This article presents the novel and efficient approach to solve the dynamic economic dispatch (DED) problem, including valve-point effects. The DED problem is an optimization problem with an objective to determine the optimal combination of power outputs for all committed generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. The differential evolution (DE) algorithm is a powerful evolutionary algorithm for global optimization in real problems. In the proposed approach, the conventional economic load dispatch, for each time interval in a forward and reverse sequence, is independently performed using the DE algorithm with suitable modifications of the generation limits of the units due to the ramp-rate constraints of the generators. A certain load profile requires the traditional DED for a given set of committed units is determined by checking each interval in the scheduling horizon for the power-balance constraint violation due to the ramp-rate constraints of generators. A look-ahead procedure is implemented in the algorithm to identify the number of preceding intervals in case of forward dynamic dispatch or succeeding intervals in case of backward DED, which requires traditional DED to satisfy the power-balance constraints. Five- and ten-unit test systems with non-linear characteristics of the generators are considered to illustrate the effectiveness of the proposed method. The feasibility of the proposed method is demonstrated and compared to those reported in the literature. The results are promising and show the effectiveness of the proposed method.
机构:
King Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
Al Azhar Univ, Fac Sci, Dept Math, Assiut 71511, EgyptKing Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
Elaiw, A. M.
Xia, X.
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Univ Pretoria, Dept Elect Elect & Comp Engn, Ctr New Energy Syst, ZA-0002 Pretoria, South AfricaKing Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia
Xia, X.
Shehata, A. M.
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Al Azhar Univ, Fac Sci, Dept Math, Assiut 71511, EgyptKing Abdulaziz Univ, Fac Sci, Dept Math, Jeddah 21589, Saudi Arabia