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Cost minimization is one of the main goals in electric market so economic dispatch and load allocating, named as optimal power flow (OPF), are more interesting concerns. In this paper a Modified Genetic Algorithm (MGA) is presented for the solution of the OPF. The control variables are unit active power outputs, generator-bus voltages and discrete transformer-tap settings. To overcome the operating...
In this paper, the power system stabilizer (PSS) and flexible ac transmission system devices (FACTS) interaction is investigated. The objective of this work is to study and design a controller capable of doing the task of damping in less economical control effort, and to globally link all controllers of national network in an optimal manner, towards smarter grids. This can be well done if a specific...
This paper presents an improved dynamic genetic algorithm (IDGA) for reactive power optimization and voltage control. The problem is formulated as a mixed integer, nonlinear optimization problems considering both continuous and discrete control variables. The objective of optimization is minimizing active power losses while maintaining the quality of voltages. During evolution process, the crucial...
Electric power steering system model was set up in this thesis. The mixed H2/H∞ state feedback controllers with robustness and better system performance are designed through making H∞ controllers have H2 optimization by GA. In this method, the coding is float, the selection operator is rank-based fitness assignment and elitist model, the crossover operator is real valued recombination, and the mutation...
This paper introduces a modified particle swarm optimization (MPSO) algorithm which gets benefit from all remarkable advantages of conventional PSO (CPSO) in addition to lower possibility of catching in premature convergence and higher accuracy. In this paper, influence of CPSO parameters changes on the output accuracy is firstly represented and studied; then, a modified PSO called MPSO is studied...
Genetic Algorithm (GA) is emerging as a popular tool in the optimization problems of power systems. In reliability indices calculation and adequacy assessment, methods have been previously developed to use GA as the sampling tool. One of the techniques developed is to use GA as the state space pruning tool in order to truncate the state space before calculating the reliability indices. This means...
The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques to solve different engineering problems. Besides, Short Term Electrical Load Forecasting (STLF) is one of the important concerns of power systems and accurate load forecasting is vital for managing supply and demand of electricity. This study estimates short term electricity loads...
This paper presents an Elman neural network based on Genetic algorithms for the identification of dynamic equivalents of power system. The Elman neural network is one of the dynamic recurrent neural networks. In this paper, a modified Elman network is introduced first. Then we propose its training algorithm using Genetic algorithms. Lastly, the proposed method is demonstrated and compared with the...
The Bacterial Foraging (BF) optimization algorithm imitates the foraging behavior of Escherichia coli (E. coli) bacteria that exist in human intestine, whose foraging habit is modeled as a distributed optimization process. This paper applies the BF algorithm to design optimal controllers of a single-machine-infinite-bus (SMIB) system equipped with an interline power flow controller (IPFC). The system...
In this paper, the power system stabilizer (PSS) and Thyristor controlled phase shifter (TCPS) interaction is investigated. The objective of this work is to study and design a controller capable of doing the task of damping in less economical control effort, and to globally link all controllers of national network in an optimal manner, toward smarter grids. This can be well done if a specific coordination...
Design of an optimal controller requires optimization of multiple performance measures that are often noncommensurable and competing with each other. Design of such a controller is indeed a multi-objective optimization problem. Being a population based approach; genetic algorithm (GA) is well suited to solve multi-objective optimization problems. This paper investigates the application of GA-based...
In this paper an improved genetic algorithm (IGA) for unit commitment problem with lowest cost is presented. The unit commitment problem (UCP) has an important role in power systems, due to improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimization problems in power systems, because this problem has...
Economic dispatch (ED) is a power system optimization problem and its objective is to reduce the total generation cost of units while satisfying constraints. The presence of nonlinearities in practical generator operation makes solving the ED problem more challenging. These generator nonlinearities are modeled as constraints to be met in the form of ramp-rate limits and prohibited operating zones...
The paper proposes a comparison between nonlinear optimization and genetic algorithms for optimal location and sizing of distributed generation in a distribution network. The objective function consists of both power losses and investment costs and the methods are tested on the IEEE 69-bus system. The study covers a comparison between the proposed approaches and shows the importance of installing...
This paper proposes a genetic algorithm (GA) tuned differential evolution (DE) method for solving economic dispatch (ED) problem with non-smooth cost curves. The tuning of the weights in differential evolution is the key issue in designing an efficient differential evolution algorithm. Their values are dependent on nature and characteristic of objective function. As there is no explicit rule or guideline...
Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper...
This paper improves integer coded genetic algorithm (ICGA) with some operators, to schedule the commitment states of units. ICGA technique reduces the size of chromosomes and computation time significantly. Chromosomes contain sequence of alternative sign integers which represent operation/reservation hours of the generating units. Therefore minimum up/down time can be checked directly in chromosome...
Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents...
Power suppliers are faced with the trade-off between benefit and risk when they purchase energy from several sub-markets under electricity market environments. With conditional value-at-risk (CVaR) as a measuring index for market risk, a purchasing model for power suppliers among the wholesale, forward, options and interruptible load (IL) markets, is proposed, in which the objective function is to...
Voltage security is a crucial issue in power systems especially under heavily loaded condition. In the new scheme of restructuring, voltage stability problem becomes even more serious. To solve the problem, we integrate reactive power compensation concept by static synchronous compensator (STATCOM) with equivalent-current injection (ECI). We derive a new STATCOM with ECI model. This paper shows the...
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