Biplab Bhattacharyya

Loss Sensitivity Approach in Evolutionary Algorithms for Reactive Power Planning

Abstract This article presents evolutionary algorithm-based optimal reactive power planning. A “loss sensitivity” approach is developed and implemented using differential evolution, particle swarm optimization, and the genetic algorithm. The objectives are to minimize real power loss and to improve the voltage profile of an interconnected power system. Transmission loss is expressed in terms of voltage increments by relating the control variables, i.e., reactive var generations by the generators, tap positions of transformers, and reactive power injected by the shunt capacitors. Based on the values of the loss sensitivity, corrective action is taken by adding a shunt capacitor at the weak buses identified by weak bus analysis, by controlling reactive generations at the generator buses by judging the sensitivity at these buses, and also by controlling tap changing positions if the tap changing transformers are in between the loss sensitive buses. The solutions obtained by this method is compared with the solutions obtained by each of these evolutionary algorithm—separately and with their hybrids with simulated annealing. From the comparisons, it is shown how the sensitivity-based evolutionary technique can be a very useful new tool for the reactive power planning.

Differential Evolution Technique for the Optimization of Reactive Power Reserves

In the present work, reactive power planning problem along with voltage stability margin is addressed by effective co-ordination of reactive power sources. Modal analysis and L-index methods are used to detect weak nodes of the system accordingly. Differential Evolution (DE) and Genetic Algorithm (GA)-based optimization techniques are applied for the proper co-ordination of Var sources under base and increased loading conditions maintaining voltage stability of the connected power network. The problem is multi-objective and IEEE 30 bus system is taken as the standard system. It is observed that modal analysis based detection of weak nodes are more effective than the L-index-based detection. Moreover, the DE-based optimization algorithm gives better result compared to GA-based approach in maximizing reactive power reserves.

Fuzzy-DE approach for the optimal placement of FACTS devices to relief congestion in a power system

Congestion in transmission lines is considered as a major problem for the electric power transmission. Flexible AC transmission systems (FACTS) devices play a vital role in eliminating transmission line congestion in deregulated power system, improvement of power transfer capacity of an interconnected power system under different loading conditions, thereby increases the possibilities of better economic operation of power system. In the proposed approach fuzzy membership function is used for the determination of weak nodes of a power system for the placement of SVC as one of the FACTS devices. TCSC is the other type of FACTS devices whose positions are determined by the reactive power flow in lines. Then Differential Evolution (DE) is used for the optimal setting of the power system variables, including FACTS devices. The proposed technique is compared with other methods for weak bus detection using modal analysis and the significance of the use of fuzzy membership is clearly observed from the comparative analysis.

Fuzzy Genetic Algorithm Approach for the Optimal Placement of Flexible AC Transmission Systems Devices in a Power System

Abstract—This article presents a novel approach for optimal flexible AC transmission systems devices planning in an interconnected power system under different loading conditions. The static VAR compensator and thyristor-controlled series capacitor are two types of flexible AC transmission systems devices considered for optimal power system operation. In the proposed approach, a fuzzy membership function is used to determine weak nodes in the power system for the placement of static VAR compensators as a flexible AC transmission systems device. The thyristor-controlled series capacitor is the other type of flexible AC transmission systems devices for which its positions are determined by the reactive power flow in lines. The genetic algorithm is used for the optimal setting of the power system variables, including flexible AC transmission systems devices. The proposed technique is compared with other optimization methods using different globally accepted evolutionary algorithms where the nodes or point of VAR compensation is determined by eigenvalue analysis, and the amount of flexible AC transmission systems devices is determined by evolutionary techniques, such as the genetic algorithm, differential evolution, and particle swarm optimization. The superiority of the proposed fuzzy-based optimization approach is established by the results and comparative analysis with other methods.

Weak Bus-Oriented Installation of Phasor Measurement Unit for Power Network Observability

Abstract Phasor measurement unit (PMU) is a GPS-based monitoring equipment employed for the improvement of the stability and reliability of the electrical grid. In this work, an optimal PMU placement has been considered to utilize the least number of units in order to make the power network fully observable. Further, this article also suggests to not only determine the minimal number and optimal locations of PMUs but also installation of the maximum number of PMUs on the weakest bus in an electrical network. Thus, the weak bus based on line stability index utilizing load flow measurement is determined. Then a novel numerical methodology which depends upon binary integer linear programming, constrained by weak bus measurement is proposed in this paper. Also, the effect of a single PMU loss considering weak buses is shown. The developed approach has been conducted on standard IEEE -14, -118, -300 and New England 39- bus test systems. Finally, obtained results and comparison with different weak bus methodologies are shown and examined.

Weak bus-oriented optimal Var planning based on grey wolf optimization

From last few decades, the frequent occurrence of the voltage collapse has attracted more and more attention. Voltage collapse is the system instability, usually, associated with the shortage of reactive power at the load end involving the entire power systems. The most effective method to counter voltage collapse is to find out the possible locations where voltage collapse may occur i.e. to find the weakest buses existing in the system. Weak bus oriented Var planning by grey wolf optimization (GWO) for system security has been proposed in this paper. Weak buses of the system has been determined by using four different methods, namely, fast voltage stability index (FVSI), line stability factor (LSF), line stability index (LSI) and voltage collapse proximity indicator (VCPI) method. Standard IEEE 57 bus test system is used as the test system to show the applicability of the proposed work. It has been observed that Var planning based on the detection of weak buses by voltage collapse proximity indicator provides the best result among other methods reported in literature.

Weak bus determination and real power loss minimization using Grey wolf optimization

A new optimization algorithm approach is proposed named Grey wolf optimization algorithm for the solution of reactive power planning (RPP) of a connected power network based on the detection of weak buses determined by line stability index method and Fast voltage stability index. The optimization algorithm is then applied on standard IEEE 30 and IEEE 57 bus system. The objective of the proposed work is to minimize active power loss and operating cost by proper coordination of reactive power generation of the generators, transformer tap setting positions and shunt capacitors placed at the weak buses of the system while maintaining voltage profile within acceptable limit. Finally, it is observed that reactive power planning with line stability index method yields better result than planning with fast voltage stability index.

A novel approach for the voltage stability assessment and reactive power planning

In the present work, reactive power planning problem along with voltage stability margin is addressed by effective co-ordination of reactive power sources. Modal analysis and L-index methods are used to detect weak nodes of the system accordingly. GA (Genetic Algorithm) based optimization technique is applied for the proper co-ordination of Var sources under base and increased loading conditions maintaining voltage stability of the system. The problem is multi-objective and IEEE 30 bus system is taken as the standard system.

Allocation of Phasor Measurement Unit using A-star method in connected power network

This paper explores an A-star based approach for optimal Phasor Measurement Unit (PMU) placement (OPP) which is beneficial for achieving full observability of the connected power network under usual operating environments. The main aim of the proposed approach is to lessen the number of PMU at the connected power network buses, which in turn reduce the setup cost of the PMU. The proposed approach is tested on conventional IEEE 14-bus, 30-bus, New England 39-bus, 57-bus, Indian Utility 62-bus, and 118-bus system. The results obtained with the proposed approach have been compared with the existing methods. It is observed that the proposed approach is able to achieve the full observability of the connected power network with minimum number of PMU.

Optimal placement of phasor measurement unit using binary particle swarm optimization in connected power network

This paper suggested binary particle swarm optimization (BPSO) technique to place phasor measurement units (PMUs) optimally at suitable sites in a connected power network so that the connected power network can be fully perceptible. The goal of the suggested approach is to minimize number of PMUs as it is unwise to site PMUs at each bus to measure the state of connected power network as the PMUs and communication facilities are very expensive. The suggested method is applied on standard test systems such as IEEE 14, 30, New England 39 and IEEE 57-bus test system for optimal placements of PMUs with and without deliberation of zero injection bus. The outcomes compared with the existing standard results in literature. It is observed that the suggested approach ensures that the connected power network with minimum number of PMUs is fully observable.