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Hydro-thermal-wind generation scheduling (HTWGS) with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to generate an hour-by-hour optimum schedule of hydro-thermal-wind power plants to attain the least emission of pollutants from thermal plants and a reduced generation cost of thermal and wind plants for a 24-h period, satisfying the system constraints. The paper presents a detailed framework of the HTWGS problem and proposes a modified particle swarm optimization (MPSO) algorithm for evolving a solution. The competency of selected heuristic algorithms, representing different heuristic groups, viz. the binary coded genetic algorithm (BCGA), particle swarm optimization (PSO), improved harmony search (IHS), and JAYA algorithm, for searching for an optimal solution to HTWGS considering economic and environmental factors was investigated in a trial system consisting of a multi-stream cascaded system with four reservoirs, three thermal plants, and two wind plants. Appropriate mathematical models were used for representing the water discharge, generation cost, and pollutant emission of respective power plants incorporated in the system. Statistical analysis was performed to check the consistency and reliability of the proposed algorithm. The simulation results indicated that the proposed MPSO algorithm provided a better solution to the problem of HTWGS, with a reduced generation cost and the least emission, when compared with the other heuristic algorithms considered. [ABSTRACT FROM AUTHOR]

The congestion on transmission lines is a major issue in restructured power systems, the congestion occurs when the physical constraints on the transmission line are active, it means that the thermal limit of lines violates and it is called as a congested system. The congestion management (CM) is an important technique to control the transactions and keep the line flows schedule which will not overload the network. This paper presents relieving transmission line congestion with two methods. The first method is without disturbing any existing transactions by placing a thyristor-controlled series capacitor (TCSC) at optimal locations in the lines and the second method is rescheduling generators by considering a distribution generation (DG) unit at optimal locations on a load bus. The optimal locations of TCSC and DG units are obtained by the real power flow sensitivity index (PI) and transmission line relief (TLR) sensitivity indexes. The optimal power flow (OPF) is developed by overloading or line outage test system and simulated by optimization methods to find congested networks, the same line congestion will be alleviated by placing the TCSC/DG unit at optimal locations, and their optimal locations are found with the help of PI and TLR sensitivity indexes. All the OPF solutions are obtained by both classical (primal linear programming and interior point) and intelligent (particle swarm optimizations and genetic algorithm) methods. The proposed methods have been examined on 26-bus test systems. [ABSTRACT FROM AUTHOR]