旋转备用的经济分配及其内点法实现

在最优潮流中,发电机组出力通常是独立变量,然而系统的旋转备用约束增加了发电机组出力间的耦合关系。基于非线性内点法针对实时旋转备用最优分配问题提出了一种解耦算法,使得发电机约束矩阵和网络约束矩阵在最优潮流中能够单独进行得到。进一步推导得到一个降阶的KKT(Karush-Kuhn-Tucker)系统,其规模由网络自身大小决定,仅通过修改扩展海森矩阵元素即可计及旋转备用约束的影响,并使用先进的超级稀疏技术全面分析、研究了该降阶KKT系统的稀疏结构。该算法涉及的旋转备用也包括了切负荷。     

Interruptible load management using optimal power flow analysis

An interruptible load management (ILM) scheme is proposed using dynamic optimal power flow analysis. It enables real-time selection of interruptible loads incorporating power network constraints and dynamic restriction on generation, viz. ramp-rate limits. The model provides an analytical framework for addressing several important issues associated with optimal selection of load curtailment, e.g. advance notification for load curtailment, short-term price discounts and long-term discounts on demand-charges, power factor of the load and customer-cost associated with the load to be curtailed, and power system security. A six-bus example illustrates the proposed methodology     

考虑源荷协调的风电并网系统旋转备用容量优化

风电的接入给电力系统带来更大不确定性,要求电网公司购买更多的旋转备用以维持电力系统的功率平衡和稳定,兼顾系统运行可靠性与经济性的旋转备用优化配置具有重要意义。考虑风电、需求侧互动资源,提出一种基于多场景的概率性旋转备用优化方法。该方法综合考虑风电预测误差、负荷波动及发电机非计划停运不确定性因素对旋转备用的需求,将弃风、可中断负荷分别作为部分负、正旋转备用融入发电日前调度计划,以购电总费用最低为目标函数建立日前机组组合优化模型,获得各时段旋转备用优化配置量。通过对IEEE 30节点、IEEE 118节点系统进行算例分析,验证了所提方法的正确性和有效性。     

基于非线性互补问题函数的半光滑牛顿最优潮流算法

提出了一种新的基于非线性互补问题(NCP)函数的半光滑牛顿方法，以用于求解最优潮流(OPF)问题。通过引入NCP函数，将OPF模型KKT条件的互补松弛约束转化为等式约束，并采用非光滑牛顿法求解。算法的突出优势在于能够有效地处理OPF模型中的不等式约束，从而完全避免了OPF计算中起作用的不等式约束的识别问题。同时，文中利用电力系统的弱耦合特性，构造了牛顿分解算法。IEEE多个算例的数值试验表明：提出的算法具有很好的收敛特性和计算效果，有很好的实际应用前景。     

A comprehensive strategy for transmission switching action in simultaneous clearing of energy and spinning reserve markets

There is a great resolution calling for smart grids in recent years. Introduction of new technologies, that make the network flexible and controllable, is a main part of smart grid concept and a key factor to its success. Transmission network as a part of system network has drawn less attention. Transmission switching as a new transmission service can release us from load shedding and remove the constraints’ violations.Transmission switching can provide economic benefits compared to other control methods such as generation unit rescheduling or load shedding for contingency management.Utilizing a stochastic mix-integer nonlinear programming (SMINLP) model, transmission switching is used during contingencies and steady state to determine optimal required energy and reserve values.Stochastic joint energy and reserve markets with transmission switching considering dynamic constraints has been proposed to minimize the cost of supplying load, security expenses.Considering dynamic constraints in proposed model avoid the occurrence of transient instability when opening the line in transmission switching action.A network reduction method based on modified Jacobean AC Newton–Raphson technique power flow considering switchable line in technique is used for speeding up the calculation, efficiency and simplicity.To investigate the efficiency of the proposed strategy IEEE 14 bus test and IEEE 57 bus test system are studied. According to the obtained results, this strategy decreases energy and reserve marginal prices, as well as security cost.     

Decomposition model and interior point methods for optimal spotpricing of electricity in deregulation environments

In this paper, an integrated optimal spot pricing model is presented first. The proposed model includes the detailed derivation of optimal nodal specific real-time prices for active and reactive powers, and the method to decompose them into different components corresponding to generation, loss, and many selected ancillary services such as spinning reserve, voltage control and security control. The features of the proposed model are discussed in relationship to existing pricing models and classical economic dispatch. The model is then implemented by modifying existing Newton OPF methods through interior point algorithms, which can effectively avoid “go” “no go” gauge (i.e. highly volatile) in the calculation of spot prices. Case studies on 5-bus and IEEE 30-bus systems are reported to illustrate the proposed method     

Energy and ancillary service dispatch through dynamic optimal power flow

This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system.     

Interior-point based algorithms for the solution of optimal power flow problems

Interior-point method (IPM) is a very appealing approach to the optimal power flow (OPF) problem mainly due to its speed of convergence and ease of handling inequality constraints. This paper analyzes the ability of three interior-point (IP) based algorithms, namely the pure primal-dual (PD), the predictor–corrector (PC) and the multiple centrality corrections (MCC), to solve various classical OPF problems: minimization of overall generation cost, minimization of active power losses, maximization of power system loadability and minimization of the amount of load curtailment. These OPF variants have been formulated using a rectangular model for the (complex) voltages. Numerical results on three test systems of 60, 118 and 300 buses are reported.     

An interior point nonlinear programming for optimal power flowproblems with a novel data structure

This paper presents a new interior point nonlinear programming algorithm for optimal power flow problems (OPF) based on the perturbed KKT conditions of the primal problem. Through the concept of the centering direction, the authors extend this algorithm to classical power flow (PF) and approximate OPF problems. For the latter, CPU time can be reduced substantially. To efficiently handle functional inequality constraints, a reduced correction equation is derived, the size of which depends on that of equality constraints. A novel data structure is proposed which has been realized by rearranging the correction equation. Compared with the conventional data structure of Newton OPF, the number of fill-ins of the proposed scheme is roughly halved and CPU time is reduced by about 15% for large scale systems. The proposed algorithm includes four kinds of objective functions and two different data structures. Extensive numerical simulations on test systems that range in size from 14 to 1047 buses, have shown that the proposed method is very promising for large scale application due to its robustness and fast execution time     

旋转备用对电网可靠性的影响及优化配置研究

旋转备用(Spinning Reserve,SR)的不同分配方案会导致不同的电网可靠性水平。从改善大电网运行可靠性的角度出发,综合考虑机组类型和爬坡速率、元件可靠性参数、网络拓扑结构以及传输容量限制等因素,将SR的优化分配纳入到最优负荷削减模型中。利用该模型不等式约束中控制参数的拉格朗日乘子的物理意义,推导出系统电力不足期望对各机组备用容量的灵敏度表达式,提出了根据该灵敏度结果进行备用优化配置的启发式思路。同时以SR成本与用户停电损失之和最小为目标,通过同步联合优化确定SR的总量与配置方案。RBTS测试系统的仿真结果表明了所提方法的有效性和正确性。     

基于系统频率响应特征的电网广义旋转备用优化配置

现有的旋转备用配置方法多将旋转备用的来源限定于常规发电机组,较少虑及储能装置与柔性负荷等新兴电力设施对旋转备用优化配置的积极影响。为此,文中提出了电网广义旋转备用的概念;借助序列化建模思路与可描述随机变量取值相依结构的Copula函数,建立电网等效负荷(电网原始负荷与对应时刻点新能源发电出力的差值)波动量与预测偏差模型;综合考虑系统频率响应特征,以电网广义旋转备用购置成本、停电损失成本与弃新能源发电成本最低为目标,提出一种基于系统频率响应的新能源高渗透电网广义旋转备用优化配置方法。以新疆某新能源高渗透区域电网实际运行数据为依据,仿真验证了所提方法的可行性。     

应用于高风电渗透率电网的风电调度实时控制方法与实现

为适应风电的快速波动,提出一种快速的风电实时控制方法,适用于高风电渗透率的电网。该方法根据自动发电控制机组的向下转旋备用、联络线功率调整偏差,在线计算电网可消纳风电裕度。然后,结合风电考核打分和网络安全约束,依据不同场景分别进行以消除断面越限为目标的校正控制、以消纳最大风电并兼顾公平调度为目标的最小弃风控制以及系统安全裕度充足下的风电自由发控制。基于所提出的方法,开发了相应系统并在某省级电网投运。测试系统的仿真和实际系统的实际运行结果证明了该方法的有效性。     

Application of linear programming redispatch technique to dynamicgeneration allocation

Consideration is given to dispatch problems that involve the allocation of system generation optimally among generating units while tracking a load curve and observing the power rate limits of the units, system spinning reserve requirements, and other security constraints. Two methods are used in the solution of the problem. The first method is a quadratic programming technique combined with a linear programming redispatch technique. The latter utilizes a linear programming formulation of the dynamic dispatch problem about the base case static economic dispatch solution. The second method is based on the Dantzig-Wolfe decomposition technique. Tests and computer results of four systems of different combinations of units and intervals are given to show the advantages of the techniques proposed     

Evaluating the integration of wind power into distribution networks by using Monte Carlo simulation

This paper provides a probabilistic method to assess the impact of wind turbines (WTs) integration into distribution networks within a market environment. Combined Monte Carlo simulation (MCS) technique and market-based optimal power flow (OPF) are used to maximize the social welfare by integrating demand side management (DSM) scheme considering different combinations of wind generation and load demand over a year. MCS is used to model the uncertainties related to the stochastic variations of wind power generation and load demand. The market-based OPF is solved by using step-controlled primal dual interior point method considering network constraints. The method is conceived for distribution network operators (DNOs) in order to evaluate the effect of WTs integration into the network. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4 kV radial distribution system.     

Composite power systems reliability evaluation based on demand-side reserve

This paper proposes new demand-side reliability indices and useful computational methods for reliability evaluation of composite power systems. These new indices are based on the active power which can reach each demand spot under generating and transmission network constraints. This conception is defined as “reachable power,” and it leads the reserve margin on each demand spot, which is called as “demand-side reserve.” If the reachable power is insufficient to satisfy the demand, load curtailment is required. In the proposed approach, the conception of the load curtailment area is defined, and the estimate method of load curtailment area is indicated. In case the reachable power exceeds the demand, system reliability is evaluated by the demand-side reserve, and the power system is divided into several reliability zones according to the demand-side reserve levels. Small system examples are used to illustrate principles of the proposed approach, and middle system examples show the effectiveness and practicality.     

Fuzzy constraint enforcement and control action curtailment in anoptimal power flow

Conventional power system optimal power flow (OPF) solutions utilize standard optimization techniques. These techniques limit the practical value and scope of OPF applications. Realistic OPF solutions require special attention to the constraint enforcement and control action curtailment. From a practical point of view, an OPF does not need to find a rigid minimum solution. Certain trade-offs among: (1) minimizing of objective function; (2) satisfying constraints; and (3) moving control variables would be desirable. In this paper, a fuzzy set method is applied to the OPF problem to model these considerations. The method has been implemented in a successive linear programming OPF package. Test results based on the PG&E network (USA) are promising     

电力市场环境中常规潮流与最优潮流在网损分摊中的应用

潮流计算是电力系统最重要的运算之一,为此,通过算例对BX型快速解耦潮流和最优潮流进行了分析.算例使用基于合作博弈论中的核仁理论的网损分摊方法对这两种潮流计算方法所计算的网损进行了分摊,计算结果表明,采用最优潮流计算网损优于使用常规潮流计算网损,并且基于最优潮流的网损分摊结果更易于被市场成员接受.     

Optimal power flow by a fuzzy based hybrid particle swarm optimization approach

This paper presents a fuzzy based hybrid particle swarm optimization (PSO) approach for solving the optimal power flow (OPF) problem with uncertainties. Wind energy systems are being considered in the study power systems. OPF is an optimization problem which minimizes the total thermal unit fuel cost, total emission, and total real power loss while satisfying physical and technical constraints on the network. When performing the OPF problem in conventional methods, the load demand and wind speed must be forecasted to prevent errors. However, actually there are always errors in these forecasted values. A characteristic feature of the proposed fuzzy based hybrid PSO method is that the forecast load demand and wind speed errors can be taken into account using fuzzy sets. Fuzzy set notations in the load demand, wind speed, total fuel cost, total emission, and total real power loss are developed to obtain the optimal setting under an uncertain environment. To demonstrate the effectiveness of the proposed method, the OPF problem is performed on the IEEE 30- and 118-Bus test systems.     

Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network

This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.     

求解非光滑燃料费用函数的基于进化规划的机组最优潮流

提出求解具有非光滑燃料费用函数的存在爬坡率限制的最优潮流方法。针对两次、阶梯形、联合循环机组的非光滑燃料费用函数,介绍一个基于进化规划的算法。在该算法中,为避免早熟,交叉操作随后代的数目非线性变化。介绍了所提出的进化算法应用于有线路约束的IEEE30节点系统和印度62节点系统的情况。以MVA为单位的线路潮流直接采用牛顿-拉夫逊法计算。算例证明所提出的进化算法简单,对求解具有非光滑燃料费用函数的存在很多约束的最优潮流问题有效。