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.     

考虑负荷率的不同电压等级可选择两部制输配电价

考虑负荷率的可选择输配电价套餐模型是我国省级电网输配电价改革中的重要技术理论问题之一。针对此本文应用峰荷责任法和输配电成本逐级传导法,建立了计及负荷率的不同电压等级用户输配电成本模型;结合系统负荷率同时率关系的统计特性,应用激励机制设计理论,构造了考虑负荷率的可选择两部制输配电价模型;经严格数学推导证明该套餐模型满足激励相容约束,揭示了其具备选择性及其成立条件,能够科学地甄别用户负荷率的真实信息,能够有效解决选择性定价的逆向选择问题。算例验证表明该模型既能反映不同负荷率和电压等级用户的真实输配电成本,实现公平定价;又能鼓励用户合理用电,提高送变电设备利用率,降低和延缓电网投资;当选项数目为4~5项时,该套餐的定价效果就能够接近完全非线性价格形式。     

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.     

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.     

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。     

Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm

Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the installation of both feeders and substations reinforcement and DG integration at different times are considered in the formulation of a minimum cost distribution systems reinforcement strategy problem. An application on a medium size network, hypothesizing a scenario of reinforcement also using as DG gas micro-turbines, is carried out using a novel optimization technique allowing the identification of optimal paths in trees or graphs. The proposed technique is the Dynamic Ant Colony Search algorithm     

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。     

考虑需求响应的CCHP系统中分布式电源的选址定容

以往对于冷/热/电联供(combined cooling heating and power,CCHP)系统的研究主要集中在其运行优化上,较少对系统中分布式电源(distributed generation,DG)的选址定容问题进行研究,更少有文献将基于价格与基于激励的需求响应(demand response,DR)综合考虑在系统中。该文利用CCHP系统的多能源互补特性,综合考虑基于价格与基于激励的需求响应,以分布式电源接入节点与接入容量为变量,提出了计及需求响应的分布式电源选址定容模型。首先,建立了CCHP系统热电耦合运行模型。其次,综合考虑负荷削减量、中断持续时间与中断时间因子等因素,提出了可中断负荷的单位电量补偿定价的方法。通过在目标函数中分析需求响应成本,使规划目标更为全面,从而节约投资。另外,综合基于激励与基于价格的需求响应作用,考虑用户对于电价、燃气价格、可中断负荷单位电量补偿定价的响应,定义了改进的价格弹性系数,并利用此系数对负荷预测进行修正。最后,通过基于邻域再搜索的改进粒子群算法(neighborhood re-dispatch particle swarm optimization,NR-PSO)对规划模型进行求解,并通过对某13节点综合园区系统的仿真分析,验证了所提模型及方法的有效性。     

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。     

需求侧管理参与的孤岛型微电网多目标优化调度

分析了MG中分布式电源的功率特性和需求侧响应的基本理论与相关政策,并建立了DG的数学模型和基于负荷分类的DR模型;综合考虑微源的出力成本、需求侧管理成本和环境治理费用,建立了考虑需求侧管理的多目标微电网优化调度模型,引入不同的孤岛微电网运行评价指标评价DR对微电网经济性、环保性以及可靠性的影响,并选择不同的场景分析验证。采用改进粒子群算法优化外点法对规划问题进行求解,在将约束条件纳入目标函数的同时,尽可能避免求解规划时陷入局部极值的问题。算例分析表明,通过考虑需求侧管理,可以增加可再生能源的消纳,减轻负荷高峰时段的供电压力,缓解孤岛系统供电不足的问题,并有效提高微电网的整体效益。     

解除管制的电力零售市场实时电价研究

零售侧打破垄断引入竞争是电力市场发展的趋势,制定合理的零售电价是市场开放的关键.根据电力零售市场的特点,基于负荷价格响应的定义以及边际成本定价理论,推导出了考虑负荷价格响应的有功实时电价的表达式.以社会成本最大化为目标函数,建立了考虑负荷价格响应特性的最优潮流模型,从而求解出未来引入竞争的电力零售市场中电力库交易模式下的实时电价.采用32节点配电系统对所提方法进行仿真,结果证明为促进零售市场竞争、引导用户合理用电提供了合理有效的定价方法.     

基于随机潮流的含电动汽车配电网内分布式电源规划

随着分布式电源(DG)和电动汽车的大量发展,对接入配电网的电动汽车与DG进行协同研究具有重要意义。文中以协调配电公司、DG投资商和公共社会三者之间利益为出发点,综合考虑了配电公司的运行费用、DG投资商的投资费用,以及DG的环境效益和电动汽车入网(V2G)所节省的电网投资等社会效益,建立了基于机会约束规划的含V2G配电网中DG优化规划的数学模型,采用基于混合编码的改进自适应遗传算法对该模型进行了求解。在优化计算过程中充分考虑了负荷预测值的不确定性、风电源的输出功率的随机性以及电动汽车充放电功率的不确定性,提出了电动汽车充放电对系统最大功率影响的数学模型,并采用基于半不变量法的随机潮流算法对规划模型中的约束条件进行了检验。最后,以某实际配电网系统为仿真算例,在不同置信水平约束下对该系统内DG分别进行了优化规划,验证了文中所建数学模型及相应求解算法的有效性。     

考虑风-光-荷时空相关性的分布式电源和广义储能联合规划

在分布式电源(DG)和广义储能(GES)联合规划中,针对运行与规划如何紧密耦合、在获取大量分散资源行为规律的基础上如何预测其在规划周期内的关联特性的难题,提出了多能互补发电系统中DG与GES的双层优化规划方法.上层以新能源历史出力为输入,建立了考虑综合成本、DG承载能力和系统综合运行风险的上层规划模型,决策得到DG和GES的安装方案;下层考虑运行成本以平衡各储能系统的充放电功率,决策得到GES的调度策略.提出了可描述多维风-光-荷时空相关性的MD-K2贝叶斯网络模型,用于实现多元数据驱动下DG和GES的协同优化.算例测试结果验证了所提模型和方法的合理性以及有效性.     

区域配电网内分布式电源和负载联盟交易模式设计和分析

分布式电源和负载可在配电侧形成电能供给和消费的联盟,并参与区域电力市场交易。相比于单独进行交易,这样的联盟通过帮助市场能力较弱的分布式电源和负载参与到配电网市场中,推动配电网中的中小型负载和分布式电源之间的直购电业务的发展,促进配电网侧的电力市场形成;同时利用市场信号引导分布式电源和负载的电能生产和消费过程,使得它们获得更多的经济利益,促进分布式可再生能源的发展。文中给出了区域配电网中联盟交易模式的存在条件,并且基于公用电网的作用和合作博弈理论,建立了相应的交易价格模型。进一步,以集成售电商的收益为优化目标,构建了联盟选择和定价的优化决策模型。仿真算例说明了联盟交易模式的理论可行性,证明了在不同运行场景中所提优化决策模型的有效性。     

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。     

Optimal DG placement in deregulated electricity market

This paper presents two new methodologies for optimal placement of distributed generation (DG) in an optimal power flow (OPF) based wholesale electricity market. DG is assumed to participate in real time wholesale electricity market. The problem of optimal placement, including size, is formulated for two different objectives, namely, social welfare maximization and profit maximization. The candidate locations for DG placement are identified on the basis of locational marginal price (LMP). Obtained as lagrangian multiplier associated with active power flow equation for each node, LMP gives the short run marginal cost (SRMC) of electricity. Consumer payment, evaluated as a product of LMP and load at each load bus, is proposed as another ranking to identify candidate nodes for DG placement. The proposed rankings bridges engineering aspects of system operation and economic aspects of market operation and act as good indicators for the placement of DG, especially in a market environment. In order to provide a scenario of variety of DGs available in the market, several cost characteristics are assumed. For each DG cost characteristic, an optimal placement and size is identified for each of the objectives. The proposed methodology is tested in a modified IEEE 14 bus test system.     

考虑主动管理措施的配电网无功补偿双层优化配置

为了适应未来大量分布式电源(DG)并网及自动化水平显著提高的主动配电网发展,在规划阶段应该考虑主动管理措施,优化系统运行方式。同时,现有的无功补偿规划研究忽略了DG及负荷的不确定性。为此,计及间歇性DG及负荷的不确定性,提出主动配电网无功补偿双层优化配置模型。上层规划以无功补偿电容器的投资成本、网络损耗费用综合最优为目标函数,下层规划在此基础上考虑调节无功补偿容量及调节有载变压器抽头两种主动管理措施,对每个场景进行优化。采用K-均值聚类法对场景进行缩减,结合和声搜索算法和粒子群算法联合求解模型。通过IEEE33节点算例进行仿真计算,验证所提模型和方法的正确性。     

Planning for distributed generation

Distributed generation (DG) can be incorporated into distribution planning as an option along with traditional feeder and substation options. In place of rigid capacity planning rules, the planning process needs to incorporate more detailed simulations of capacity constraints and customer damage costs because utilities now assume more risk. Planning tools need to simulate load variations, contingencies, dispatch and control action to more accurately determine the capacity limits and related costs. This is especially important when considering DG because the siting and dispatch have an important impact on the benefits to the utility. Equally important is the evaluation of economic risk given uncertainties such as load growth. Because of the added complexities associated with these analysis techniques, the planning process must incorporate appropriate screening tools to determine the depth of analysis needed for particular projects, thereby making more efficient use of already scarce planning resources     

考虑风电不确定性的蓄热式电采暖消纳弃风经济性分析

针对冬季采暖期我国北方地区严重弃风和燃煤导致的空气污染问题,综合考虑风电预测误差及供给价格弹性,以采暖期系统运行成本最小为优化目标,构建基于终端热负荷特性的电锅炉日前优化调度模型,并在电力市场背景下分析了蓄热式电采暖供暖系统的运行经济性。通过引入储热装置来更加合理地利用各时段弃风电量,从而进一步提高供热系统运行经济性。在求解阶段,采用CPLEX软件包下的分支定界法(BBA)对模型求解,并通过具体算例仿真结果验证了所提方法的有效性。     

基于委托-代理理论的负荷率可选择电价最优合约设计

首先以综合成本定价法为基础,分析了考虑负荷特性的不同电压等级用户的供电成本;在此基础上,应用经济学委托-代理理论,建立了考虑负荷率的两部制可选择电价委托-代理模型;经过严谨的数学推导给出了该制度安排问题的数学解析解,即求得最优合约函数,能够有效解决选择性定价中的逆向选择问题;算例验证表明该激励机制既能反映不同负荷率和电压等级用户的真实成本,实现公平定价,又能给予用户选择权并鼓励用户合理用电;且当选项数目为4-5项时,该套餐的定价效果能够接近完全非线性价格形式。