this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

UC (Unit Commitment) is a non-linear, large scale, complex, mixed-integer combinatorial constrained optimization problem. This paper proposes, a new hybrid approach for generating UC schedules using SI (Swarm Intelligence) learning rule based NN (Neural Network). The training data has been generated using DP (Dynamic Programming) for machines without valve point effects and using genetic algori...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

Combined cooling, heat, and power (CCHP) units can be integrated with conventional separate cooling, heat, and power production units to meet demands. The goal of this study is to develop and examine a hybrid GA-heuristic optimization algorithm for solving the unit commitment problem for integrated CCHP-thermal-heat only system with considerations for electricity boiler. When environmental emis...

Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED) problems with valve-p...

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evo...

a computational optimization was performed for a direct-injection diesel engine using three-dimensional modeling. fully transient cfd analyses of different valve profile strategies for the intake and compression strokes were performed to evaluate the effects on both engine performance and in-cylinder flow-field evolution. the turbulence model was used along with the second order linear upwind s...

A computational optimization was performed for a direct-injection diesel engine using three-dimensional modeling. Fully transient CFD analyses of different valve profile strategies for the intake and compression strokes were performed to evaluate the effects on both engine performance and in-cylinder flow-field evolution. The turbulence model was used along with the second order linear upwin...

economic dispatch with valve point effect and prohibited operating zones (pozs) is a non-convex and discontinuous optimization problem. harmony search (hs) is one of the recently presented meta-heuristic algorithms for solving optimization problems, which has different variants. the performances of these variants are severely affected by selection of different parameters of the algorithm. intel...