K.S. Swarup

Unit Connuitment Solution Methodology Using Genetic Algorithm

Solution methodology of unit commitment using genetic algorithms (Gas) is presented. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start-up cost, and spinning reserve, which is defined as minimization of the total objective function while satisfying the associated constraints. Problem-specific operators are proposed for the satisfaction of time-dependent constraints. Problem formulation, representation, and the simulation results for a 10-generator-scheduling problem are presented.

Differential evolution approach for optimal reactive power dispatch

Differential evolution based optimal reactive power dispatch for real power loss minimization in power system is presented in this paper. The proposed methodology determines control variable settings such as generator terminal voltages, tap positions and the number of shunts to be switched, for real power loss minimization in the transmission system. The problem is formulated as a mixed integer nonlinear optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling. The formulation also checks for the feasibility of the optimal control variable setting from a voltage security point of view by using a voltage collapse proximity indicator. The algorithm is tested on standard IEEE 14, IEEE 30, and IEEE 118-Bus test systems. To show the effectiveness of proposed method the results are compared with Particle Swarm Optimization and a conventional optimization technique - Sequential Quadratic Programming.

Multi-objective biogeography based optimization for optimal PMU placement

The paper proposes a multi-objective biogeography based optimization (MO-BBO) algorithm to design optimal placement of phasor measurement units (PMU) which makes the power system network completely observable. The simultaneous optimization of the two conflicting objectives such as minimization of the number of PMUs and maximization of measurement redundancy are performed. The Pareto optimal solution is obtained using the non-dominated sorting and crowding distance. The compromised solution is chosen using a fuzzy based mechanism from the Pareto optimal solution. Simulation results are compared with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Non-dominated Sorting Differential Evolution (NSDE). Developed PMU placement method is illustrated using IEEE standard systems to demonstrate the effectiveness of the proposed algorithm.

A Hybrid Interior Point Assisted Differential Evolution Algorithm for Economic Dispatch

The paper proposes a novel hybrid algorithm connecting interior point method (IPM) and differential evolution (DE) for solving economic load dispatch problem with valve point effect. The algorithm involves two stages. The first stage employs IPM to minimize the cost function without considering the valve point effect. The second stage considers valve point effect and minimizes the cost function using DE. The initial population for DE is generated in a narrow range of 2π/f around the solution obtained in the first stage. The effectiveness of the algorithm is validated by carrying out extensive tests on three different systems involving 13 and 40 thermal generating units. The proposed method outperforms other existing techniques for economic load dispatch considering valve-point effects.

High-Speed Fault Classification in Power Lines: Theory and FPGA-Based Implementation

This paper presents a fast hardware-efficient logic for fault detection and classification in transmission lines, implemented using a field-programmable gate array (FPGA). The general-purpose SPARTAN3E FPGA was employed for developing the prototype, with all the coding done using a hardware description language (HDL) called very high speed integrated circuit (VHDL). The proposed logic employs only one-terminal current samples and is based on wavelet analysis. Depending on the amount of high frequency components in the current signals after processing, the faults are classified into ten types. The real time windows target toolbox of MATLAB was used to apply the current signal inputs to the prototype in real time. An adaptive threshold value is chosen, rather than a fixed threshold in the case of faults involving the ground, to make the classification reliable and accurate. The fault classification time is 6 ms, which is about 1/3 of the power frequency cycle (20 ms). A high level of computational efficiency is achieved as compared to the other wavelet-transform-based algorithms, since only the high frequency details at first level are employed in this algorithm. The validity of the proposed logic was exhaustively tested by simulating various types of faults on a system modeled in the electromagnetic transients program/alternative transients program. The proposed logic was found to be highly reliable and accurate, even in the presence of fault resistance.

Particle swarm optimization for security constrained economic dispatch

This paper presents an efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with security constraints. The proposed approach employ particle swarm optimization (PSO) algorithm for ELD. Incorporation of type 1 PSO as a derivative-free optimization technique in solving ELD with voltages and lineflow constraints significantly relieves the assumptions imposed on the optimized objective function. The proposed approach has been tested on three representative systems, i.e. IEEE 14 bus, IEEE 30 bus and IEEE 57 bus systems respectively. The feasibility of the proposed method is demonstrated and the results are compared with linear programming, quadratic programming and genetic algorithm respectively. The developed algorithms are computationally faster (no. of load flows) than the other methods.

A genetic algorithm approach to generator unit commitment

Application of genetic algorithms for the solution of unit commitment with detailed problem formulation, solution methodology and representation is described in this paper. New Encoding and Representation strategy is proposed that can handle large systems with an improvement in solution and faster convergence. The unit commitment problem is formulated as the minimization of the performance index, which is the sum of objectives (fuel cost, startup cost) and constraints (minimum up time (MUT), minimum down time (MDT), spinning reserve). Solution methodology and Simulation Results are provided for a 10-generator unit commitment problem for 24 h duration.

Multiagent based differential evolution approach to optimal power flow

This paper proposes a new differential evolution approach named as multiagent based differential evolution (MADE) based on multiagent systems, for solving optimal power flow problem with non-smooth and non-convex generator fuel cost curves. This method integrates multiagent systems (MAS) and differential evolution (DE) algorithm. An agent in MADE represents an individual to DE and a candidate solution to the optimization problem. All agents live in a lattice like environment, with each agent fixed on a lattice point. In order to obtain optimal solution quickly, each agent competes and cooperates with its neighbors and it can also use knowledge. Making use of these agent-agent interaction and DE mechanism, MADE realizes the purpose of minimizing the value of objective function. MADE applied to optimal power flow is evaluated on 6 bus system and IEEE 30 bus system with different generator characteristics. Simulation results show that the proposed method converges to better solutions much faster than earlier reported approaches.

Distribution system load flow using object-oriented methodology

Distribution system has been analyzed in this paper using object-oriented approach. The important contribution of this paper is the development of software objects for various distribution system components in such a way that they can be reused in most of the distribution system analysis programs. The design, proposed in this paper, is used for developing load flow analysis program. Object-oriented design replicates the physical system structure exactly in the software. The extensibility of the object-oriented design is exploited to extend the radial load flow analysis module for performing the load flow analysis of weakly meshed system by deriving few specialized objects from the fundamental objects used for radial load flow. Modeled objects are implemented in C++, an object-oriented programming language, and tested with various test systems. The results obtained for 69-bus radial system and 33-bus weakly meshed system are provided. This design is being extended for developing load flow analysis module for 3-phase unbalanced distribution system and distribution system with dispersed generations.

Computationally Efficient Wavelet-Transform-Based Digital Directional Protection for Busbars

This paper proposes a novel wavelet-transform-based directional algorithm for busbar protection. The algorithm decomposes the current and voltage signals into their first-level details, which consist of frequencies in 500- to 1000-Hz bandwidth, for generating directional signals. A high level of computational efficiency is achieved compared to the other wavelet-transform-based algorithms proposed, since only the high-frequency details at the first level are employed in this algorithm. The validity of this method was exhaustively tested by simulating various types of faults on a substation modeled in the alternative transients program/electromagnetic transients program. The algorithm correctly discriminated between bus faults, various types of external faults, and transformer energization even in the presence of current-transformer saturation. This paper also provides the design details of the algorithm using field-programmable gate array technology.