The economic emission load dispatch (EELD) problem is a multiple non-commensurable objective problem that minimizes both cost and emission together. In the paper a stochastic EELD problem is formulated with consideration of the uncertainties in the system production cost and nature of the load demand, which is random. In addition, risk is considered as another conflicting objective to be minimized because of the random load and uncertain system production cost. The weighted minimax technique is used to simulate the trade-off relation between the conflicting objectives in the non-inferior domain. Once the trade-off has been obtained, fuzzy set theory helps the power system operator to choose the optimal operating point over the trade-off curve and adjust the generation levels in the most economic manner associated with minimum emission and risk. The validity of the method is demonstrated by analysing a sample system comprising six generators.
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"The typical formulations of power generation scheduling problems are considered to be deterministic, as these are assumed disturbance free and accurate (Dhillon et al., 1993). But, this assumption is not appropriate for practical applications, as uncertainties is available everywhere 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. "
[Show abstract][Hide abstract] ABSTRACT: In this paper, Stochastic Economic Load Dispatch (ELD) problem with multiple fuels is solved using Improved Particle Swarm Optimization (IPSO). Generally, ELD problem is solved using deterministic models, but data required for such studies are rarely available with complete certainty. So uncertainties in unit’s generation, load demand and cost coefficients should be considered to get actual scenario. Thus, stochastic model for ELD problems is more suitable than deterministic model from the utilities point of view. ELD problem with deterministic model is first solved using IPSO to examine the effectiveness of the proposed method. Then IPSO is applied for ELD problem with stochastic model to investigate the real generation cost.
"However, the approach provided only weakly non-dominated solution and that too in considerably large time. The economic emission dispatch is solved by weighted min–max approach along with risk in expected power deviations as third objective . The EED problem with line flow security constraint is solved by weighted sum method in  to convert the multiobjective EED problem in single objective optimization problem. "
"In the concern of environmental awareness, pollution should be minimized which is achieved by combining cost and emission dispatch in a single objective function. Emission constrained economic dispatch is discussed in . "
[Show abstract][Hide abstract] ABSTRACT: The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.
Full-text · Article · Jan 2015 · Journal of Electrical Engineering and Technology