Deblina Maity

Implementation of quassi-oppositional TLBO technique on economic load dispatch problem considering various generator constraints

This paper presents a novel modified teaching learning based optimization method(TLBO) i.e quasi-oppositional TLBO (QOTLBO) algorithms to solve economic load dispatch problem of the thermal plant without considering transmission losses. The offered methodology can manage ELD problems using nonlinearities such as valve point loading, ramp rate limit and prohibited zone. The objective of ELD problem is to evaluate the optimal power generation allocation of units to satisfy the load demand, and also the overall cost of generation should be minimized, and different operational constraints should be fulfilled. General TLBO, a newly appeared evolutionary algorithm depend on two basic ideas of education namely teaching phase and learning phase. The efficiency of the offered algorithms has been checked on test system with equality and inequality constraints. The result is compared with the other existing techniques which prove the efficiency of algorithms.

Implementation of MRPSO techniques on economic load dispatch problem considering various generator constraints

This article presents moderate-random-search strategy PSO called MRPSO to solve both convex and non-convex economic load dispatch (ELD) problem of the thermal unit. Here transmission loss is not considered. The proposed methodology can take care of ELD problems considering nonlinearities such as valve point loading, ramp rate limits, prohibited zone etc. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. The effectiveness of the proposed algorithms has been verified on different test systems with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithms.

Solving of economic load dispatch problem with generator constraints using ITLBO technique

This paper presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering nonlinearities such as valve point loading, ramp rate limit and prohibited zone. The objective of ELD problem is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.

Solution of multi-objective emission & economic dispatch using bare bones TLBO algorithm & biogeography based optimization algorithm

Now a days economic emission load dispatch (EELD) is a major difficulty in electrical engineering network. The main goal of economic and emission load dispatch suitable power allocation meeting and satisfying constraints where fuel and emission cost are minimized. Here transmission losses are not considered. Here bare-bones teaching learning based optimization technique and biogeography based optimization technique have been proposed in this article to solve ELD and emission dispatch(ED) problem. The proposed algorithms have been tested on three different test systems with linear and non-linear constraints. The advantage of these proposed algorithms has been proved by comparing with different optimization techniques.

Multi-objective economic emission load dispatch using modified biogeography based optimization algorithm

In this article modified biogeography-based optimization (MBBO) algorithm is proposed to solve convex and non-convex combined economic and emission load dispatch (CEELD) problem of power system. Some non-linearities like transmission losses and valve point loading effects are considered. The main objective of EELD is to allocate power generation within their limits satisfying load demand where cost and emission both will be minimized. Biogeography interacts with the biological distribution of species. The proposed MBBO algorithm has been tested on three different test systems considering equality and inequality constraints. The results are checked the convergence characteristics with other techniques which prove the advantage of the proposed MBBO algorithms.

Optimal sizing and location determination of distributed generation in distribution networks

Distributed generation (DG) can be integrated into distribution systems to meet the increasing load demand. This paper discusses the sizing and sitting issue of single DG placement in radial distribution systems using distflow technique. The main objective of the work is to minimize the active and reactive power loss and enhance voltage profile of overall system. The effectiveness of the proposed idea has been successfully tested on 12.66 kV radial distribution systems consisting of 33 nodes and the results are found to be in very good agreement.