Multi-Objective Economic Environmental Dispatch of Variable Hydro-Wind-Thermal Power System

2021 ◽  
Vol 12 (2) ◽  
pp. 16-35
Author(s):  
Suman Kumar Dey ◽  
Deba Prasad Dash ◽  
Mousumi Basu
Keyword(s):  
Power System ◽  
Thermal Power ◽  
Nox Emission ◽  
Fuel Cost ◽  
Nsga Ii ◽  
So2 Emission ◽  
Emission Level ◽  
Multi Objective ◽  
Thermal Power System ◽  
Operational Constraints

This article presents a multi-objective economic environmental/emission dispatch (EED) of variable head hydro-wind-thermal power system. The combination of NOx emission, SO2 emission, and fuel cost are minimized for non-smooth hydrothermal plants while satisfying various operational constraints like non-smooth fuel cost, penalty coefficient, and wind power uncertainty. The objectives—cost, NOx emission, and SO2 emission—are optimized at the same time. In this research, the non-dominated sorting genetic algorithm-II (NSGA-II) has been employed for solving the given problem where the total cost, NOx emission level, and SO2 emission level are optimized at the same time while satisfying all the operational constraints. The simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against strength pareto evolutionary algorithm 2 (SPEA 2).

scholarly journals Combined Economic and Emission Dispatch Problem of Wind-Thermal Power System Using Gravitational Particle Swarm Optimization Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Shanhe Jiang ◽  
Chaolong Zhang ◽  
Wenjin Wu ◽  
Shijun Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Particle Swarm Optimization Algorithm ◽  
Thermal Power ◽  
Particle Swarm ◽  
Compromise Solution ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Thermal Power System ◽  
Emission Dispatch

In this paper, a novel hybrid optimization approach, namely, gravitational particle swarm optimization algorithm (GPSOA), is introduced based on particle swarm optimization (PSO) and gravitational search algorithm (GSA) to solve combined economic and emission dispatch (CEED) problem considering wind power availability for the wind-thermal power system. The proposed algorithm shows an interesting hybrid strategy and perfectly integrates the collective behaviors of PSO with the Newtonian gravitation laws of GSA. GPSOA updates particle’s velocity caused by the dependent random cooperation of GSA gravitational acceleration and PSO velocity. To describe the stochastic characteristics of wind speed and output power, Weibull-based probability density function (PDF) is utilized. The CEED model employed consists of the fuel cost objective and emission-level target produced by conventional thermal generators and the operational cost generated by wind turbines. The effectiveness of the suggested GPSOA is tested on the conventional thermal generator system and the modified wind-thermal power system. Results of GPSOA-based CEED problems by means of the optimal fuel cost, emission value, and best compromise solution are compared with the original PSO, GSA, and other state-of-the-art optimization approaches to reveal that the introduced GPSOA exhibits competitive performance improvements in finding lower fuel cost and emission cost and best compromise solution.

Strategic Storage Use in a Hydro-Thermal Power System with Carbon Constraints

2020 ◽  
Author(s):  
Sébastien Debia ◽  
Pierre-Olivier Pineau ◽  
Afzal Siddiqui
Keyword(s):  
Power System ◽  
Thermal Power ◽  
Thermal Power System
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