基于最优潮流的无功定价方法探讨

电力市场环境下精确可行的无功服务定价是近年来研究的热点问题。将无功发电机会成本和无功补偿设备的投资加入到最优潮流的目标函数中,并考虑旋转备用的重要性,加入旋转备用约束条件,提出了新的基于最优潮流的无功功率实时定价模型。并对IEEE4-57节点系统进行了测试,所得的无功电价既能涵盖大部分的无功生产费用,又能提供足够的经济信息。     

A new approach for cost allocation and reactive power pricing in a deregulated environment

Power industry has been facing restructuring problems during the past decade. Appropriate management of reactive power is very essential for supporting power system security. Reactive power has dominant effects on real energy transfer. Furthermore, it can support the secure operation of the system as an ancillary service. However, most researches have been focused on active power as the main good transacted in electricity markets. On the other hand, while reactive power production cost is highly dependent on real power output, it is mainly confined to local consumption. As a result, to avoid market power and to maintain the secure operation of the system, a fair cost allocation method seems to be very essential. Appropriate pricing of reactive power as an ancillary service has been a challenging problem during the past decade. However, most methods proposed so far for reactive power pricing are essentially based on empirical approximations. In this paper, a new method for reactive power cost allocation is proposed. The method is based on calculation of the accurate cost which will be imposed on generators due to supporting reactive power. The proposed method is fair, accurate and realistic and it can be formulated very easily. Furthermore, a new approach based on tracing algorithm is proposed for pricing of reactive power which considers the cost of both active and reactive losses allocated to each generator. Application of the proposed method on IEEE 9-bus standard network confirms its validity and effectiveness.     

电力市场环境下的无功采购

在放松管制后的电力市场环境下,无功支持被视为一种重要的辅助服务.采用市场手段来获取无功服务可以激励无功供应商积极提供系统所需的无功出力,并有利于引导合理的无功投资.文章首先提出了一种分段形式的发电机无功报价模型,其包括容量报价和电量报价两部分.这种模型既可以满足无功供应商全面回收成本的需要,也兼顾了在很多实际运营的电力市场中对各发电机所施加的强制无功出力要求.在此基础上,给出了四种不同目标的无功采购模型,分别为:优化系统网损、优化系统采购成本、优化电能质量以及优化系统安全性.最后,通过算例计算对采用这四种模型下所得到的结果进行了比较和分析.     

基于最优潮流的实时无功辅助服务定价分析

从发电机的功率运行极限出发,分析无功功率的生产费用曲线。基于最优潮流以有功功率和无功功率生产费用最小为模型、以IEEE30节点系统为算例,总结出无功电价与无功负荷大小并不呈正比关系,而是受无功源距离远近的影响,验证该定价方法能够在比较合理的电价水平上保证有功功率和无功功率生产投资费用的有效回收。在概括国内外研究成果的基础上提出无功定价的研究方向。     

计及无功功率成本及其资源价值的无功采购方法

电力市场中，满足负荷无功功率需求以及提供系统电压支持属于辅助服务的范围，一般由系统运行员（ISO）进行集中优化调度和控制计算，向相应的辅助服务提供者购买无功功率，并将成本分摊到用户。在分析无功和电压支持的特点，无功的生产成本和资源价值的基础上，文中提出了一种新的无功／电压辅助服务市场机制，并设计了向发电机，调相机等动态无功源采购无功功率的算法，该算法的特点是：考虑了无功的容量成本和电量成本；引入基于等效无功补偿法的无功价值因子，从而考虑了系统中不同位置无功源的资源价值差异，计及了无功分布对有功网损以及相应的有功功率生产成本的影响。IEEE14节点系统的算例表明，该方法能够优化无功采购成本，算法合理有效。     

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.     

基于功率贡献的负荷电价计算

合理地制定负荷电价是电力市场中的一个重要问题。文中提出了一种应用叠加原理求解某一潮流运行点下各电源对负荷的有功、无功贡献，依据综合成本分摊进行负荷电价计算的电力定价新方法。该方法适用于存在环流的网络，有效地解决了发电机进相运行时生产成本的回收问题，并将负荷有功、无功电价计算有效地统一起来；该方法计算简单、实用性强。文中以IEEE 14节点系统为例进行了负荷电价仿真计算，验证了该方法的合理性。     

Swarm intelligence based algorithms for reactive power planning with Flexible AC transmission system devices

In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive Particle Swarm Optimization) and EPSO (Evolutionary Particle Swarm Optimization) are used for the optimal setting of the Var sources and FACTS devices. The result obtained with the proposed approach is compared with the result found by the conventional RPP (Reactive power planning) approach where shunt capacitors, transformer tap setting arrangements and reactive generations of generators are used as planning variables. It is observed that reactive power planning with FACTS devices yields much better result in terms of reducing active power loss and total operating cost of the system even considering the investment costs of FACTS devices.     

Active and reactive dispatch with minimum control movements

This paper proposes a new formulation of the combined Optimal Active and Reactive Dispatch (OARD) problem with Minimum Control Movements (MCM) for the voltage control devices. The main objective of the proposed model is to minimize the total power system operation cost which include fuel cost of generators and switching cost of equipments like tap transformers and shunt capacitors. Practical constraints such as maximum allowable number of switching operation in a day for tap changing transformers and switchable capacitors are taken into consideration. A penalty based approach has been formulated to tackle with the switching costs of adjustable equipments. The problem has been formulated as a nonlinear dynamic optimization problem with the presence of both continuous and discrete control variables and solved using Artificial Bee’s Colony (ABC) algorithm. The approach has been tested on IEEE 30 bus system and the simulation is carried out in MATLAB. In order to verify the effectiveness of the results obtained, both active and reactive power dispatch problems have been solved separately and compared with the proposed approach. Results demonstrate the effectiveness of the proposed approach.     

多种运行方式下的无功定价方法

提出了多种运行方式下多目标优化的无功定价机理。提出的优化算法协调了系统的经济性和电能质量,其中系统经济性的无功优化采用系统无功成本和系统有功网损最低;基于电能质量的无功优化采用运行方式发生改变时电压偏离当前值最小,通过无功的有效调整获得了优化的电压特性。提出的无功等值电价为无功电量电价和容量电价之和,该定价方法符合无功成本特征,其价格机制具有市场公平性、注重无功投资回报和抑制价格尖峰的特性。通过IEEE 30系统算例验证了该价格模型的有效性和实用性。     

Congestion management considering hydro-thermal combined operation in a pool based electricity market

This paper proposes a novel congestion management strategy for a pool based electricity market considering combined operation of hydro and thermal generator companies. The proposed congestion management problem is formulated as mixed binary nonlinear programming problem to minimize the cost of re-dispatching the hydro and thermal generator companies to alleviate congestion subject to operational, line overloading and water availability constraints. A piecewise-linearized unit performance curve is used in this formulation, which takes into account its non-concave nature. The effectiveness of the proposed technique is demonstrated by solving the modified IEEE 57-bus and IEEE 118-bus systems for congestion management under line outages.     

Distributed control algorithm for optimal reactive power control in power grids

Reactive power generation has been commonly used for power loss minimization and voltage profile improvement in power systems. However, the opportunity cost of reactive power generation should be considered since it affects the frequency control capability of the generator to some degree. This paper proposed a distributed nonlinear control based algorithm to achieve the optimal reactive power generation for multiple generators in a power grid. The reactive power control setting update for each generator only requires local measurement and information exchange with its neighboring buses. It is demonstrated that the proposed algorithm can reduce the non-convex objective function monotonically till convergence and achieve comparable solutions to the centralized technique: particle swarm optimization with faster convergence speed. The proposed algorithm has been tested on the IEEE 9-bus, 39-bus and 162-bus systems to validate its effectiveness and scalability.     

基于连续潮流的配电网供电能力评估

随着非全相运行的分布式电源大量接入配电网,配电网固有的三相不平衡特征更加突出,传统配电网供电能力评估因忽略配电网三相不平衡特征导致结果不准确。为了准确分析三相不平衡特征对配电网最大供电能力评估的影响,建立了以配电网供电负荷参数最大为目标函数,考虑了支路热约束和节点电压等状态变量和分布式电源的有功和无功功率等控制变量的含分布式电源三相不平衡配电网供电能力评估模型。选择电压跌落情况最严重的相作为连续参数,确保预测-校正过程的的连续潮流法求解的结果更加精确。最后,采用拓展的IEEE33节点配电系统进行仿真验证,表明文中所提的模型和求解方法是有效的。     

Two-stage optimization algorithm for short-term reactive power planning based on zonal approach

There are various methods for procurement of reactive power as an ancillary service in deregulated market environment. Reactive power market model based on voltage control zones and two-step optimal power flow algorithm is proposed in this paper. Zones are formed by splitting the power system or a control area of an interconnected power system into autonomous voltage sub-areas with sufficient reactive power reserves using the electrical distance method. Every zone formes a single reactive power market. First step of an optimization algorithm determines zonal reactive power prices based on generator's cost functions for reactive power production. Total cost minimization is the goal of the second optimization step where the final dispatching decision is made according to transmission losses and zonal reactive power prices respecting power system planned conditions and security constraints. Proposed algorithm is tested on IEEE 39 bus test system ensuring the system operator's minimal payment for reactive power and transmission losses, without jeopardizing power system security.     

A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects

Economic dispatch (ED) generally formulated as convex problem using optimization techniques by approximating generator input/output characteristic curves of monotonically increasing nature results in an inaccurate dispatch. The genetic algorithm has previously been used for the solution of problem for economic dispatch but takes longer time to converge to near optimal results. The hybrid approach is one of the methodologies used to fine tune the near optimal results produced by GA. This paper proposes new hybrid approach to solve the ED problem by using the valve-point effect. The approach we propose combines the genetic algorithm (GA) with active power optimization (APO) based on the Newton's second order approach (NSO). The genetic algorithm acts as a global optimizer giving near optimal generation schedule, which becomes the input for generation buses in APO algorithm. This algorithm acting as local search technique dispatching the generated active power of units for minimization of cost and gives optimum generation schedule. Three machines 6-bus, IEEE 5-machines 14-bus, and IEEE 6-mchines 30-bus systems have been tested for validation of our approach. Results of the proposed scheme compared with results obtained from GA alone give significant improvements in the generation cost showing the promise of the proposed approach.     

Optimal Power Flow using Glowworm Swarm Optimization

An important objective of the Optimal Power Flow (OPF) problem is to minimize the generation cost and keep the power outputs of generators, bus voltages, bus shunt reactors/capacitors and transformer tap settings in their secure limits. Solving this OPF problem using classical methods suffer from the disadvantages of highly limited capability to solve the practical large scale power system problems. To overcome the inherent limitations of conventional optimization techniques, Swarm Intelligence (SI) methods have been developed. However, the environmental concern, dictate the minimization of emissions of the thermal plants. Individually, if one objective is optimized, other objective is compromised. Hence, Multi-Objective Optimal Power Flow (MO-OPF) problem has been formulated in this paper. Swarm Intelligence methods, such as Particle Swarm Optimization (PSO) and Glowworm Swarm Optimization (GSO) have been used to solve the OPF problem with generation cost and emission minimizations as objective functions. The effectiveness of the proposed algorithms are tested on IEEE 30 bus and practical Indian 75 bus systems for cost minimization as objective function, and IEEE 30 bus test system for minimization of cost and emission as objectives. The results obtained from both the networks, the PSO and GSO are compared with each other based on different parameters.     

Stochastic optimal power flow incorporating offshore wind farm and electric vehicles

In this paper, an optimal power flow model of a power system, which includes an offshore wind farm and plug-in electric vehicles (PEVs) connected to grid, is presented. The stochastic nature of wind power and the uncertainties in the EV owner’s behavior are suitably modelled by statistical models available in recent literatures. The offshore wind farms are assumed to be composed of doubly fed induction generators (DFIGs) having reactive power control capability and are connected to offshore grid by HVDC link. In order to obtain the optimal active power schedules of different energy sources, an optimization problem is solved by applying recently introduced Gbest guided artificial bee colony algorithm (GABC). The accuracy of proposed approach has been tested by implementing AC–DC optimal power flow on modified IEEE 5-bus, IEEE 9-bus, and IEEE 39-bus systems. The results obtained by GABC algorithm are compared with the results available in literatures. This paper also includes AC–DC optimal power flow model, implemented on modified IEEE-30 bus test system by including wind farm power and V2G source. It has been shown that the uncertainty associated with availability of power from wind farm and PEVs affects the overall cost of operation of system.     

A multi-year transmission planning under a deregulated market

Due to the deregulation of power industry, the transmission expansion plan is different from the process done by the integrated monopolies. In a monopoly electric market, the transmission expansion plan is carried out by the vertically integrated utility. The power company integrates its generations’ exploiting plans and its transmission expansion plans to maintain the system reliability. While in a deregulated power industry, generation, transmission, and distribution companies belong to different owners. The problem becomes more difficult. Generators experiencing transmission constraints can be expected to lobby for new transmission facilities that might relieve their constraints, while generators closer the load centers will likely toward not to build any new transmission facilities that would increase their competition. In order to provide a fair environment for all market participants, this paper proposed a reasonable expansion plan taking the operation cost, load curtailment cost, and investment cost into account. Due to the complexity of this model, the algorithm that combines the genetic algorithm with the linear programming method (GA-LP) is used to solve this problem. The 6-bus system and 24-bus IEEE reliability test system are used to verify the proposed model, and comparisons of test results between the proposed model and the traditional model are also demonstrated in this paper.     

单相光伏大量接入的三相不平衡配电网无功优化

随着光伏发电等大量非全相运行的分布式电源(DG)接入,配电网固有的三相不平衡特征更加突出,传统无功优化方法因忽略了三相不平衡导致效果较差。文中提出一种三相不平衡主动配电网的无功优化模型,以系统负序电压最小和网络损耗最小为目标,考虑有载调压变压器、分组投切电容器、静止无功补偿装置等离散和连续控制变量,形成一个带有二次约束的混合整数二次规划问题。利用分支定界法处理该混合整数规划问题,将原问题松弛为多个不含离散变量的子问题,分别求得各子问题中设备的控制量,进而求得原问题的最优解。采用扩展的IEEE 33节点三相测试系统仿真计算,验证了所述模型和方法的有效性。     

多源协同的配电网多时段负荷恢复优化决策方法

当极端灾害引起大停电事故时,可协同多种电源和储能快速恢复重要负荷,提升配电网韧性。首先探讨多源协同故障恢复对配电网韧性的提升作用,然后以最大化负荷的加权供电时间及最小化总网损为目标,以各时段负荷状态、电源输出功率及线路投运状态为优化变量,考虑有限能量约束、运行约束和拓扑约束等,将多源协同的配电网多时段负荷恢复问题建模并松弛为混合整数二阶锥规划模型,并利用商业优化软件求解,得到最优恢复策略。最后,通过改进IEEE 13节点和IEEE 123节点配电系统标准算例和仿真验证了所提方法的有效性和优越性。