Multiobjective particle swarm optimization for environmental/economic dispatch problem
نویسنده
چکیده
A newmultiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed in this paper. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposedMOPSO technique has been implemented to solve the EED problemwith competing and non-commensurable cost and emission objectives. Several optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. The comparison with the different reported techniques demonstrates the superiority of the Multiobjective optimization Nondominated solutions P proposed MOPSO in terms of the diversity of the Pareto-optimal solutions obtained. In addition, a quality measure to Pareto-optimal solutions has been implemented where the results confirm the potential techn
منابع مشابه
A Study of VEPSO Approaches for Multiobjective Real World Applications
The purpose of this paper is to evaluate the performance of two approaches based on Vector Evaluated Particle Swarm Optimization (VEPSO) algorithm in two real world applications, which are the environmental economic dispatch problem and the optimization of a reinsurance contract portfolio. The two tested algorithms are the canonical VEPSO and a new version called VEPSO-N, where in the last one ...
متن کاملCultural quantum-behaved particle swarm optimization for environmental/economic dispatch
In this paper, a novel CMOQPSO algorithm is proposed, in which cultural evolution mechanism is introduced into quantum-behaved particle swarm optimization (QPSO) to solve multiobjective environmental/economic dispatch (EED) problems. There are growing concerns about the ability of QPSO to handle multiobjective optimization problems. Two important issues in extending QPSO to multiobjective conte...
متن کاملParticle Swarm Optimization with Smart Inertia Factor for Combined Heat and Power Economic Dispatch
In this paper particle swarm optimization with smart inertia factor (PSO-SIF) algorithm is proposed to solve combined heat and power economic dispatch (CHPED) problem. The CHPED problem is one of the most important problems in power systems and is a challenging non-convex and non-linear optimization problem. The aim of solving CHPED problem is to determine optimal heat and power of generating u...
متن کاملEconomic Dispatch of Thermal Units with Valve-point Effect using Vector Coevolving Particle Swarm Optimization Algorithm
Abstract: This paper is intended to reduce the cost of producing fuel from thermal power plants using the problem of economic distribution. This means that in order to determine the share of each unit, considering the amount of consumption and restrictions, including the ones that can be applied to the rate of increase, the prohibited operating areas and the barrier of the vapor barrier, the pr...
متن کاملA Novel Social-environmental-economic Dispatch Model for Thermal/wind Power Generation and Application
A novel model including social, environmental and economic benefits is proposed in hybrid thermal/wind power system and studied by Karush-Kuhn-Tucker and hybrid particle swarm optimization techniques. Our work is the first to develop social dispatch model by calculating risk caused by wind power. Then the novel multi-objective optimization model of social-environment-economic dispatch is establ...
متن کامل