Recently, Combined Heat and Power (CHP) systems have been utilized increasingly in power systems. With the addition penetration of CHP-based co-generation of electricity and heat, the determination of economic dispatch of power and heat becomes a more complex and challenging issue. The optimal operation of CHP-based systems is inherently a nonlinear and non-convex optimization problem with a lot of local optimal solutions. In this paper, the Improved Shuffled Frog Leaping Algorithm (ISFLA) is used for solution of the problem. ISFLA is an improved version of shuffled frog leaping algorithm in which new solutions are produced in respect to global best solution. The ISFLA is well able to attain the optimal solutions even in the case of non-convex optimization problems. To evaluate the efficiency of the proposed method, it has been implemented on the standard test system. The obtained results have been compared with other heuristic methods. The numerical results show that the ISFLA is faster and more precise than other methods. Manuscript profile

Due to the ever-growing load, especially peak load, the increase in the capacity of plants is inevitable for the response to this growth. Peak load causes increases in customer costs and vast investments in generating and transmission parts. Therefore, restructuring in the electrical industry, competition in the electrical market and Demand Response Programs (DRPs) are of special importance in power systems. In DRPs, customers in certain periods, such as peak or times when the price is high, decrease self-consumption. It means profit for costumers and prevention of expensive production in peak time for a genera-tion source. Moreover, to decrease the operation cost of network and ever-growing technology significantly, the power sys-tems operators have employed new sources of energy production as well as thermal units, and it has led to the emergence of Electric Vehicles (EVs) technology as a new source of energy production. This paper studies the simultaneous presence of DRPs and EVs to minimize the total operation cost of a network from one hand and from the other to improve the level of system reserve in Unit Commitment (UC) problem with considering the security constraint. Here, the proposed framework is structured as a Mixed Integer Programming (MIP) and solved using CPLEX solver. Manuscript profile