恶劣"场景。在此基础上,针对优化模型中的min-max-min结构,提出了主–子问题交互迭代的求解方法。基于41节点配网的仿真结果表明,采用改进两阶段鲁棒优化模型的主动配电网经济调度切实可行,相应的求解算法具有高效性。该方法为配电网安全、经济运行提供了一个崭新的视角。

综合能源背景下的配电网多场景规划

随着能源利用设备的发展,综合能源系统成为能源供应的一个重要发展方向。与单一形式的能源供应相比,综合能源供应系统可以为用户提供更加经济、高效、多样化的能源供应。其中,包含冷热电联产机组(CCHP)、电制冷等设备的配电网是综合能源系统的主要物理载体。基于此,提出考虑新能源、电、热、冷负荷不确定性的综合能源系统设备和配电网变电站容量协同规划的多场景规划方法,实现电、气、热能源的高效、可靠供应。首先,根据CCHP机组、电制冷装置、燃气热水锅炉的物理特性,建立相应能量转化的数学模型。考虑综合能源系统中诸多元件对配电网节点电压的影响,采用Distflow模型建立交流潮流模型。其次,针对新能源出力和电、气、热负荷需求的不确定性对规划结果的影响,采用典型场景来描述电、气、热负荷的季节特性和新能源出力的波动性,进而建立基于多场景的综合能源系统和配电网协同规划模型。对改造的IEEE 33节点配电网系统进行规划计算,算例结果验证了所提规划方法的有效性及合理性。

Exploiting demand-side heterogeneous flexible resources in risk management of power system frequency

More demand-side flexible resources(DFRs)are participating in the frequency regulation of renewable power systems,whose heterogeneous characteristics have a significant impact on the system frequency response.Consequently,selecting suitable DFRs poses a formidable challenge for independent system operators(ISO).In this paper,a reserve allocation methodology for heterogeneous DFRs is proposed to manage the risk of power system frequency.Firstly,a performance curve is developed to describe the cost,capacity,and response speed of DFRs.Moreover,a clustering method for multiple distributed DFRs is conducted to calculate the aggregated performance curves and uncertainty coefficients.Then,the frequency security criterion considering DFRs’performance is constructed,whose linearity makes it can be easily coupled into the system scheduling model and solved.Furthermore,a risk management model for DFRs considering frequency-chance-constraint is proposed to make a trade-off between cost and frequency security.Finally,the model is transformed into mixed integer second-order cone programming(MISOCP)and solved by the commercial solver.The proposed model is validated by the IEEE 30 and IEEE 118 bus systems.

Delay-aware downlink beamforming with discrete rate adaptation for green cloud radio access network

With the popularity of variety delay-sensitive services, how to guarantee the delay requirements for mobile users （MUs） is a great challenge for downlink beamformer design in green cloud radio access networks （C-RANs）. In this paper, we consider the problem of the delay-aware downlink beamforming with discrete rate adaptation to minimize the power consumption of C-RANs. We address the problem via a mixed integer nonlinear program （MINLP）, and then reformulate the MINLP problem as a mixed integer second-order cone program （MI-SOCP）, which is a convex program when the integer variables are relaxed as continuous ones. Based on this formulation, a deflation algorithm, whose computational complexity is polynomial, is proposed to derive the suboptimal solution. The simulation results are presented to validate the effectiveness of our proposed algorithm.

Renewable Generation Capacity and Reliability Assessments for Resilient Active Distribution Networks Based on Time-sequence Production Simulation

The penetration of renewable generation will affect the energy utilization efficiency,economic benefit and reliability of the active distribution network(ADN).This paper proposes a time-sequence production simulation(TSPS)method for re-newable generation capacity and reliability assessments in ADN considering two operational status:the normal status and the fault status.During normal operation,an optimal dispatch model is proposed to promote the renewable consumption and increase the economic benefit.When a failure occurs,the renewable generators are partitioned into islands for resilient power supply and reliability improvement.A novel dynamic island partition model is presented based on mixed integer second-order cone programming(MISOCP).The effectiveness of the proposed TSPS method is demonstrated in a standard network integrated with historical data of load and renewable generations.