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Well-structured reactive power policies and dispatch are major concerns of operation and control technicians of any power system. Obtaining a suitable reactive power dispatch for any given load condition of the system is a prime duty of the system operator. It reduces loss of active power occurring during transmission by regulating reactive power control variables, thus boosting the voltage profile, enhancing the system security and power transfer capability, thereby attaining an improvement in overall system operation. The reactive power dispatch (RPD) problem being a mixed-integer discrete continuous (MIDC) problem demands the solution to contain all these variable types. This paper proposes a methodology to achieve an optimal and practically feasible solution to the RPD problem through the diversity-enhanced particle swarm optimization (DEPSO) technique. The suggested method is characterized by the calculation of the diversity of each particle from its mean position after every iteration. The movement of the particles is decided based on the calculated diversity, thereby preventing both local optima stagnation and haphazard unguided wandering. DEPSO accounts for the accuracy of the variables used in the RPD problem by providing discrete values and integer values compared to other algorithms, which provide all continuous values. The competency of the proposed method is tested on IEEE 14-, 30-, and 118-bus test systems. Simulation outcomes show that the proposed approach is feasible and efficient in attaining minimum active power losses and minimum voltage deviation from the reference. The results are compared to conventional particle swarm optimization (PSO) and JAYA algorithms.

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]

These paper proposes real and reactive power management strategies of electronically interfaced distributed generation (DG) units in the context of multiple-DG of microgrid systems. In autonomous mode of microgrid, the power demand in the microgrid is supplied by the distributed generators (DGs) and controlled with the help of voltage source converters (VSCs), which control the desired real and reactive power flow between DGs to reach different load conditions. An arrangement of DGs in the microgrid is proposed to achieve load sharing in both grid connected and autonomous modes. This system can work as grid connected and autonomous mode depends on power requirement of microgrid, where power flow form grid to microgrid and vice-versa. The back-to-back converters also provide total frequency isolation between the grid and the microgrid. It is shown that the voltage or frequency fluctuation on the grid side has no impact on voltage or power on microgrid side. Different loads are considered to verify the system stability. All system model and daily load demand of microgrid has been simulated in PSCAD. [ABSTRACT FROM AUTHOR]

In this paper, design and implementation of an optimized controller for a single magnet-based electromagnetic levitation system (EMLS) where an electromagnet of 2.6-kg mass is levitated over a large gap under a fixed ferromagnetic guide-way has been discussed. EMLS is inherently unstable and strongly non-linear in nature. A single position controller (lead type) along with an outer proportional-integral (PI) controller has been designed that will stabilize the EMLS represented mathematically by three different plants corresponding to three different operating points. An optimization technique utilizing the random search method with interval reduction, proposed by Luus and Jaakola, has been used for designing the controller. A "model matching control" design procedure has been utilized for the design of outer PI controller. The inner controller stabilizes the three unstable plants, whereas the outer PI control action is used to modify the three position outputs as per the desired model response. The combined control action provides good stability and satisfactory performance (like fast response, less overshoot, and zero steady-state error) for the different operating zones of EMLS. Stability has been confirmed by Kharitonov-Nyquist enclosure diagrams. The simulated controllers have been successfully implemented, thus validating the modeling and controller design procedure. [ABSTRACT FROM AUTHOR]