基于改进粒子群优化算法的输电系统多阶段协调规划

提出了一种输电系统多阶段协调规划模型,模型中计入了以N-1静态安全条件表示的可靠性约束,并对采用粒子群优化算法PSO(Partic le Swarm Optim ization)来求解该模型进行了研究,引入新的变异策略对基本PSO算法进行了改进,改进后的算法可以处理多维的离散变量,有可能使粒子摆脱局部最优,提高搜索效率。仿真算例表明该方法用于输电系统的多阶段协调规划是可行的。     

基于改进粒子群优化算法的输电系统多阶段协调规划

提出了一种输电系统多阶段协调规划模型,模型中计入了以N-1静态安全条件表示的可靠性约束,并对采用粒子群优化算法PSO(Particle Swarm Optimization)来求解该模型进行了研究,引入新的变异策略对基本PSO算法进行了改进,改进后的算法可以处理多维的离散变量,有可能使粒子摆脱局部最优,提高搜索效率.仿真算例表明该方法用于输电系统的多阶段协调规划是可行的.     

Optimal transmission expansion planning for electric power systems

This paper presents a new method for transmission expansion planning in which the utility loss revenue and the customer outage cost resulting from service outages are incorporated. A new algorithm based on the total probability formula is developed for evaluating the expected value of demand not served (EDNS) and the expected value of energy not served (EENS). These reliability indices are employed to determine the utility loss revenue curve. The system expansion cost curve is obtained by using a maximum reliability design algorithm. The optimal reliability level of a transmission expansion plan is determined by minimizing the sum of the investment cost, the utility loss revenue, and the customer outage cost. An example is presented for illustration of the proposed method.     

Market-driven dynamic transmission expansion planning

We present a novel transmission expansion planning model that explicitly considers a multi-year planning horizon. The proposed formulation is a mixed-integer linear problem that can be solved using commercially available software. The algorithm determines the best overall transmission expansion plan, reflecting both investment and operational costs. To analyze the results obtained from the model, we use a set of efficiency metrics to appraise the effect of the expansion among generators and demands, as well as congestion metrics to measure changes in nodal prices and line congestions. This paper also provides a case study that considers the expansion plan for a transmission system based on the one of mainland Spain.     

Multistage distribution network expansion planning under smart grids environment

This paper presents a novel model for multistage smart distribution network expansion planning (MSDNEP) in the presence of vehicle to grid (V2G) and fault passage indicator (FPI) in a multi-objective optimization framework. Distribution networks should be expanded in order to serve load growth in the best manner possible. The two objectives considered are: minimization of total cost during the planning horizon and maximization of reliability index. The proposed model determines the sitting and sizing of parking lot as well as conventional alternatives for expansion, such as, optimal size, location and time in which the new lines must be added, replaced or removed. Moreover, the impacts of using FPIs in a distribution network on reliability and the investment cost are in the scope of this study. Due to its good handling of mixed integer nonlinear problem, a non-dominated sorting genetic algorithm (NSGA-II) is utilized for optimization such a complex problem. The effectiveness of the proposed model is demonstrated by applying to a distribution test system and results show a significant improvement in the area of distribution network planning.     

A dynamic model for coordination of generation and transmission expansion planning in power systems

This paper presents a new dynamic approach on the expansion planning problem in power systems. First, the coordination between generation system expansion and transmission system expansion has been formulated as a mixed integer nonlinear programming (MINLP) problem. Then, it has been shown that this MINLP model cannot be efficiently solved by the traditional MINLP solvers. Since the nonlinear term comes from the multiplication of a binary variable by a continuous one, a Benders decomposition approach has been employed to convert the MINLP formulation into a mixed integer linear programming (MILP) master problem, and a linear programming (LP) sub-problem. Besides, different times of construction have been considered for different transmission and generation facilities. In addition, a clustering based algorithm has been proposed to evaluate the reliability of the system at hierarchical level II (HLII). Since this dynamic planning method is an upgraded version of a recent developed static model, the result from both methods have been also compared. A simple 6-bus test system and IEEE 30-bus system have been selected to confirm the effectiveness of the introduced method.     

Dynamic model for long-term expansion planning studies of power transmission systems: the Ortie model

With regard to its complexity, the long-term expansion planning problem of a power transmission system cannot be tackled without making some broad assumptions. In the present study, it is assumed that the investment variables are continuous variables and that the flow on the transmission system complies with Kirchhoff's current law only. Moreover, only the forced outage rates on thermal generation units are taken into account, whereas all other uncertainties are ignored. The problem to be solved may be defined in the following way: if the increase in demand and the structure and site of the generators are known, the maximum transfer limits of the network at each point of time of the period studied can be determined so as to minimize the investment, operation and reliability costs. Using certain assumptions, the problem is solved by linear programming techniques. The special structure of the constraint matrix makes it possible to apply two methods for solving large-scale problems: a column generation technique with maximal flow problems as subproblems, and a partitioning technique of the basis matrix.     

Static transmission capacity expansion planning under uncertainty

This paper presents a new formulation of the static optimization problem in long-range transmission capacity expansion planning. A quantitative reliability technique is used in conjunction with a stochastic load flow formulation in order to accommodate uncertainty in system component availability and demand projections. The problem is solved using chance-constrained programming. Application of the formulation is demonstrated using the IEEE five-bus test system.     

A simulated rebounding algorithm applied to the multi-stage security-constrained transmission expansion planning in power systems

This research discusses the multi-stage security-constrained transmission network expansion planning. In modern power systems, the problem is formulated as a large-scale, mixed-integer, non-linear programming problem, which for a real power systems is very difficult to solve. Although remarkable advances have been made in optimization techniques, finding an optimal solution to a problem of this nature can still be extremely challenging. In this paper, a new constructive heuristic approach, based on a local controlled random search (simulated rebounding algorithm) is proposed to choose the decision variables. The model can produce better solutions than other references techniques such as particle swarm optimization, evolutionary particle swarm optimization, genetic algorithms, and simulated annealing algorithm, among other evolutionary methods. The methodology is applied to assess the capabilities of the proposed approach in the Ecuadorian and Chilean Power Systems as an example of application. Simulation results show that the proposed approach is accurate and very efficient, and it has the potential to be applied to real power system planning problems. The algorithm has been presented and applied to the multi-stage security-constrained transmission expansion planning.     

Multi-year expansion planning for distribution systems

A multi-term distribution system expansion planning method is proposed. Many mathematical programming approaches have been proposed in this area. However, because of the complexity of the problem or the limitations of a computational time and memory size, these methods can only be applied to a small-scale system. To solve large-scale problems, the authors propose a new decomposition algorithm based on the branch exchange method. A n-years planning problem is decomposed into n one-year planning problems, and one-year results are coordinated through what can be called the forward/backward path. The validity and effectiveness of the algorithm are ascertained by applying it to real-scale numerical examples     

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RGA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models.     

Transmission surplus capacity based power transmission expansion planning

A power transmission expansion planning model with consideration of transmission surplus capacity and network load factor is presented. With traditional planning model, some transmission lines will operate on high load factors due to ignorance of the load levels of transmission lines. This may lead to network congestion or degrade the dispatch flexibility of future network. Traditional planning model has put more emphasis on investment cost rather than other aspects such as operation environment, transmission benefit, etc. The transmission expansion planning model in the paper aims to maximize network transmission surplus capacity and optimize network load factor distribution with least investment. Chaos Optimal Algorithm (COA) is introduced to solve this nonlinear integer planning optimization problem for its advantage of stochastic and ergodic searching characteristics. The effectiveness of proposed model and methodology is tested with two typical systems.     

考虑传输线重构的电气综合能源系统分布鲁棒扩展规划模型

针对综合能源系统扩展规划模型多采用随机优化处理系统负荷需求增长不确定性问题,且场景信息缺失,易造成随机优化结果经济性与可参考性低的情况,提出一种以系统综合成本最小为目标函数、考虑传输线重构的两阶段电气综合能源系统分布鲁棒扩展规划模型.第一阶段为考虑综合能源负荷预测和传输线重构的扩展规划模型;第二阶段为计及机组调整出力与...     

多回直流输电系统间协调控制的的研究

结合南方电网的实际情况,综述了直流输电系统调制控制对改善交流系统动态和暂态稳定性的作用,对多回直流输电系统间功率调制功能协调控制的可行性和必要性进行了分析,提出了在南方电网内对多回直流输电系统调制功能进行协调控制的构思,针对多回直流调制功能在不同控制策略下的计算分析表明,多直流输电系统的协调控制减少了送端系统切机和受端电网切负荷,对改善南方电网交流稳定性方面有重要作用,根据研究结果提出了协调控制实现的初步方案。     

Distribution systems expansion planning by multi-stage branchexchange

The authors present a multistage branch exchange algorithm for solving expansion planning problems in distribution systems. Since it is formulated as a combinatorial optimization problem, it is difficult to solve such a large-scale problem accurately. Therefore, in order to find a solution quickly, the authors have developed a method based on the branch exchange technique which is able to find an approximate solution. To obtain a more accurate solution, the multistage branch exchange algorithm is introduced. The validity and effectiveness of the proposed algorithm are demonstrated by applying it to a 59-node, 69-branch numerical example system     

现代启发式算法及其在输电网络扩展规划中的应用

对遗传算法、模拟退火法、Tabu搜索法,蚂蚁算法和粒子群算法等具有代表性的现代启发式算法的发展、特点及其比较和在输电网络扩展规划中的应用进行了总结和综述,提出了对现代启发式算法改进的三种思路,以及一些尚待深入研究的工作。     

基于伪动态的混沌人工鱼群算法在多阶段输电网络规划中的应用

与传统输电网络规划不同,多阶段输电网络规划需要考虑时段因素,在何阶段搭建何种路线使全局规划方案最优。多阶段规划的难点是阶段之间的过渡,后面阶段的决策要根据前面阶段的决策来定,对于大规模输电网规划经典的动态规划方法无法解决。利用伪动态规划的思想处理多阶段问题,这样减少了算法的迭代次数和运算时间。将混沌优化算法和人工鱼群算法相结合,摆脱了混沌搜索的盲目性和人工鱼搜索的局限性,使该混合算法效率高、收敛速度快。对巴西南部46节点系统的计算结果表明,该混合算法具有可行性和高效性。     

Interactive computer program for planning the expansion of meshed transmission networks

A scheme is described for the interactive development of expansion strategies for transmission networks in which stability and voltage considerations are not of prime importance. According to the planning methodology adopted, the transmission/generation system is to be reinforced when it can no longer feed the peak demand without equipment overload in a single contigency. Outages of generators are considered, as well as the outages of transmission lines and transformers. Generation can be redispatched in order to eliminate overloads. If this is not possible, the model minimizes the load curtailment and identifies the weak parts of the system. It also ranks the possible investments according to their effectiveness in reducing the load curtailment. The planning engineer can build, interactively, several expansion policies by successive investment decisions. The model computes the discounted costs of the various policies developed. The files containing the expansion policies created are also automatically managed by the interactive package.The scheme has been implemented in a package called Tranex which consists of two separate interactive computer programs. An example illustrating the application of the method via this package to the Yugoslav network is given, along with computer performance details and an overview of the program structure.     

面向主辅能量市场出清的输电网双层扩展规划

电力市场开放下源荷频繁互动给高比例可再生能源并网的电力系统规划带来一系列挑战。提出了一种面向电力主辅市场出清的价格驱动下的输电系统双层规划模型。上层模型主要考虑系统运营商的投资成本及系统运行效用成本。下层模型则主辅电力市场出清模型,在考虑系统运行宽裕度的前提下以边际节点电价与备用价格引导上层输电网扩展规划。通过将下层市场出清模型基于Karush-Kuhn-Tucker (KKT)条件作为约束代入上层优化模型,构成混合整数非线性规划问题,进一步用近似线性化以及互补松弛等方式将非线性优化问题线性化。最后,以Garver-6节点系统及中国西南某500 kV输电网络为例进行验证。仿真结果表明所提输电网扩展规划方案有利于激励用户参与新能源市场化消纳,降低尖峰负荷场景下线路阻塞,保障电力市场交易的公平性。     

A new mixed-integer methodology for optimal transmission expansion planning

This paper presents a new model and a solution methodology for optimal planning of high-voltage transmission network investments. The objective of this problem is to minimize capital costs needed for new network elements while meeting imposed operating constraints, and it is formulated via a linear mixed-integer model. Then, a new branch-and-bound methodology is proposed as the problem solution. The fundamental idea of this methodology is to reduce the number of discrete variables contained in the original set of unknowns. This reduction is achieved by using the decomposition principle and by developing a new separation of the region of feasible solutions. The proposed methodology was verified on several test examples, as well as on the real transmission network of the eastern part of former Yugoslavia.