Serhat Duman

Application of gravitational search algorithm for optimal reactive power dispatch problem

In this paper, Gravitational Search Algorithm (GSA) is applied to solve the optimal reactive power dispatch (ORPD) problem. The ORPD problem is formulated as a nonlinear constrained single-objective optimization problem where the real power loss and the bus voltage deviations are to be minimized separately. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system consisting 6 generator and compared other algorithms reported those before in literature. Results show that GSA is more efficient than others for solution of single-objective ORPD problem.

Symbiotic organisms search algorithm for optimal power flow problem based on valve-point effect and prohibited zones

Abstract In this study, symbiotic organisms search (SOS) stochastic method is proposed to solve the optimal power flow (OPF) problem with valve-point effect and prohibited zones, which is one of the most important problems of the modern power system. The SOS approach is defined as the symbiotic relationships observed between two organisms in the ecosystem, which do not need the control parameters unlike other meta-heuristic algorithms in the literature. The effectiveness of the proposed SOS method is tested on modified IEEE 30-bus test system. The OPF problem is considered with four different test cases, such as (1) without valve-point effect and prohibited zones, (2) with valve-point effect, (3) with prohibited zones and (4) with valve-point effect and prohibited zones. The obtained results from the SOS algorithm are compared with the other optimization techniques in the literature. The obtained comparison results indicate that proposed approach is effective to reach optimal solution for the OPF problem.

Symbiotic organisms search optimization algorithm for economic/ emission dispatch problem in power systems

This paper presents symbiotic organisms search (SOS) algorithm to solve economic emission load dispatch (EELD) problem for thermal generators in power systems. The basic objective of the EELD is to minimize both minimum operating costs and emission levels, while satisfying the load demand and all equality–inequality constraints. In other research direction, this multi-objective problem is converted into single-objective function by using price penalty factor approach in order to solve it with SOS. The proposed algorithm has been implemented on various test cases, with different constraints and various cost curve nature. In order to see the effectiveness of the proposed algorithm, its results are compared to those reported in the recent literature. The results of the algorithms indicate that SOS gives good results in both systems and very competitive with the state of the art for the solution of the EELD problems.

Optimal power flow incorporating FACTS devices using Gravitational Search Algorithm

This paper aims to solve the optimal power problem (OPF) incorporating flexible AC transmission systems (FACTS) devices using Gravitational Search Algorithm (GSA) that minimizes the fuel cost function in the problem. In the optimization problem, Thyristor controlled series compensation (TCSC) and thyristor controlled phase shifter (TCPS) FACTS devices are considered to find their optimum location in transmission lines. In order to evaluate the effectiveness of proposed algorithm, it has been tested on modified IEEE 30 bus system and compared with particle swarm optimization (PSO) and hybrid tabu search and simulated annealing (TS/SA) approach which are used in solving the same problem and reported before in the literature. Results show that GSA produces better results than others and has fast computing time for solving OPF problem with FACTS.

Symbiotic organisms search algorithm for dynamic economic dispatch with valve-point effects

Abstract In this study, symbiotic organisms search (SOS) algorithm is proposed to solve the dynamic economic dispatch with valve-point effects problem, which is one of the most important problems of the modern power system. Some practical constraints like valve-point effects, ramp rate limits and prohibited operating zones have been considered as solutions. Proposed algorithm was tested on five different test cases in 5 units, 10 units and 13 units systems. The obtained results have been compared with other well-known metaheuristic methods reported before. Results show that proposed algorithm has a good convergence and produces better results than other methods.

Load frequency control of a single area power system using Gravitational Search Algorithm

In this paper, a novel heuristic search method called Gravitational Search Algorithm (GSA) is proposed for determination of the optimal proportional-integral (PI) and proportional-integral-derivate (PID) parameters in load frequency control of a single area power system. A single area non reheat thermal system is considered to design the PI and PID controllers which have optimized parameters obtained using GSA. The effectiveness of the proposed PI and PID controllers are compared with those of conventional PI controller. The simulation results show that the enhanced PI and PID controllers with the proposed approach provide a better damping of oscillations compared to those of conventional PI controller in power system.

A novel MPPT algorithm based on optimized artificial neural network by using FPSOGSA for standalone photovoltaic energy systems

Maximum power point tracking (MPPT) algorithms are used to maximize the output power of the photovoltaic (PV) panel under different temperature and irradiance conditions in photovoltaic energy sources (PVES). In this paper, a novel MPPT method based on optimized artificial neural network by using hybrid particle swarm optimization and gravitational search algorithm based on fuzzy logic (FPSOGSA) is proposed to track the operation of the PV panel in maximum power point (MPP). The performance of the proposed MPPT approach is tested by doing the simulation and experimental studies under different environmental conditions. The proposed method is compared with the conventional perturb and observation (P&O) method for standalone PVES. The results of the comparison the obtained from the simulation and experimental studies demonstrate that the proposed MPPT method provides the reduction oscillations around the MPP and the increased maximum power yield of the PV system in the steady state.

Application of Symbiotic Organisms Search Algorithm to solve various economic load dispatch problems

This paper proposes the application of Symbiotic Organisms Search (SOS) Algorithm to solve the various Economic Load Dispatch (ELD) problems. Both classical ELD problem which has smooth fuel cost function and nonconvex ELD problem which has nonconvex and discontinuous fuel cost function due to considering of some practical constraints like valve point effects, ramp rate limits and prohibited generating zones have been solved in the study. Three different test cases have been used to show the efficiency and reliability of the proposed algorithm. 38-unit test system has been used for classical ELD and 3-unit and 15-unit test systems have been used for nonconvex ELD problem. Results have been compared to various heuristic methods reported before in the literature and they show that proposed algorithm converges to the global optimum in early iterations and can produce superior results than others in the solution of ELD problems which have both smooth and nonconvex and discontinuous fuel cost function.

Optimal scheduling of short-term hydrothermal generation using symbiotic organisms search algorithm

In this study, the Symbiotic Organisms Search (SOS) algorithm is proposed to solve the short-term hydrothermal generation scheduling (STHGS) problem. This problem aims to optimize the power generation strategy produced by hydroelectric and thermal plants by minimizing the total fuel cost function while satisfying some operational constraints. In order to evaluate the effectiveness of the SOS, it has been tested on a system having a hydro plant with four-cascaded reservoir and a thermal plant. Results have been compared other metaheuristic methods. Results obtained from the experiment show that the proposed algorithm produces better results than the other methods and shows a good convergence.

A novel FACTS based on modulated power filter compensator for wind-grid energy systems

This paper represents a novel FACTS based on modulated power filter compensator (MPFC) for voltage stabilization in renewable wind energy with AC grid connected. Self-excited squirrel-cage induction generator (SEIG) is driven by a wind turbine for renewable a wind energy system. In order to improve voltage stabilization and energy utilization, the proposed FACTS technique is driven by a tri-loop dynamic error driven proportional-integral-derivate (PID) controller. To demonstrate the effectiveness of the proposed FACTS technique, a simulation model is developed for different operation conditions in MATLAB/SIMULINK software environment. Simulation results demonstrate that designed FACTS power filter compensator can be used to provide voltage regulation and efficient energy utilization.