Abstract
In this paper, a computation framework for addressing combined economic and emission dispatch (CEED) problem with valve-point effects as well as stochastic wind power considering unit commitment (UC) using a hybrid approach connecting sequential quadratic programming (SQP) and particle swarm optimization (PSO) is proposed. The CEED problem aims to minimize the scheduling cost and greenhouse gases (GHGs) emission cost. Here the GHGs include carbon dioxide (CO2), nitrogen dioxide (NO2), and sulphur oxides (SOx). A dispatch model including both thermal generators and wind farms is developed. The probability of stochastic wind power based on the Weibull distribution is included in the CEED model. The model is tested on a standard system involving six thermal units and two wind farms. A set of numerical case studies are reported. The performance of the hybrid computational method is validated by comparing with other solvers on the test system.
Highlights
Power system generation scheduling problem can be divided into two sub-problems, unit commitment (UC) and economic dispatch (ED)
To address the uncertainties in wind power production, wind speed distribution probability functions are applied in formulating the optimization model
UC and ED problem of wind power will start to affect market price of smart grid system, because it became a factor affecting the operation of smart grid and the cost
Summary
With the awareness of environmental pollution contributed by the combustion of fossil fuels, building a low-carbon world has attracted widespread attentions. Based on our experience, when compared with other approaches, the PSO is computationally inexpensive in terms of memory and speed These heuristic methods do not always guarantee discovering globally optimal solutions in finite time, especially when being applied into large-scale optimization problems. In [23], a hybrid approach combining DE with biogeography-based optimization (DE/BBO) was developed to address both convex and non-convex ED problem. SQP is firstly used to solve the CEED problem without considering the valve-point effects, and based on the obtained initial solution and boundaries PSO is employed to solve the CEED problem with non-smooth fuel cost function.
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