This paper presents a comparison of optimization methods applied to islanded micro-grids including renewable energy sources, diesel generators and battery energy storage systems. In particular, a comparative analysis between an optimization model based on linear programming and a model based on mixed integer programming has been carried out. The general formulation of these models has been pres...

An approach to calculate the wind farm penetration capacity based on chance constrained programming combining with transient check was presented. A novel model for programming penetration of wind farm under indeterminacy operating mode was presented. Constraint condition consisted of conventional generator output limits, system spinning reserve, transmission lines capability, nodal voltage, sys...

In a real electricity market, complete information of rivals’ behavior is not available to market participants. Therefore, they make their bidding strategies based on the historical information of the market clearing price. In this paper, a new market simulator is introduced for a joint energy and spinning reserve market, in which market participants’ learning process is modeled using Q-learnin...

In this paper, the authors present an approach combining the feedforward neural network and the simulated annealing method to solve unit commitment, a mixed integer combinatorial optimisation problem in power system. The artificial neural network (ANN) is used to determine the discrete variables corresponding to the state of each unit at each time interval. The simulated annealing method is use...

The impact of human activities on the environment as a consequence of the industrialization process, the rising trend of the price of fossil fuels, and the incentives offered by governments in many countries have driven the development and evolution of renewable energy sources such as wind energy. The optimal selection of on-line units and optimal output levels of committed units for convention...

Ant colony optimization (ACO) was inspired by the observation of natural behavior of real ants’ pheromone trail formation and foraging. Ant colony optimization ismore suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem. Multistage decision making of ACO gives an edge over other conventional methods. This paper proposes evolving ant col...

Ant Colony Optimization is more suitable for combinatorial optimization problems. ACO is successfully applied to the traveling salesman problem, and multistage decision making of ACO has an edge over other conventional methods. In this paper, the authors propose the Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) f...

In order to maintain the stability and security of the power system, the uncertainty and intermittency of wind power must be taken into account in economic dispatch (ED) problems. In this paper, a dynamic economic dispatch (DED) model based on chance constrained programming is presented and an improved particle swarm optimization (PSO) approach is proposed to solve the problem. Wind power is re...

In recent years, there has been a significant increase in energy produced by sustainable resources like windand solar power plants. This led to a shift from traditional energy systems to so-called smart grids (i.e., distributed systems of energy suppliers and consumers). While the sustainable energy resources are very appealing from an environmental point of view, their volatileness renders the...

This paper presents a new approach with artificial immune system algorithm to solve the profit based unit commitment problem. The objective of this work is to find the optimal generation scheduling and to maximize the profit of generation companies (Gencos) when subjected to various constraints such as power balance, spinning reserve, minimum up/down time and ramp rate limits. The proposed hybr...