Electrical power has been the technological foundation of industrial societies for many years. Although the systems designed to provide and apply electrical energy have reached a high degree of maturity, unforeseen problems are constantly encountered, necessitating the design of more efficient and reliable systems based on novel technologies. The book series Power Systems is aimed at providing detailed, accurate and sound technical information about these new developments in electrical power engineering. It includes topics on power generation, storage and transmission as well as electrical machines. The monographs and advanced textbooks in this series address researchers, lecturers, industrial engineers and senior students in electrical engineering. ** Power Systems is indexed in Scopus** More information about this series at http://www.springer.com/series/4622

SUMMARY In this paper, a new framework is presented for multi‐objective transmission expansion planning which expansion options are combination of transmission lines and phase shifter transformers. This framework is based on a multiple criteria decision making whose fundamental elements are reliability and market. Investment cost, congestion cost, users' benefit and expected customer interruption cost are considered in the optimization as four objectives. The proposed model is a non‐convex optimization problem having a non‐linear mixed‐integer nature. Hence, a hybrid genetic algorithm and quadratic programming is used followed by a fuzzy satisfying method to obtain the final optimal solution. The planning methodology has been demonstrated on the IEEE 30‐bus test system to show the feasibility and capabilities of the proposed model. Also, to compare the practical expansion plan and the expansion plan developed by the proposed method, it was implemented to the part of a real life 400‐kV transmission grid. Copyright © 2012 John Wiley & Sons, Ltd.

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a b s t r a c tIn this paper, a new approach is presented for developing optimal double-sided bidding strategy in security-constrained electricity markets by considering emission of pollutants, as further objectives. In the proposed methodology, both Generation Companies (GenCos) and Distribution Companies (DisCos) try to maximize their profit by implementation of optimal strategies, whiles they have incomplete information about their rivals and market mechanism of payment is locational marginal pricing. In addition, each participant provides its strategic bids based on supply function equilibrium model and it modifies its bidding strategies until Nash equilibrium points are computed. The proposed approach is modeled as a bi-level optimization problem with the upper sub problem addressing individual GenCos and DisCos and the lower sub problem addressing the Independent System Operator (ISO). The upper level maximizes the individual market participant's profit and the lower one solves the ISO's market clearing problem for maximizing Community Welfare Function (CWF). A Self-adaptive Global-based Harmony Search Algorithm (SGHSA) is used to obtain optimal bidding strategies. The proposed methodology has been implemented on the 6-machine 8-bus system test system to demonstrate the feasibility and effectiveness of the proposed approach. Simulation results illustrate the profitableness of the newly developed approach in the obtaining optimal bidding strategies.