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Hybrid of Lamda and Bee Colony Optimization for Solving Economic Dispatch DOI:10.15199/48.2016.09.54

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This paper proposes the method to solve the economic dispatch problem with hybrid of lamda and bee colony optimization (HLBCO). The fundamental constraints of economic dispatch problem are the load demand and power loss into consideration. The generation cost function considering smooth cost function characteristic. To verify the performance of the proposed HLBCO algorithm, it is operated by the simulation on the MATLAB program and tested the two case studies. The simulation results indicate that the HLBCO can provide a better solution than the others in terms of quality solution, computational and convergence efficiently. Streszczenie. W artykule zapropponowano metode optymalizacji rozsyłu energii prze wykorzystanie hybrydy dwóch metod: lamda i algorytmów rojowych HLBCO. Symulacja przeprowadzona nakilku przykładach dowodzi że zaproponowany algorytm lepiej rozwiązuje prtoblemy ekonomicznego rozsyłu biorąc pod uwagę jakość I skuteczność. Optymalizacja ekonomii rozsyłu enegii z wykorzystaniem metod rojowych I metody lamda.. Keywords: lamda, bee colony, optimization, economic dispatch. Słowa kluczowe: metody rojowe, metoda lamda, optymalizacja rozsyłu enrgii. Introduction The electricity is an important for economic and social development. Planning, security and reliability of electrical power are necessary for electrical power generation. Economic dispatch is the method of determinative the most efficient, low cost and reliable operation of a power. The objective function of economic dispatch is to minimize the total fuel cost of electrical power generation which the demand, power loss and constraints are satisfied. There are many methods to solving the economic dispatch problem. The conventional methods for solving economic dispatch problem are lamda iteration method, gradient method, newton’s method, piecewise linear cost functions and dynamic programming [1] that owing to tedious calculations and its incapability to solve mu[...]

Hybrid Algorithm combining Lambda Iteration and Bee Colony Optimization to Solve an Economic Dispatch Problem with Prohibited Operating Zones DOI:10.15199/48.2019.10.02

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Reliability, stability, and economic efficiency are very important for the planning and operation of a power generation system. To get profits from the capital invested, efficient economic operation is critical. Operational economics, involving then minimization of power generation and delivery costs, is called Economic Dispatch (ED). The objective of economic dispatch is to minimize the total cost of all generations while satisfying all operating constraints. To solve the problem of economic dispatch, there are two approaches, including classical and meta-heuristic methods. Classical methods, such as lambda iteration and gradient methods are the most common ones applied to solve the continuous ED problem [1]-[2]. These methods require incremental fuel cost curves which are piecewise and linear. Lagrangian relaxation [3] and dynamic programming [4] is one of the approaches that are used to solve a non-linear and discontinuous ED problem. Numerical methods can cause problems in complicated and large power systems as they suffer from the complexities of dimensionality and local optimality. Recently, meta-heuristic methods have been used to solve the economic dispatch problem. Such methods include simulated annealing (SA) [5]-[6], a genetic algorithm (GA) [7]-[8], an evolutionary program (EP) [9]-[10], tabu search (TS) [11], particle swarm optimization (PSO) [12]-[14], ant colony optimization (ACO) [15]-[17] and bee colony optimization (BCO) [18]-[20]. These methods can obtain a global optimum within a short time and guarantee an optimum solution. However, in these techniques the initial populations are generated randomly. This results in long computation times and a long time to convergence when the generated initial populations are too far from the optimum solution. This problem has been solved by HLBCO [21]-[22] in which the initial population of BCO is modified. However, this method considers a static economic dispatch si[...]

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