JOURNAL ARTICLE

Stochastic Evolutionary Multiobjective Environmental/Economic Dispatch

Abstract

Power system operation is subject to many uncertainties since acquired data are subject to inaccuracies due to inaccuracies in the process of measuring and forecasting of input data and changes of unit performance during the period between measuring and operation. In the environmental/economic dispatch problem, both fuel cost and emission are to be simultaneously minimized. In this paper, in order to obtain a solution closer to real-world situations, a constrained Monte Carlo sampling scheme is considered with stochastic decision variables, power system loads and objective functions whereby NSGA-II is used for solving the resulting stochastic environmental/economic dispatch problem. Simulation results presented for the standard IEEE 30-bus system show that the optimized system is reliable if stochastic variables are correlated.

Keywords:
Economic dispatch Electric power system Monte Carlo method Mathematical optimization Computer science Stochastic process Power system simulation Process (computing) Stochastic optimization Sampling (signal processing) Power (physics) Mathematics Statistics

Metrics

31
Cited By
3.02
FWCI (Field Weighted Citation Impact)
21
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Load and Power Forecasting
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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