This paper proposes a methodology for placement of sectionalizing switches in distribution networks in the presence of distributed generation sources. The multiobjective considerations are handled using a fuzzy approach. The primary objective is reliability improvement with consideration of economic aspects. Thus, the objectives are defined as reliability improvement and minimization of the cost of sectionalizing switches. A fuzzy membership function is defined for each term in the objective function according to relevant conditions. Some considerations incorporated in the proposed model are relocation of existing switches and operating constraints on distribution networks and distributed generation (DG) sources during post-fault service restoration. The Ant Colony Optimization (ACO) algorithm is adopted to solve the fuzzy multiobjective problem efficiently. The performance of the proposed approach is assessed and illustrated by various case studies on a test distribution system and also a real distribution network.
A Bilevel Stochastic Programming Problem (BSPP) model of the decision-making of an energy hub manager is presented. Hub managers seek ways to maximize their profit by selling electricity and heat. They have to make decisions about: i) the level of involvement in forward contracts, electricity pool markets and natural gas networks and ii) the electricity and heat offering prices to the clients. These decisions are made under uncertainty of pool prices, demands as well as the prices offered by rival hub managers. On the other hand, the clients try to minimize the total cost of energy procurement. This two-agent relationship is presented as a BSPP in which the hub manager is placed in the upper level and the clients in the lower one. The bilevel scheme is converted to its equivalent single-level scheme using the Karush-Kuhn-Tucker (KKT) optimality conditions although there are two bilinear products related to electricity and heat. The heat bilinear product is replaced by a heat pricequota curve and the electricity bilinear product is linearized using the strong duality theorem. In addition, Conditional Value at Risk (CVaR) is used to reduce the unfavorable effects of the uncertainties. The effectiveness of the proposed model is evaluated in various simulations of a realistic case study. Index Terms -Bilevel stochastic programming, energy hub, hub manager, electricity pool, forward contract, Conditional Value at Risk. NOMENCLATURE Indices Scenario index f Forward contract index t Time index k Forward contract block A. Najafi, H. Falaghi and M. Ramezani are with the
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