Sharif Digital Repository

In this paper, a new approach based on hybrid Particle Swarm-Based- Simulated Annealing Optimization (PSO-B-SA) for solving thermal unit commitment (UC) problems is proposed. The PSO-B-SA presented in this paper solves the two sub-problems simultaneously and independently; unit-scheduled problem that determines on/off status of units and the economic dispatch problem for production amount of generating units. Problem formulation of UC is defined as minimization of total objective function while satisfying all the associated constraints such as minimum up and down time, production limits and the required demand and spinning reserve. Simulation results show that the proposed approach can... 

In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and X iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods. © 2006 IEEE  

Energy storage systems are expected as a near-term solution for renewable energy application in the residential energy hubs. Within this context, this study investigates the feasibility of using storage systems in improving the technical and financial performance of the residential renewable-based energy hub. A new approach has been proposed in this study in which economic dispatch problem has been formulated for an energy hub including both electrical and heat storage system. The proposed approach determines the optimal supply of energy demand and storage system operation to minimise the total energy cost of the hub. The economic benefit of storage system due to energy cost saving and... 

In order to generate adequate electricity energy, conventional power plants utilize dramatic volume of water resources. Different methods such as replacing cutting-edge technologies of facilities have been proposed to diminish water consumption in this industry. Most of the approaches are considered as medium or long-term solution which requires substantial investment costs. Meanwhile, because of the process and technology, natural gas-fired power plants need less water among conventional power plants. Therefore, shifting unit commitment planning toward these power plants would aid to save water consumption. Nevertheless, overlooking combined cycle power plants can perform negative impact on... 

The usage of conventional fossil fuels has aided fast economic growth while also having negative consequences, such as increased global warming and the destruction of the ecosystem. This paper proposes a novel swarm-based metaheuristic method called Chimp Optimization Algorithm (ChOA) to tackle the environmental, economic dispatch issue and reducing the waste nonrenewable materials. In this regard, two objective functions named fuel cost function and emission cost function are proposed. Unique constrained handling also solves the challenge of multi-objective optimization. Standard IEEE 30 bus with six generators and a 10-unit system are used to demonstrate the usefulness of ChOA. The result... 

This paper presents a novel heuristic algorithm for solving economic dispatch (ED) problems, by employing iteration particle swarm optimization with time varying acceleration coefficients (IPSO-TVAC) method. Due to the effect of valve-points and prohibited operation zones (POZs) in the generating units' cost functions, ED problem is a non-linear and non-convex optimization problem. The problem even may be more complicated if transmission losses are taken into account. The effectiveness of the proposed method is examined and validated by carrying out extensive tests on three different test systems. Valve-point effects, POZs, ramp-rate constraints and transmission losses are modeled. Numerical...