N.K. Jain

Multiobjective optimal load flow based on ideal distance minimization in 3D space

Abstract In this paper, three objectives of Multiobjective Optimal Load Flow (MOLF) problem — cost of generation, system transmission loss and pollution — are considered. The MOLF problem is formulated as a multiobjective optimization problem using weighting method and a number of noninferior solutions are generated in 3D space. The optimal power system operation is attained by Ideal Distance Minimization method. This method employs the concept of an ‘Ideal Point’ (IP) to scalarize the problems having multiple objectives and it minimizes the Euclidean distance between IP and the set of noninferior solutions. This method has been applied to three IEEE standard systems.

GA based multiobjective economic load dispatch by Maximization Of Minimum Relative Attainments

In this paper, two important objectives of power systems - cost of generation and system transmission losses have been considered. The multiobjective economic load dispatch (MELD) problem is formulated using constraint method. Genetic Algorithm has been used to generate the noninferior set for IEEE 5, 14 and 30 bus systems in 2D space. Target Point (TP) or the best compromise solution has been achieved by Maximization of Minimum Relative Attainments method. This method assumes that all the objectives are being minimized and seeks the solution which maximizes the minimum relative attainment by any objective of its ideal reference value relative to its worst feasible value. The TP obtained by this method has been compared with that obtained by Ideal Distance Minimization method and Surrogate Worth Tradeoff technique. It is observed that the proposed method gives encouraging results for IEEE 5 and 14 bus systems whereas Ideal Distance Minimization method is the best for IEEE 30 bus system.

Regret analysis of sequential goal programming for multiobjective optimal power flows

The ideal power system operation is achieved when various objectives like cost of generation, system transmission losses, environmental pollution etc. are simultaneously attained with minimum values. These cannot be handled by single objective techniques as the above three objectives may be conflicting in nature in certain domain. Therefore, multiobjective programming techniques have to be employed as these are capable of minimizing more than one objective simultaneously. In this paper, three objectives of multiobjective optimal power flow (MOPF) problem - cost of generation, system transmission losses, environmental pollution are considered and MOPF problem is attempted sequentially using sequential goal programming (SGP). Six strategies have been developed for IEEE 5, 14 and 30 bus systems. The optimal strategy has been identified by the power systems operator using regret analysis