A stochastic framework for clearing of reactive power market

This paper presents a new stochastic framework for clearing of day-ahead reactive power market. The uncertainty of generating units in the form of system contingencies are considered in the reactive power market-clearing procedure by the stochastic model in two steps. The Monte-Carlo Simulation (MCS) is first used to generate random scenarios. Then, in the second step, the stochastic market-clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. In each of these deterministic optimization problems, the objective function is total payment function (TPF) of generators which refers to the payment paid to the generators for their reactive power compensation. The effectiveness of the proposed model is examined based on the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS).     

Stochastic reactive power market with volatility of wind power considering voltage security

While wind power generation is growing rapidly around the globe; its stochastic nature affects the system operation in many different aspects. In this paper, the impact of wind power volatility on the reactive power market is taken into account. The paper presents a novel stochastic method for optimal reactive power market clearing considering voltage security and volatile nature of the wind. The proposed optimization algorithm uses a multiobjective nonlinear programming technique to minimize market payment and simultaneously maximize voltage security margin. Considering a set of probable wind speeds, in the first stage, the proposed algorithm seeks to minimize expected system payment which is summation of reactive power payment and transmission loss cost. The object of the second stage is maximization of expected voltage security margin to increase the system loadability and security. Finally, in the last stage, a multiobjective function is presented to schedule the stochastic reactive power market using results of two previous stages. The proposed algorithm is applied to IEEE 14-bus test system. As a benchmark, Monte Carlo Simulation method is utilized to simulate the actual market of given period of time to evaluate results of the proposed algorithm, and satisfactory results are achieved.     

地区电网无功电压最优控制

本文提出了地区电网在满足母线电压、线路及变压器不超载的安全约束下,以有载调压变分接头和母线无功补偿量为控制变量,用线性规划获得计入无功电压静态特性的无功电压最优控制策略的方法.本文根据实时采样数据辨识负荷母线的无功电压静态特性,并有网损最小、无功补偿量最小、控制效益最大、三种不同的目标函数可供不同需要选用.在IEEE试验和实际系统的试验表明:能快速获得不同目标函数的最优控制策略.     

Market clearing of joint energy and reserves auctions using augmented payment minimization

This paper presents the market clearing of joint energy and reserves auctions and its mathematical formulation, focusing on a possible implementation of the Payment Cost Minimization (PCM). It also discusses another key point in debate: whether market clearing algorithm should minimize offer costs or payment costs? An aggregated simultaneous market clearing approach is proposed for provision of ancillary services as well as energy, which is in the form of Mixed Integer Nonlinear Programming (MINLP) formulation. In the MINLP formulation of the market clearing process, the objective function (Payment cost or offer cost) are optimized while meeting AC power flow constraints, system reserve requirements and lost opportunity cost (LOC) considerations. The model is applied to the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS), and simulation studies are carried out to examine the effectiveness of each objective function.     

Impact of FACTS devices on exercising market power in deregulated electricity market

In power system studies, congestion in transmission lines and utilization of flexible alternating current transmission system (FACTS) devices are closely associated. These devices are very important due to their role in power delivery system enhancement. It is to be noted that the generation companies can exercise their market power which depends on the line flows, line constraints, generators’ location and its share to the individual loads. This issue cannot be overlooked as it creates monopoliness which is against the deregulated market policy. The objective of this paper is to study the impact of market power when FACTS devices like thyristor controlled switching capacitor (TCSC) and thyristor controlled phase angle regulator (TCPAR) are used under steady state operation. The market power is determined using nodal must-run share (NMRS) index for the standard IEEE 14-bus system with and without the above FACTS devices and the results obtained are compared. All the above simulations are conducted in a MATLAB 7.9-R2009b environment.     

Joint market clearing in a stochastic framework considering power system security

This paper presents a new stochastic framework for provision of reserve requirements (spinning and non-spinning reserves) as well as energy in day-ahead simultaneous auctions by pool-based aggregated market scheme. The uncertainty of generating units in the form of system contingencies are considered in the market clearing procedure by the stochastic model. The solution methodology consists of two stages, which firstly, employs Monte–Carlo Simulation (MCS) for random scenario generation. Then, the stochastic market clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. The objective function of each of these deterministic optimization problems consists of offered cost function (including both energy and reserves offer costs), Lost Opportunity Cost (LOC) and Expected Interruption Cost (EIC). Each optimization problem is solved considering AC power flow and security constraints of the power system. The model is applied to the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS) and simulation studies are carried out to examine the effectiveness of the proposed method.     

Tuned reactive power dispatch through modified differential evolution technique

This paper explores the capability of modified differential evolution (MDE) technique for solving the reactive power dispatch (RPD) problem. The proposed method is based on the basic differential evolution (DE) technique with a few modifications made into it. DE is one of the strongest optimization techniques though it suffers from the problem of slow convergence while global minima appear. The proposed modifications are tried to resolve the problem. The RPD problem mainly defines loss minimization with stable voltage profile. To solve the RPD problem, the generator bus voltage, transformer tap setting and shunt capacitor placements are controlled by the MDE approach. In this paper, IEEE 14-bus and IEEE 30-bus systems are chosen for MDE implementation. The applied modification show much improved result in comparison to normal DE technique. Comparative study with other soft-computing technique including DE validates the effectiveness of the proposed method.     

Optimal placement and sizing of PV systems and electric parking lots considering reactive power capability and load variation

Power systems should operate in reliable, stable, and efficient conditions. Addition of new generation units or loads to the power systems may change their performance. Therefore, appropriate decisions should be made to manage these elements to improve the power system performance. In this study, optimal placement and sizing of photovoltaic systems and electric parking lots (EPLs) are studied considering the reactive power capability of the inverters and load variation in a 24-h period. For the EPL, a proper charge/discharge scheme (CDS) is initially proposed to flatten the daily load profile; then the EPL with the associated CDS is considered to find its optimal location. Voltage profile, energy losses, bus, and line voltage stability are considered as the objectives of the problem. Genetic algorithm and backward–forward power flow method are utilised to solve the problem considering the IEEE 33-bus system. The results show that all objectives are improved utilising the proposed method.     

Genetic single objective optimisation for sizing and allocation of renewable DG systems

The optimal design of renewable-based distributed generations (DGs) is a challenging issue in order to maximise their benefits and to overcome power quality problems. Therefore, this paper proposes a methodology for optimal allocation and sizing of renewable DG units to minimise total power losses over radial distribution systems. The planning problem is formulated as a single objective nonlinear mixed integer-constrained optimisation problem and is solved by using the augmented Lagrangian genetic algorithm (ALGA) by combining the objective function and the nonlinear constraints. In that case, the ALGA solves a sequence of sub-problems where the objective function penalises the constraints violation in order to obtain the best solution. The proposed technique is applied to IEEE radial test systems including 33-bus, 69-bus and 119-bus and is implemented with different scenarios including all possible combinations and various types of renewable DG units to prove the effectiveness of the proposed methodology.     

Market-clearing for pricing system security based on voltage stability criteria

This paper presents a novel technique for representing system security in the operation of decentralized electricity markets, with special emphasis on voltage stability. The market-clearing algorithm is modeled as voltage stability constrained-optimal power flow (VSC-OPF) problem for providing market solutions by means of a function of complying with the required voltage stability criteria. Benders’ decomposition is applied for solving the VSC-OPF incorporating post-contingency control actions, which is motivated by the improvement of computational efficiency using parallel processing. The proposed VSC-OPF framework also takes into consideration the bilateral contract information, which is integrated into the market-clearing process and, at the same time, the optimal pricing expressions through computing local marginal prices (LMPs) with respect to ensuring voltage stability are derived. VSC-OPF is tested on the IEEE 14-bus benchmark system and the results obtained, when compared to those obtained by means of a conventional OPF, show that the proposed technique is able to improve system security while yielding better market solutions and total transaction levels.     

Simplified reactive power management strategy for complex power grids under stochastic operation and incomplete information

In the current released energy market, the large-scale complex transmission networks and the distribution ones with dispersed energy sources and “intelligent” components operate under uncertainties, stochastic and prior incomplete information. A safe and reliable operation of such complex power grids is a major issue for system operators. Under these circumstances an online reactive power management strategy with minimum risk concerning all uncertain and stochastic parameters is proposed. Therefore, new concepts such as reactive power-weighted node-to-node linking and reactive power control capability are introduced. A distributed and interconnected stochastic learning automata system is implemented to manage, in a unified and unique way, the reactive power in complex power grids with stochastic reactive power demand and detect the vulnerable part. The proposed simplified strategy can also consider more stochastic aspects such as variable grid’s topology. Results of the proposed strategy obtained on the networks of IEEE 30-bus and IEEE 118-bus systems demonstrate the effectiveness of the proposed strategy.     

Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: A stochastic approach

Optimal reactive power dispatch (ORPD) problem is an important problem in the operation of power systems. It is a nonlinear and mixed integer programming problem, which determines optimal values for control parameters of reactive power producers to optimize specific objective functions while satisfying several technical constraints. In this paper, stochastic multi-objective ORPD (SMO-ORPD) problem is studied in a wind integrated power system considering the loads and wind power generation uncertainties. The proposed multi objective optimization problem is solved using ε-constraint method, and fuzzy satisfying approach is employed to select the best compromise solution. Two different objective functions are considered as follow: 1) minimization of the active power losses and 2) minimization of the voltage stability index (named L-index). In this paper VAR compensation devices are modeled as discrete variables. Moreover, to evaluate the performance of the proposed method for solution of multi-objective problem, the obtained results for deterministic case (DMO-ORPD), are compared with the available methods in literature. The proposed method is examined on the IEEE-57 bus system. The proposed models are implemented in GAMS environment. The numerical results substantiate the capability of the proposed SMO-ORPD problem to deal with uncertainties and to determine the best settings of control variables.     

基于一致性协议的配电网分布式优化控制策略研究

分布式控制以其鲁棒性强、可扩展性强等突出优势,已逐渐取代集中式控制,成为高渗透率配电网优化控制的一种有效途径。文章研究了一种基于无功补偿设备和分布式电源分组协作机制的配电网分布式优化控制策略,将多个无功补偿设备或分布式电源聚合在一起,以基于领导者的一致性协议控制节点电压和交换功率。文章给出了分布式协同控制框架,各分组控制目标及一致性变量的选取,并证明了各控制组分布式控制算法的收敛性。通过IEEE14节点系统的仿真算例验证了所提出方法的正确性和有效性。     

基于图论的电力系统PMU布点优化算法

基于最小支配集理论和电力系统线性量测模型．提出了可观测节点集合、WAMS可观测矩阵两个概念以及一种新的节点可观测性计算规则。以保证系统的完全可观测性和以系统图的最小支配集为搜索范围构成约束条件,以电力系统状态完全可观测和相量测量装置（PMU）配置数目最小为目标,形成了PMU配置优化问题。并应用禁忌搜索（TS）方法求解该问题,保证了全局寻优。最后采用IEEE14、30、57、118节点系统和新英格兰39节点系统对该方法进行了验证,仿真结果表明该方法的有效性和可行性。     

Impact of heat,power and hydrogen generation on optimal placement and operation of fuel cell power plants

In this paper, a stochastic model is proposed for planning the location and operation of Fuel Cell Power Plants (FCPPs) as Combined Heat, power, and Hydrogen (CHPH) units. Total cost, emissions of FCPPs and substation, and voltage deviation are the objective functions to be minimized. Location and operation of FCPPs as CHPH are considered in this paper while their investment cost is not taken into account. In the proposed model, indeterminacy refers to electrical and thermal loads forecasting, pressure of oxygen and hydrogen, and the nominal temperature of FCPPs. In this method, scenarios are produced using roulette wheel mechanism and probability distribution function of input random variables. Using this method, the probabilistic problem is considered to be distributed as some scenarios and consequently probabilistic problem is considered as combination of some deterministic problems. Considering the nature of objective functions, the problem of locating and operating FCPPs as CHPH is considered as a mixed integer nonlinear problem. A Self Adaptive Charged System Search (SACSS) algorithm is employed for determining the best Pareto optimal set. Furthermore, a set of non-dominated solutions is saved in repository during simulation procedure. A 69-bus distributed system is used for verifying the beneficiary proposed method.     

A modified shuffle frog leaping algorithm for multi-objective optimal power flow

This paper presents an efficient and reliable evolutionary-based approach to solve the Optimal Power Flow (OPF) problem by considering the emission issue. The OPF problem has been widely used in power system operation and planning for determining electricity prices. Therefore, the conventional optimal power flow cannot meet the environmental protection requirements, because it only considers generation cost minimization. The multi-objective optimal power flow considers economical and emission issues. By adding the emission objective in the optimal power flow problem, this problem become more complicated than before and it needs to be solved with an accurate algorithm. This paper proposes an algorithm based on the Shuffle Frog Leaping Algorithm (SLFA) to solve the multi-objective OPF problem. Furthermore, this paper presents a modified SLFA called MSLFA algorithm which profits from a mutation in order to reduce the processing time and improve the quality of solutions, particularly to avoid being trapped in local optima. The IEEE 30-bus test system is presented to illustrate the application of the proposed problem.     

Reactive power market management considering voltage control area reserve and system security

This paper presents a new algorithm to optimize reactive power procurement through commercial transactions considering system voltage security. The proposed algorithm minimizes reactive power provision and transmission loss costs in addition to maximizing system voltage security margin through a multiobjective function. In order to maintain the voltage profile of power system during sever contingencies or due to load uncertainty, all voltage control areas (VCA) of the system are detected and then optimal reactive power reserve is provided for each VCA during the market settlement. A four-stage multiobjective mathematical programming method is proposed to settle the reactive power market. The proposed algorithm has been applied on IEEE-RTS test system. The simulation results show the effectiveness of the proposed algorithm for reactive power market management.     

Green hydrogen: A new flexibility source for security constrained scheduling of power systems with renewable energies

Green hydrogen, i.e. the hydrogen generated from renewable energy sources (RES) will significantly contribute to a successful energy transition. Besides, to facilitate the integration and storage of RES, this promising energy carrier is well capable to efficiently link various energy sectors. By introduction of green hydrogen as a new flexibility source to power systems, it is necessary to investigate its possible impacts on the generation scheduling and power system security. In this paper, a security-constrained multi-period optimal power flow (SC-MPOPF) model is developed aiming to determine the optimal hourly dispatch of generators as well as power to hydrogen (P2H) units in the presence of large-scale renewable energy sources (RES). The proposed model characterizes the P2H demand flexibility in the proposed SC-MPOPF model, taking into account the electrolyzer behavior, reactive power support of P2H demands and hydrogen storage capability. The developed SC-MPOPF model is applied to IEEE 39-bus system and the obtained numerical results demonstrate the role of P2H flexibility on cost as well as RES's power curtailment reduction.     

Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization

This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.     

IEEE-PES Transmission and Distribution Conference and Exposition Call for Papers

Static network-related system voltage stability margin (VSM) depends on the availability of reactive power to support the transport of real power from sources to sinks. Based on this premise, the total VAr loss is minimized in the unified OPF framework considering real and reactive power controllers, and its effect on VSM is studied. Studies are conducted on a three-bus system, the IEEE 30-bus system, and a 191-bus Indian electric power system, and their results are reported.