考虑不同负荷水平下DG定容选址的配电网协调规划研究

针对多种负荷水平下,分布式电源(DG)接入配电网带来的随机性问题以及无法兼顾DG容量与选址的协调规划问题,本文构建了一种考虑不同负荷水平与DG定容选址的配电网协调规划模型,可对配电网网架进行重新构建的同时,综合考虑DG容量与配置位置的规划,以获得最小的有功网损与最大的电压支撑效果。该规划模型首先对风电接入配电网的随机特性构建数学概率模型,然后将配电网开关组合与各个DG的容量、配置位置同时作为变量引入烟花优化算法求解,最后在不同风电场景与负荷水平下得到最优规划结果。美国PEG69节点系统的算例仿真结果表明该模型不仅可以满足配电网辐射状与稳定运行的约束,在与仅引入DG容量和仅引入DG位置规划的对比中,验证了容量位置协调规划在配电网经济运行方面的优越性。     

内嵌需求响应与优化运行策略的主动配电系统源网协同规划

针对主动配电系统的分布式电源与网络结构协同规划过程中难以同时考虑它们在运行环节交互作用的问题,提出了一种考虑多主体利益均衡及规划运行交替优化的数学模型和求解算法。首先,建立了分别以分布式电源和配电网各自成本效益最优为目标并内嵌需求响应与运行策略的3层优化框架及数学模型;其次,提出了基于拓扑等效原则的网络结构简化方法,并结合网架生成过程中拓扑结构变化特征的深入分析,提出了基于破圈法的单联络网络快速生成方法,制定了与之相结合的粒子群优化算法的编/解码方案;再次,基于网供负荷特性和用户需求响应意愿,提出了有源配电网动态分时电价优化方法及运行策略,并建立了内嵌精细化运行的源网协同规划求解流程;最后,通过算例验证了所述方法的合理性和有效性。     

考虑越限风险的主动配电网中DG、SOP与ESS的两阶段协调规划

双碳和新型配电系统构建目标下优化多种灵活型资源位置与容量是实现该目标的重要技术路线。为此,兼顾规划运行的经济性和安全性,提出一种考虑越限风险的主动配电网中可再生分布式电源(distributed genevation, DG)、智能软开关(soft open point, SOP)、储能(energy storage, ESS)的两阶段协调规划方法。阶段1以综合成本与越限风险最小为目标优化DG、SOP与ESS的位置和容量。阶段2属于联合SOP、网络重构、有载调压变压器、电容器组、需求响应和储能多种调节手段的多目标运行优化。同时,以基于灰靶决策技术的LDBAS算法和二阶锥优化的混合方法为规划优化的求解工具。在IEEE 33节点配电系统上仿真,测试结果证明了所提两阶段协调规划模型能够有效地提高系统运行效率、增强灵活性、降低运行安全风险及经济成本。     

考虑需求响应影响的含分布式电源的配电网多目标协调规划

分析了考虑需求响应影响的含分布式电源(DG)的配电网多目标协调规划问题,建立了以DG综合投资成本(包括DG安装及运行维护成本、购电综合成本、需求响应运行成本、网络损耗成本和环境效益)最小为目标的模型,综合考虑网络系统安全约束和需求响应运行约束条件,实现DG位置和容量的协调规划。利用自适应粒子群算法对IEEE33节点系统进行求解,算例结果表明,该模型能有效提高可再生能源的利用率,提升含DG的配电网规划的经济性。     

Swarm-Intelligence-Based Optimal Planning of Distributed Generators in Distribution Network for Minimizing Energy Loss

This research work proposes a heuristic approach for the planning of Distributed Generator (DG) to minimize annual system energy loss. The particle-swarm-optimization-based method has been used as an optimization tool for determining the optimal size and allocating the DGs to minimize energy loss. In this approach, time-varying characteristics of electrical load demand have been considered to mimic real load scenario in the electrical distribution system. The proposed approach is generic and simple. It can provide optimal solutions to the distribution utilities to select multiple DGs in stages under various constraints. The effectiveness of the proposed approach is validated on 16-, 33-, and 69-bus radial distribution networks. The results are compared with those of already existing methods as suggested in the literature.     

Distribution system planning considering integration of distributed generation and load curtailment options in a competitive electricity market

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new technologies, new energy trading strategies and new deregulated environment. In the new deregulated energy market and considering the incentives coming from the technical and economical fields, it is reasonable to consider distributed generation (DG) as a viable option to solve the lacking electric power supply problem. This paper presents a mathematical distribution system planning model considering three planning options to system expansion and to meet the load growth requirements with a reasonable price as well as the system power quality problems. DG is introduced as an attractive planning option with competition of voltage regulator devices and interruptible load. In mathematical model, the object function includes investment costs, which are evaluated as annualized total cost, plus total running cost as well as cost of curtailed loads and losses. This model identifies the optimal type, size and location of the planning options. In the studies presented in this paper also the fluctuation of load and electricity market price versus time period and the effect of DG placement on system improvement are considered. To solve the proposed mathematical planning model a new software package interfacing MATLAB and GAMS is developed. This package is enabling to solve large extent distribution system planning program visually and very fast. The proposed methodology is tested in the case of the well-known IEEE 30-bus test system.     

Optimal integration of DGs into radialdistribution network in the presence ofplug-in electric vehicles to minimize dailyactive power losses and to improve thevoltage profile of the system using bioinspiredoptimization algorithms

Purpose: The increase in plug-in electric vehicles (PEVs) is likely to see a noteworthy impact on the distribution system due to high electric power consumption during charging and uncertainty in charging behavior. To address this problem, the present work mainly focuses on optimal integration of distributed generators (DG) into radial distribution systems in the presence of PEV loads with their charging behavior under daily load pattern including load models by considering the daily (24 h) power loss and voltage improvement of the system as objectives for better system performance. Design/methodology/approach: To achieve the desired outcomes, an efficient weighted factor multi-objective function is modeled. Particle Swarm Optimization (PSO) and Butterfly Optimization (BO) algorithms are selected and implemented to minimize the objectives of the system. A repetitive backward-forward sweep-based load flow has been introduced to calculate the daily power loss and bus voltages of the radial distribution system. The simulations are carried out using MATLAB software. Findings: The simulation outcomes reveal that the proposed approach definitely improved the system performance in all aspects. Among PSO and BO, BO is comparatively successful in achieving the desired objectives. Originality/value: The main contribution of this paper is the formulation of the multi-objective function that can address daily active power loss and voltage deviation under 24-h load pattern including grouping of residential, industrial and commercial loads. Introduction of repetitive backward-forward sweep-based load flow and the modeling of PEV load with two different charging scenarios.     

A novel optimal distribution system planning framework implementing distributed generation in a deregulated electricity market

This paper introduces a new framework included mathematical model and a new software package interfacing two powerful softwares (MATLAB and GAMS) for obtaining the optimal distributed generation (DG) capacity sizing and sitting investments with capability to simulate large distribution system planning. The proposed optimization model allows minimizing total system planning costs for DG investment, DG operation and maintenance, purchase of power by the distribution companies (DISCOs) from transmission companies (TRANSCOs) and system power losses. The proposed model provides not only the DG size and site but also the new market price as well. Three different cases depending on system conditions and three different scenarios depending on different planning alternatives and electrical market structures, have been considered. They have allowed validating the economical and electrical benefits of introducing DG by solving the distribution system planning problem and by improving power quality of distribution system. DG installation increases the feeders’ lifetime by reducing their loading and adds the benefit of using the existing distribution system for further load growth without the need for feeders upgrading. More, by investing in DG, the DISCO can minimize its total planning cost and reduce its customers’ bills.     

提升配电网供电性能的风-光-储两阶段规划与配置

针对配电网中分布式电源（DG）不合理规划引起供电性能下降的问题,文中提出了一种在风-光-储接入情况下的配电网两阶段规划与配置方法。第一阶段通过计算节点有功网损灵敏度确定风-光电源的接入位置和容量,第二阶段以储能接入容量最小,系统电压稳定指标最大,负荷缺电率最小建立多目标规划模型,同时结合节点平均等效负荷对储能充/放电进行管理。为提高第二阶段多目标问题的求解精度,提出了一种基于多目标粒子群算法的混合智能求解算法用于求解第二阶段模型,最后利用序数偏好法（TOPSIS）选出储能最优接入方案。为验证本文所提方法的有效性在IEEE-33节点系统上设置四种场景进行仿真测试,结果表明所提方法可以明显改善配电网的运行情况,给相关规划与配置提供借鉴与参考。     

多馈入交直流系统关联测量分散协调控制

介绍了关联测量分散控制基本原理,针对多馈入交直流系统,采用关联测量的分散协调控制原理推导直流线路的附加控制策略,提出基于关联测量矢量直流系统附加控制的分散协调控制策略.该方法只需要当地信号,控制结构简单,易于实现.算例结果表明,该方法能够充分利用HVDC的快速响应能力,实现多条直流线路的分散协调控制、功率支援和电压保持,具有很好的鲁棒性并能提高系统的稳定性.     

计及不确定性因素的配电网网架规划方法

为了在配电网网络架构规划中计及分布式电源出力与负荷不确定性的影响,提出了模糊规划法。通过三角模糊数表述分布式电源(Distributed Generation, DG)出力的不确定性,并利用可信度理论构建配电网网架规划模型;提出了一种快速生成树算法形成待规划系统的初始网络架构,再利用遗传算法对初始网架进行调整寻优,最终得到系统最优网架。通过算例仿真验证了该方法的有效性。     

Long term scheduling for optimal allocation and sizing of DG unit considering load variations and DG type

This paper proposes a new long term scheduling for optimal allocation and sizing of different types of Distributed Generation (DG) units in the distribution networks in order to minimize power losses. The optimization process is implemented by continuously changing the load of the system in the planning time horizon. In order to make the analysis more practical, the loads are linearly changed in small steps of 1% from 50% to 150% of the actual value. In each load step, the optimal size and location for different types of DG units are evaluated. The proposed approach will help the distribution network operators (DNOs) to have a long term planning for the optimal management of DG units and reach the maximum efficiency. On the other hand, since the optimization process is implemented for the entire time period, the short term scheduling is also possible. The proposed method is applied to IEEE 33-bus test system using both the analytical approach and particle swarm optimization (PSO) algorithm. The simulation results show the effectiveness and acceptable performance of the proposed method.     

Reliability centered planning for distributed generation considering wind power volatility

This paper investigates a stochastic planning model to minimize the lifecycle cost of distributed generation (DG) systems under the energy reliability criterion, namely the loss-of-load probability. In particular, our study focuses on the DG system penetrated by renewable wind technology. The optimization is formulated to determine the wind turbine capacity and their placement in the DG system with the intent to minimize the capital, operational and environmental costs. Statistical moments including mean and variance are utilized to characterize the wind power volatility and the load uncertainty. Genetic algorithm combined with heuristic search is used to find the best sitting and sizing of the distributed energy recourses. Our study is among the first attempts in the literature to model and optimize DG system based on continuous probabilistic theory. The moment methods are shown to be effective in characterizing the stochastic behavior of wind power and load dynamics. Case studies are provided to demonstrate the application and performance of the planning method.     

Distribution network expansion planning and DG placement in the presence of uncertainties

Distribution network expansion planning (DNEP) is one of the most important tools to deal with the demand growth in a system. DNEP is usually carried out through reinforcement or installation of new components. In this paper, a new and combined methodology is used to consider several practical aspects in DNEP such as uncertainty, distributed generation (DG), load growth, electricity market and multi stage dynamic expansion are included in the planning. So that DNEP is addressed in the presence of distributed generation (DG), considering load and price uncertainties under electricity market environment. The proposed planning aims at minimizing investment and operational costs simultaneously. Since DNEP in coordination with DG planning leads to reduce planning cost; therefore, the coordinated DNEP and DG planning are presented in this paper. The proposed planning is implemented by the particle swarm optimization (PSO) technique. Besides, the uncertainties are modeled as the probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert the uncertainties into the programming. The proposed planning is carried out based on the 9-bus as well as Kianpars–Ahvaz test systems (Kianpars–Ahvaz is a practical network in Ahvaz province, Iran). The simulation results demonstrate the ability and effectiveness of the proposed planning to deal with uncertainties under electricity market environment.     

基于有序充电策略的换电站及分布式电源多场景协调规划方法

通过引入电动汽车换电站的有序充电策略,以系统建设运行成本、综合净负荷波动指标以及网络能量损耗最小为目标,提出统筹考虑电动汽车换电站和分布式电源的多场景协调规划方法,并给出满足电动汽车换电需求约束和备用电池存在性约束的备用电池调度方案和最少备用电池计算方法。结合风光电源出力的季节特性,针对IEEE 33节点系统,利用生物地理优化算法进行多场景规划仿真分析,验证了所提规划方法可利用换电站有序充电策略平抑配电网综合净负荷波动,起到了削峰填谷的作用,大幅降低了网络能量损耗,显著提高了风光电源的可规划容量;同时所采用的最少备用电池计算方法,可充分考虑换电站内备用电池在一天中的循环利用,在维持有序充电策略周转的前提下能有效缓解电池储备压力,大幅降低了换电站投资成本。     

有源配电网分布式电源与智能软开关三层协调规划模型

当前配电系统调节能力的欠缺严重限制了高比例可再生分布式电源(DG)的广泛并网。在以智能软开关(SOP)为代表的电力电子装置接入系统的趋势下,考虑系统规划与运行优化相结合,协调DG运营商与配电公司的利益需求,提出一种有源配电网DG与SOP三层协调规划模型。上层以DG运营商单位容量收益最大化为目标进行DG规划,中层以配电公司年综合成本最小化为目标进行SOP规划,下层以场景内运行成本最小化为目标优化系统运行状态,决策DG消纳量返回上层与中层模型。采用场景分析法解决DG与负荷的随机性问题,基于并行遗传算法和锥规划的混合算法求解模型。最后以IEEE 33节点系统为例,与仅规划DG,DG和SOP先后规划的情况对比,结果表明兼顾系统运行优化的DG与SOP协调规划有利于满足不同主体的利益需求,提高规划方案可行性。     

考虑多种分布式电源及其随机特性的配电网多目标扩展规划

为了增强新建配电网环网转供能力,提高供电可靠性,同时减小投资和运行维护成本,提出了一种分布式电源(DG)选址定容和多供电途径的网状新建配电网协调规划方法。该方法建立了考虑经济性、可靠性和稳定性的多目标优化模型,优化求解采用两层嵌套的粒子群算法。在规划中考虑了风电、光伏、燃气轮机、储能电池4种DG的选址和定容。针对输出功率不确定的DG,建立了概率模型,利用多状态系统理论,将随机性问题转化为确定性问题。最后以某开发区的实际配电系统为例,验证了所提模型和方法的合理性。     

Dynamic sub-transmission system expansion planning incorporating distributed generation using hybrid DCGA and LP technique

Since the emerging of distributed generation (DG) technologies, their penetration into power systems has provided new options in the design and operation of electric networks. In this paper, DG units are considered as a novel alternative for supplying the load of sub-transmission system. Thus, the mathematical model of considering DG on the expansion planning of sub-transmission system is developed. Fix and variable costs of the plan and the related constraints are formulated in the proposed model. The proposed objective function and its constraint are converted to an optimization problem where the hybrid decimal codification genetic algorithm (DCGA) and linear programming (LP) technique are employed to solve it. Solution of the proposed method gives the optimal capacity of substations; optimal location and capacity of DGs as well as optimal configuration of the sub-transmission lines. To demonstrate the effectiveness of the proposed approach, it is applied on a realistic sub-transmission system of Zanjan Regional Electrical Company, Iran, and the results are evaluated.     

主网与配电网协调规划的评价指标和规划方法

城市110 kV变电站作为连接主网与配电网的纽带,其选址和供电范围的划分是主网与配电网协调(以下简称主配网协调)规划的关键.文中提出协调因子及主配网协调规划评价模型,强调以提高总体运行均衡性为目标的电网规划思想.首先对变电站的基本属性进行分析,提出由运行率和关联度构成的负重系数的概念;然后利用约束圆环协调规划范围,将负重系数作为权值,利用改进后的加权Steiner最小树理论优化变电站选址;进而确定变电站的容量及供电范围.实际算例表明,从主配网协调程度考虑,所提出方法的规划结果优于传统选址规划结果.     

分布式发电规划的负荷模型研究

分布式发电大规模接入配电网,是当前电力系统面临的挑战之一.虽然学术界广泛认同分布式发电具有降低系统网损的的潜力,但是如果计算过程中负荷建模不当,很可能会影响分布式发电规划的准确性.研究配电网负荷模型对分布式发电规划的影响,采用综合电力负荷模型将配电网负荷分为居民用电、工业用电和商业用电,对比分析了不同负荷模型对含分布式发电的配电网损的影响.对一38节点配电系统进行分析,计算不同分布式发电接入方案以及采用不同负荷模型时系统的网损.算例的仿真结果表明,负荷模型的选取对分布式发电的规划具有重要影响.