Stochastic multi-objective optimization of combined heat and power economic/emission dispatch

Yousef ali Shaabani, Ali Reza Seifi and Masoud Joker Kouhanjani

Energy, 2017, vol. 141, issue C, 1892-1904

Abstract: In this paper, an optimization technique based on time-varying acceleration particle swarm optimization (TVAC-PSO) is applied for optimizing economic dispatch and emission reduction problems in a system consisting of CHP units. At first algorithm is used for deterministic model that for comparison with previous works. Besides, its convergence speed is adequately high. Then Monte Carlo method is implemented to solve the stochastic model providing real situation. In the Monte Carlo simulation you have a range of values as a result, and you are able to understand the risk and uncertainty in the model. Deterministic models used for conventional economic dispatch problems are not able to address some real conditions in practical applications. Deterministic models of power system applications are incapable to express the uncertainties that come from energy demand and supply of intermittent renewable systems. Due to the presence of these various uncertain variables stochastic attitude is inevitable in practical applications. Therefore, solving economic dispatch and emission reduction problems simultaneously and stochastically that is the main objective of this paper has a great level of importance. For modeling accurately, both power transmission losses and nonlinear fuel cost function are considered. The proposed method is applied to a 7-unit test system.

Keywords: Economic/emission dispatch; Emission reduction; Combined heat and power plant; Deterministic model; Stochastic model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:141:y:2017:i:c:p:1892-1904

DOI: 10.1016/j.energy.2017.11.124

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