Anil Pahwa

Optimal selection of capacitors for radial distribution systems using a genetic algorithm

In this paper, a new design methodology for determining the size, location, type and number of capacitors to be placed on a radial distribution system is presented. The objective is to minimize the peak power losses and the energy losses in the distribution system considering the capacitor cost. A sensitivity analysis based method is used to select the candidate locations for the capacitors. A new optimization method using a genetic algorithm is proposed to determine the optimal selection of capacitors. Test results have been presented along with the discussion of the algorithm. >

An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration

This paper proposes a hybrid algorithm based on artificial immune systems and ant colony optimization for distribution system reconfiguration, which is formulated as a multi-objective optimization problem. The algorithm maintains a population of candidate solutions called antibodies. The search space is explored by means of the hypermutation operator that perturbs existing antibodies to produce new ones. A table of pheromones is used to reinforce better edges during hypermutation. An added innovation is the use of the pheromones to obtain quick solutions to restore the distribution system under contingency situations. The hybrid approach has been successfully implemented on two test networks. The results obtained demonstrate the efficacy of the algorithm.

Voltage/VAR Control in Distribution Networks via Reactive Power Injection Through Distributed Generators

This paper demonstrates how reactive power injection from distributed generators can be used to mitigate the voltage/VAR control problem of a distribution network. Firstly, power flow equations are formulated with arbitrarily located distributed generators in the network. Since reactive power injection is limited by economic viability and power electronics interface, we formulate voltage/VAR control as a constrained optimization problem. The formulation aims to minimize the combined reactive power injection by distributed generators, with constraints on: 1) power flow equations; 2) voltage regulation; 3) phase imbalance correction; and 4) maximum and minimum reactive power injection. The formulation is a nonconvex problem thereby making the search for an optimal solution extremely complex. So, a suboptimal approach is proposed based on methods of sequential convex programming (SCP). Comparing our suboptimal approach with the optimal solution obtained from branch and bound method, we show the trade-off in quality of our solution with runtime. We also validate our approach on the IEEE 123 node test feeder and illustrate the efficacy of using distributed generators as distributed reactive power resource.

Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method

This paper presents a multi-objective algorithm to solve stochastic distribution feeder reconfiguration (SDFR) problem for systems with distributed wind power generation (WPG) and fuel cells (FC). The four objective functions investigated are 1) the total electrical energy losses, 2) the cost of electrical energy generated, 3) the total emissions produced, and 4) the bus voltage deviation. A probabilistic power flow based on the point estimate method (PEM) is employed to include uncertainty in the WPG output and load demand, concurrently. Different wind penetration strategies are examined to capture all economical, operational and environmental aspects of the problem. An interactive fuzzy satisfying optimization algorithm based on adaptive particle swarm optimization (APSO) is employed to determine the optimal plan under different conditions. The proposed method is applied to Taiwan Power system and the results are validated in terms of efficiency and accuracy.

Performance evaluation of electric distribution utilities based on data envelopment analysis

In this paper, a method for benchmarking performance of electric distribution utilities based on data envelopment analysis (DEA) is presented. Basic theory of DEA is followed by case studies addressing performance analysis of the 50 largest (based on MWh sales) electric distribution utilities in the U.S. The results include performance efficiency, gaps in inputs and outputs of inefficient utilities, sensitivity-based classification of utilities, and a gap report. Also, peer-to-peer comparison of inefficient and efficient utilities is provided. Based on these results, inefficient utilities can develop strategic plan to improve perfortnance.

An analytical approach for step-by-step restoration of distribution systems following extended outages

Loss of diversity among loads may cause cold load pickup problems after an extended outage in distribution systems. Thermostatically-controlled devices such as air-conditioners, heaters, heat pumps, water heaters etc. become the largest portion of load during restoration. In this paper, an analytical approach for restoration of distribution systems during cold load pickup is presented. A delayed exponential model is used to represent the load during cold load pickup. A thermodynamic model of a transformer is used to determine the loading limits for this type of load. Whenever loading limits are reached, sections are restored step-by-step. In step-by-step restoration, the sequence of sections restored plays an important role in total restoration time. An optimal restoration sequence of different sections of the distribution system is determined for minimum total restoration time as well as minimum customer interruption duration. >

What future distribution engineers need to learn

It is getting increasingly clear that electric distribution systems are undergoing rapid changes due to deregulation, the penetration of distributed generation and power electronics technologies, and the adoption of efficient computation, communications, and control mechanisms. The primary goal of this paper is to recommend the development of a new two-course sequence to reflect the radical changes occurring or expected to happen in the future.

Effective Wind Farm Sizing Method for Weak Power Systems Using Critical Modes of Voltage Instability

Current methods for determining wind farm maximum sizes which do not consider voltage stability margins (VSMs) may result in reducing the overall levels of wind generation in a system. In this paper, new methods have been developed to increase wind penetration level by placing new wind generation at voltage stability strong wind injection buses. Placing new generation at these buses has the least impact on VSMs not only in the vicinity of new wind generation, but also throughout the power system. The new methods provide a comprehensive methodology for the identification of system weaknesses for each wind penetration level. The new methods incorporate modal analysis as well as traditional voltage stability methods (Q-V curves) in sizing and placing new wind farms. The study shows that the location of SVCs is also key to increasing wind penetration. Wind penetration can be increased when placing SVCs at the weakest buses in the system instead of only locating them at the wind generation buses.

Multi-level ant colony algorithm for optimal placement of capacitors in distribution systems

An ant colony algorithm is proposed to determine the optimal locations and ratings of capacitors in a distribution network for reactive power compensation. The approach is multilevel. Two separate tables of pheromones are maintained by the algorithm. Ants generate solution stochastically, based on these pheromone tables. The pheromone tables are updated periodically, so that pheromones accrue more along better solutions. Results obtained by the proposed algorithm have been compared with earlier schemes. We conclude that the proposed approach is an effective approach for optimally placing capacitors in a distribution system.

Intelligent Dispatch for Distributed Renewable Resources

Time of use (TOU) pricing is considered by many to be a key part of creating a more energy-efficient and renewable-energy-friendly grid. TOU pricing is also an integral part of the smart grid and is already available to customers of some electric utilities. With TOU pricing becoming a reality, intelligent dispatching systems that utilize energy storage devices (ESDs) to maximize the use of renewable resources, such as energy produced by small, customer owned wind generators and roof-top solar generators, and grid energy while determining the most economic dispatch schedule could play an important role for both the customer and the utility. The purpose of this work is to create an algorithm upon which these dispatching systems can be based. The details of one proposed algorithm are presented. Several case studies are presented to show the effectiveness of the algorithm from both a technical standpoint and an economic standpoint. The case studies show that while the algorithm developed is successful from a technical standpoint, the high cost of energy storage at this time limits its widespread deployment.