Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC

This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets.     

计及风电相关性的区域间可用输电能力概率评估

大规模风电并网给电力系统区域间可用输电能力(available transfer capability, ATC)评估带来了新的挑战,为更加准确地评估高风电渗透率不确定性条件下的区域间ATC,文章提出了一种计及风电空间相关性的ATC概率评估方法。首先,利用条件概率原理对历史数据进行处理,并应用Copula函数对风电相关性进行建模;其次,区域间ATC的评估过程涉及到最大输电能力和现有输电协议的计算,因此提出一种ATC双层优化模型,在此基础上,利用Karush-Kuhn-Tucker(KKT)最优条件,双层模型即转化为均衡约束的数学规划(mathematica program with equilibrium constraint, MPEC)模型;再次,再将MPEC模型转化为混合整数二阶锥规划问题;最后,采用蒙特卡罗仿真对计及风电相关性的区域间ATC进行概率评估,并以IEEE 30节点系统为例,分析风电相关性对区域间ATC的影响,验证所提模型的正确性和有效性。     

计及统一潮流控制器的电力系统双层协调弹性调度

极端天气造成的故障会引发潮流转移,触发连锁故障,从而增加了大规模停电事故发生的概率。高比例电力电子设备接入电网的趋势增加了电网调度的灵活性。因此,提出计及统一潮流控制器的电力系统双层协调弹性调度策略。采用随机场景生成的方法模拟极端天气事件;通过潮流熵定量描述极端天气下潮流分布的不均衡性,以表征发生连锁故障的风险;将弹性调度代价最低和潮流熵最低分别作为上下层模型的目标函数,同时基于统一潮流控制器的调节潮流特性,构建双层弹性调度模型;基于KKT条件和对偶原则,将原双层调度模型转化为单层混合整数线性优化模型进行求解,并通过装有统一潮流控制器的IEEE 39和IEEE118节点系统进行算例仿真,验证了所提模型在降低大规模停电事故概率和提升系统弹性方面的有效性。     

计及可中断负荷的电力系统可用输电能力计算

为分析需求响应对系统可用输电能力的影响,提出一种开放电力市场环境下可用输电能力的计算方法。以可中断负荷这一典型的需求响应资源作为研究对象,构建考虑负荷服务实体和独立系统运营商不同利益需求的双层优化模型:上层模型以负荷服务实体的成本最小为目标,确定参与需求响应的用户;下层模型以发电总报价最小为目标确定节点边际电价,同时实现经济调度。将根据需求响应和发电机组报价分配的有功功率作为基态,在此基础上计算区域间可用输电能力。求解双层模型时,运用下层经济调度模型的KKT条件可将双层优化问题转化为均衡约束数学规划问题,根据强对偶理论消除约束中的非线性项,将原模型转化成混合整数线性规划模型。最后,在GAMS环境下调用CPLEX求解化简后的数学模型。通过对PJM-5节点、IEEE 30节点、IEEE118节点和IEEE 300节点系统的仿真计算,验证了所提方法的可行性和有效性,以及在可用输电能力计算中计及需求响应的必要性。     

含非正态分布概率潮流计算的改进型两点估计法

采用两点估计法进行考虑不确定性电力系统的概率潮流计算时容易产生较大的误差。提出一种可用于计算含服从非正态分布负荷的概率潮流问题的改进型两点估计法。该方法通过增加均一概率的估计点进行额外计算,不需要进行正态变换和估计高阶矩,其计算精度高于两点估计法。采用含服从非正态分布负荷的5节点系统和IEEE 14节点系统作为算例,与蒙特卡洛仿真的结果比较验证了提出的改进型两点估计法的准确性。     

考虑自适应传输备用的含风电电力系统双层随机调度方法

大规模风电接入增加了电网发生输电阻塞的概率.为克服确定性阻塞管理方法在应对系统随机扰动上的不足,基于考虑阻塞风险的机会约束规划条件,提出一种计及风电不确定性的传输备用自适应量化方法,构建了包含自适应传输备用的双层随机调度模型.该模型将线路传输备用纳入上层的机组组合模型中,针对下层的经济再调度问题,采用改进点估计法求得线路实时潮流的统计分布特性,并将结果返回上层模型以动态调整备用需求大小.同时,基于下层模型的Karush-Kuhn-Tucher最优条件,将双层优化结构合并为单层,并最终转化为便于求解的混合整数规划问题.最后,通过IEEE RTS-24节点测试算例验证了所提模型和方法能够有效缓解传输阻塞,提高风电消纳和备用可用性.     

区间不确定信息下电力系统安全性的快速评估算法

计及高压输电网络中的不确定因素,提出了区间负荷下快速评估电力系统安全性的新算法。该算法对传统分支定界算法进行了改进,证明了电力系统最小切负荷问题的负荷边界特性,将双层规划模型的求解转化为少量线性规划模型的求解。改进后的分支定界算法能够快速、准确地求解基于双层线性规划的区间至多切负荷模型,得到区间负荷下计及发电机的可调作用时,基于直流潮流模型的系统最小切负荷量的最大值。新算法的计算速度大大优于求解同类问题时所用的蒙特卡罗模拟法和分支定界法,精度较高。6节点和46节点系统算例的计算结果验证了算法的正确性和有效性。     

考虑限幅约束的多区域互联电网全分布式潮流算法

多区域互联电网中有大量限幅非光滑约束,增加了潮流模型的非凸性。针对传统基于启发式规则处理限幅的分布式潮流算法在计算过程中容易出现收敛性问题,提出了一种能鲁棒性处理非光滑约束的互联电网全分布式潮流计算方法。首先根据分层分区调度模式对电网进行分区,并将模型中非光滑约束进行光滑处理,然后基于具有二阶收敛速度的双层交替方向非精确牛顿法,将潮流问题转化为求解最优步长增量的问题。基于零空间法(Null-Space) 对状态变量的系数矩阵进行降维处理,采用共轭梯度(Conjugate Gradient, CG)算法更新每个分区的对偶乘子,乘子更新过程中利用二阶信息提高了算法的收敛性。多区域间进行分布式计算时无需协调层参与,仅需通信少量边界信息,因此通信负担轻。最后,以30节点和182节点系统为测试算例,验证了所提方法在设置恶劣初值和处理非光滑约束时具有较高的精确性和较好的收敛性。     

考虑负荷概率分布的随机最优潮流方法

针对考虑负荷概率分布的随机最优潮流问题，建立了相应的机会约束规划模型。基于经典最优潮流问题的内点法和随机潮流方法，设计了求解该模型的一种启发式方法。该方法以确定性负荷最优潮流计算结果为基础，通过求取受机会约束的变量的概率分布判断概率约束是否满足。若不满足，则根据变量分布和等效的机会约束，形成新的上下限约束，继续计算负荷为期望值时的最优潮流，直至所有概率约束满足。对5节点和IEEE 118节点系统的测试表明该算法的有效性。     

考虑风速相关性的概率潮流计算及影响分析

不同风电场之间风速的相关性会影响概率潮流计算的结果。通过对多维独立随机样本进行线性变换,得到具有任意相关性的多维随机样本,从而可计算考虑风速相关性的概率潮流;针对风电场异步发电机吸收无功的特性,提出了一种描述该特性的变系数二次多项式模型。在计及负荷随机扰动的同时,研究并分析了风速相关性的变化对节点电压概率密度和支路潮流概率分布的影响规律,以及考虑相关性后对风电场并网点无功补偿容量的配置。研究算例表明文中方法是有效可行的,考虑风速相关性可以更合理的分析评估风电场对系统静态电压和支路传输功率的影响,从而可为系统规划和运行方式的确定提供更准确完善的参考信息。     

Optimal Location of Thyristor-controlled Series Capacitor to Enhance Power Transfer Capability Using Firefly Algorithm

Abstract—The optimal power flow problem seeks to find an optimal profile of active and reactive power generations along with voltage magnitudes in such a manner as to minimize the total operating costs of a power system while satisfying network security constraints. This article presents a firefly algorithm to solve the optimal power flow problem incorporating a thyristor-controlled series capacitor. A thyristor-controlled series capacitor is considered to find the optimal location in transmission lines to enhance the power transfer capability of the transmission line. To assess the effectiveness of the proposed algorithm, it was tested on a 5-bus test system, an IEEE 14-bus system, and a modified IEEE 30-bus system, and it was compared with the genetic algorithm and differential evolution with and without a thyristor-controlled series capacitor. It has also been observed that the proposed algorithm can be applied to larger systems and does not suffer with computational difficulties. The results show that the firefly algorithm produces better results than others and has fast computing time for solving the optimal power flow problem with a thyristor-controlled series capacitor.     

负荷增长方式不确定条件下有功出力方式优化

优化有功出力方式是提升功率传输极限的有效方法之一。为在优化中考虑负荷增长方式的不确定性,提出了一种具有对立结构的双层优化模型。该模型的上层结构是以负荷裕度最大为目标函数的有功出力方式优化模型;下层结构是以负荷裕度最小为目标函数的最危险负荷增长方式求解模型。通过对上、下2层模型交替进行优化,并将所得的优化解作为参数在2个层间相互传递,快速地求出了最佳的有功出力方式,使系统在最危险负荷增长方式下的负荷裕度最大。最后通过IEEE30、118节点系统和一个实际系统的算例验证了所提方法的有效性。     

A novel modified GBMO algorithm based static transmission network expansion planning

Due to the growing demand of electricity, transmission sector has become important part of the power sector. The penetration level of renewable energy resources has increased presently, which gives more challenges to the transmission expansion planner. To overcome this problem better transmission expansion planning (TEP) needs to be done. Hence, it is necessary to incorporate the impact of high wind power penetration in TEP problem. In this paper wind farm are considered as an alternative source for supplying the load to the transmission networks. The complex wind energy cost model is incorporated with the traditional transmission network expansion planning (TNEP) problem. Factors accounting for wind power utilization cost, underestimation, and overestimation cost model of wind power are included. Static transmission network expansion planning (STNEP) problem is modeled using the DC power flow model. The main objective function is to minimize the total cost of the system, which consists of transmission line investment cost, fuel cost of generators and wind energy cost. To solve this non-linear, non-convex optimization problem with a novel optimization algorithm i.e. Modified Gases Brownian Motion Optimization (MGBMO) algorithm is applied. To validate the capability of the proposed method is tested with modified Garver’s 6-bus system, IEEE 24-bus system and IEEE 25-bus system.     

Optimal bidding strategies in oligopoly markets considering bilateral contracts and transmission constraints

In electricity industry with transmission constraints and limited number of producers, Generation Companies (GenCos) are facing an oligopoly market rather than a perfect competition one. Under oligopoly market environment, each GenCo may increase its own profit through a favorable bidding strategy. This paper investigates the problem of developing optimal bidding strategies of GenCos, considering bilateral contracts and transmission constraints. The problem is modeled with a bi-level optimization algorithm, where in the first level each GenCo maximizes its payoff and in the second level a system dispatch will be accomplished through an OPF problem in which transmission constraints are taken into account. It is assumed that each GenCo has information about initial bidding strategies of other competitors. Impacts of exercising market power due to transmission constraints as well as irrational biddings of the some generators are studied and the interactions of different bidding strategies on participants’ corresponding payoffs are presented. Furthermore, a risk management-based method to obtain GenCos’ optimal bilateral contracts is proposed and the impacts of these contracts on GenCos’ optimal biddings and obtained payoffs are investigated. At the end, IEEE 30-bus test system is used for the case study in order to demonstrate the simulation results and support the effectiveness of the proposed model.     

Advanced modeling of the multicontrol functional static synchronous series compensator (SSSC) in Newton power flow

The static synchronous series compensator (SSSC) is one of the recently developed flexible AC transmission system (FACTS) controllers. The SSSC coupled with a transformer is connected in series with a transmission line. This paper describes a multicontrol functional model of the SSSC for power flow analysis, which can be used for steady state control of one of the following parameters: (1) the active power flow on the transmission line; (2) the reactive power flow on the transmission line; (3) the voltage at the bus; and (4) the impedance (precisely reactance) of the transmission line. Furthermore, the model can also take into account the voltage and current constraints of the SSSC. The detailed implementation of such a multicontrol functional model in Newton power flow algorithm is presented. A special consideration of the initialization of the variables of the SSSC in power flow analysis is also proposed. Numerical examples on the IEEE 30-bus system, IEEE 118-bus system, and IEEE 300-bus system are used to illustrate the feasibility of the SSSC model and performance of the Newton power flow algorithm.     

考虑分布式电源支撑作用的输配电系统协同恢复方法

随着高密度分布式电源不断接入配电系统,配电系统向上支撑大电网恢复成为可能.首先,结合高密度分布式电源对电力系统分区并行恢复的促进作用,分析含分布式电源的大电网恢复分区需要满足的基本条件.然后,针对含高密度分布式电源的大电网待恢复子区,考虑相关运行约束等,构建输配电系统协同恢复的双层混合整数线性规划(MILP)模型.其中...     

含光伏随机出力的配电网两阶段无功优化

对于光伏电站及负荷出力的不确定性,无功越级传输带来的有功损耗及调压困难等问题,本文以有功网损最少、无功越级传输最小和无功补偿设备投资费用最少为目标建立两阶段无功优化多目标函数模型,利用基于逐次优化的改进遗传算法求解。求解过程中以电压稳定极限曲面法向量作为选取补偿备选节点以缩小范围和时间,采用基于拉丁超立方抽样的概率潮流计算节点电压裕度和潮流。改进的Baran&Wu33节点算例结果仿真与分析验证了本文算法及模型的有效性,对配电网无功补偿优化有一定指导意义。     

基于随机响应面法的主动配电网无功优化

考虑分布式电源(DG)的无功主动调控能力,计及状态变量的机会约束,建立主动配电网随机无功优化模型。通过非参数核密度估计对随机因素进行建模,进一步借助随机响应面法,研究适应于多种概率模型的概率潮流计算方法,用以判断状态变量是否满足机会约束,并利用Nataf变换处理随机变量的相关性。结合基于粒子群的无功优化方法,对所建立模型进行求解。最后,基于修改过的IEEE 33节点和美国PGE 69节点配电系统测试所提方法的正确性和有效性。算例表明所提概率潮流计算方法所得累积分布函数具有较高的精度,同时设计不同的场景,进一步表明所提模型和算法适应不同DG无功控制策略、可发现确定性优化方案的概率越界风险并调整解决。     

Planning of multi-type FACTS devices in restructured power systems with wind generation

Many electrical power systems are changing from a vertically integrated entity to a deregulated, open-market environment. This paper proposes an approach to optimally allocate multi-type flexible AC transmission system (FACTS) devices in restructured power systems with wind generation. The objective of the approach is to maximize the present value of long-term profit. Many factors like load variation, wind generation variation, generator capacity limit, line flow limit, voltage regulation, dispatchable load limits, generation rescheduling cost, load shedding cost, and multilateral power contracts are considered in problem formulation. The proposed method accurately evaluates the annual costs and benefits obtainable by FACTS devices in formulating the large-scale optimization problem under both normal condition and possible contingencies. The overall problem is solved using both Particle Swarm Optimization (PSO) for attaining optimal FACTS devices allocation as main problem and optimal power flow as sub optimization problem. The efficacy of the proposed approach is demonstrated for modified IEEE 14-bus test system and IEEE 118-bus test system.     

Optimal reactive power dispatch using ant colony optimization algorithm

This paper proposed a procedure to solve the optimal reactive power dispatch (ORPD) problem using ant colony optimization (ACO) algorithm. The objective of the ORPD problem is to minimize the transmission power losses under control and dependent variable constraints. Proposed sensitivity parameters of reactive power at generation and switchable sources are derived based on a modified model of fast decoupled power flow. The proposed ACO-based algorithm is applied to the IEEE standard 14-bus, 30-bus systems, and a real power system at West Delta Network as a part of the Unified Egyptian Network. The obtained simulation results are compared with those of conventional linear programming, genetic algorithm, and particle swarm optimization technique. Simulation results show the capability of the proposed ACO-based algorithm for solving the ORPD problem, especially with increasing the system size.