Binod Shaw

Solution of economic dispatch problems by seeker optimization algorithm

Seeker optimization algorithm (SOA), a novel heuristic population-based search algorithm, is utilized in this paper to solve different economic dispatch (ED) problems of thermal power units. In the SOA, the act of human searching capability and understanding are exploited for the purpose of optimization. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the algorithm has been tested on four different small, as well as, large scale test power systems to solve the ED problems. The outcome of the present work is to establish the SOA as a promising alternative approach to solve the ED problems in practical power systems. Both the near-optimality of the solution and the convergence speed of the algorithm are promising. The results obtained are compared with those published in the recent literatures.

Seeker optimisation algorithm for the solution of economic load dispatch problems

Seeker optimisation algorithm (SOA), a novel heuristic population-based search algorithm, is utilised in this paper to solve different economic load dispatch (ELD) problems of thermal power units. In the SOA, the act of human searching capability and understanding are exploited for the purpose of optimisation. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the algorithm has been tested on four different small, as well as, large-scale test power systems to solve the ELD problems. The outcome of the present work is to establish the SOA as a promising alternative approach to solve the ELD problems in practical power systems. Both the near optimality of the solution and the convergence speed of the algorithm are promising. The results obtained by the SOA are compared to those published in the recent literatures to establish its superiority.

Solution of combined economic and emission dispatch problems using hybrid craziness-based PSO with differential evolution

In this paper, a hybrid craziness-based PSO with differential evolution (CRPSO-DE) algorithm is presented to solve complex, nonlinear, non-differentiable electric power system problems of combined economic and emission dispatch (CEED) with different cost functions and constraints. Traditionally, electric power systems are operated in such a way that the total fuel cost is minimized regardless of emissions produced. With increased requirements for environmental protection, alternative strategies are required. The proposed CRPSO-DE optimization algorithm attempts to reduce the production of atmospheric emissions (SOx and NOx oxides), caused by the operation of fossil-fueled thermal generation, along with the reduction of fuel cost. Such conflicting objectives are achieved by including equivalent cost of emissions as a part along with the fuel cost part in the multi-objective CEED optimization problem. The efficacy of the proposed optimization algorithm is tested on some test power systems taken from the literature and the results obtained are compared with those obtained by other methods reported in the state-of-the art literature. The results obtained demonstrate the effectiveness of the proposed algorithm for solving the CEED problems.

Techno-economic analysis of standalone photovoltaic/wind hybrid system for application in isolated hamlets of North-East India

This paper investigates the techno-economic analysis of standalone PV/wind hybrid system for remote household in North East (NE) region of India, where grid connectivity is not a feasible option. HOMER simulation software is used for sizing, optimization, and to perform the economical analysis of the hybrid system. Sensitivity analysis is carried out with solar radiation data, wind speed data, cost of PV and wind system for a 1 kW PV/wind hybrid system. The analysis is made on the assumption of an annual peak, scaled annual average, and the average load of 694 W, 3.95 kWh/day, and 0.165 kW, respectively, for a remote household. The optimal sizing, cost of electricity (COE), battery profile, and converter profile of PV/wind hybrid system for different NE states are presented in this paper. The outcome of this study shows that COE for the NE states is found to be in the range of 0.271–0.510

Solution of Optimal Power Flow with FACTS Devices Using Opposition-Based Gravitational Search Algorithm

/kWh, which is a acceptable margin and a hybrid PV/wind system will go a long way in addressing the shortage of power...

Solution of Optimal Reactive Power Dispatch by an Opposition-Based Gravitational Search Algorithm

This paper presents the solution of optimal power flow (OPF) of power system with flexible AC transmission systems (FACTS) devices by using opposition-based gravitational search algorithm (OGSA). OPF problem with FACTS is solved by the way of minimizing an objective function which reflects cost of generation, emission and active power transmission loss. FACTS devices considered include thyristor controlled series capacitor and thyristor controlled phase shifter. The proposed approach has been examined and tested on the IEEE 57-bus test power system. The obtained results are compared with those reported in the literature. Simulation results demonstrate the superiority and accuracy of the proposed algorithm. Considering the quality of the solution obtained, the proposed algorithm seems to be effective and robust to solve the studied problem.

Solution of Optimal Power Flow by an Opposition-Based Gravitational Search Algorithm

Management of reactive power resources is vital for stable and secure operation of power systems in the view point of voltage stability. In the present work, opposition-based gravitational search algorithm OGSA is applied for the solution of optimal reactive power dispatch ORPD of power systems. ORPD is an optimisation problem that decreases grid congestion with one or more objective of minimising the active power loss for a fixed economic power schedule. In this study, OGSA is tested on the standard IEEE 30-bus test system with different test cases such as minimisation of active power losses, improvement of voltage profile and enhancement of voltage stability. The obtained results are compared with those reported in the literature. Simulation results demonstrate the superiority and accuracy of the proposed algorithm. Considering the quality of the solution obtained, the proposed algorithm seems to be effective and robust to solve the ORPD problem.

A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems

This paper presents an evolutionary-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs opposition-based gravitational search algorithm (OGSA) for optimal settings of OPF control variables. The proposed approach is tested on the standard 26-bus test system with different objective functions those reflect minimization of fuel cost, that of transmission loss, that of sum of total voltage deviation while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, line flow limits, outputs of various compensating devices, etc. The simulation results of the proposed approach are compared with those reported in the literature. The obtained results demonstrate the potential of the proposed approach and show its effectiveness and robustness to solve the OPF problem of power system considered.