Load serving entities (LSE) of industrial district that have the operation responsibility of electric network, must procure the consumers electricity from wholesale electric market or the utility’s distributed generation (DG). The generation expansion planning (GEP) has a crucial impact on the optimality of LSE’s operation. In this paper, an innovative GEP is presented in which the location, time scheduling, heat and load capacity of combined heat and power generation units are determined based on a semi dynamic scheduling. The proposed algorithm uses a genetic algorithm for minimizing of LSE’s operation costs and it considers the heat/electric load following characteristics of DGs’. A case study is performed for a medium voltage feeder of industrial district, which its results approve the optimality of the solution.
Ansari, M., & SetayeshNazar, M. (2023). Optimal Locating and Capacity Selection of Gas Fired Distributed Cogeneration Systems for an Industrial District. Energy Engineering and Management, 2(1), 2-11.
MLA
Meisam Ansari; Mehrdad SetayeshNazar. "Optimal Locating and Capacity Selection of Gas Fired Distributed Cogeneration Systems for an Industrial District", Energy Engineering and Management, 2, 1, 2023, 2-11.
HARVARD
Ansari, M., SetayeshNazar, M. (2023). 'Optimal Locating and Capacity Selection of Gas Fired Distributed Cogeneration Systems for an Industrial District', Energy Engineering and Management, 2(1), pp. 2-11.
VANCOUVER
Ansari, M., SetayeshNazar, M. Optimal Locating and Capacity Selection of Gas Fired Distributed Cogeneration Systems for an Industrial District. Energy Engineering and Management, 2023; 2(1): 2-11.