A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based ...

This paper presents an application of BAT algorithm for multi-objective optimization problem in power system. Considering the environmental impacts that grow from the emissions produced by fossil-fuelled power plant, the economic dispatch that minimizes only the total fuel cost can no longer be considered as single objective. Application of BAT algorithm in this paper is based on mathematical m...

In practice, obtaining the global optimum for the economic dispatch {bf (ED)}problem with ramp rate limits and prohibited operating zones is presents difficulties. This paper presents a new andefficient method for solving the economic dispatch problem with non-smooth cost functions using aFuzzy Adaptive Genetic Algorithm (FAGA). The proposed algorithm  deals  with the issue ofcontrolling the ex...

In this research a multi-objective Imperialist Competitive Algorithm (MOICA) is applied for Environmental and Economic Power Dispatch (EED) problem. Due to the environmental concerns that arise from the emissions produced via fossil-fueled electric power plants, the classical economic dispatch, which operates electric power systems so as to minimize only the total fuel cost, can no longer be co...

Bi-objective problem; Hydrothermal scheduling; Economic dispatch; Emission dispatch; Combined economic emission dispatch Abstract The short-term combined economic emission hydrothermal scheduling is a bi-objective problem minimizing both fuel cost and emission of a hydrothermal system while satisfying thermal, hydro and system constraints. In this paper, an efficient cuckoo bird-inspired meta-h...

Differential Evolution (DE) algorithm is a heuristic approach for minimizing nonlinear and non-differentiable continuous space functions (storn, 1997). However, the implementation of DE requires some estimate of the global minimum to be provided, which is difficult for any arbitrary function. Also, the termination with maximum number of iterations does not assure the global minima. Moreover, as...