M. Tripathy

Bacteria Foraging-Based Solution to Optimize Both Real Power Loss and Voltage Stability Limit

Summary form only given. Optimal location and control of an unified power flow controller (UPFC) along with transformer taps are tuned with a view to simultaneously optimize the real power losses and voltage stability limit (VSL) of a mesh power network. This issue is formulated as a non-linear equality and inequality constrained optimization problem with an objective function incorporating both the real power loss and VSL. A new evolutionary algorithm known as bacteria foraging is applied for solving the multi-objective multi-variable problem, with the UPFC location, its series injected voltage and the transformer tap positions as the variables. For a single objective of only real power loss, the same problem is also solved with interior point successive linearization program (IPSLP) technique using the LINPROG command of MATLAB. A comparison between the two suggests the superiority of the proposed algorithm. A cost effectiveness analysis of UPFC installation vis-a-vis loss reduction is carried out to establish the benefit of investment in an UPFC.

Transmission loss reduction based on FACTS and bacteria foraging algorithm

An optimal location and parameters of an UPFC along with values of OLTC taps are tuned with a view to minimize the real power losses of a mesh power network. This issue is formulated as a non-linear equality and inequality constrained optimization problem with an objective function incorporating power loss. A new evolutionary algorithm known as Bacteria Foraging is applied for solving, the optimum location and the amount of series injected voltage for the UPFC, and the best values of the taps present in the system. The same problem is also solved with Interior Point Successive Linearization technique using the LINPROG command of MATLAB. A comparison between the two suggests the superiority of the proposed algorithm.

Improving Stability of a DFIG-Based Wind Power System With Tuned Damping Controller

This paper focuses on the implementation of a damping controller for the doubly fed induction generator (DFIG) system. Coordinated tuning of the damping controller to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The effect of the tuned damping controller on converter ratings of the DFIG system is also investigated. The results of both eigenvalue analysis and the time-domain simulation studies are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The improvement of the fault ride-through capability of the system is also demonstrated.

A hybrid adaptive-bacterial-foraging and feedback linearization scheme based D-STATCOM

This paper investigates application of a multivariable control technique to the multi-input multi-output (MIMO) nonlinear model of a distribution static synchronous compensator (D-STATCOM). The proposed controller design is based on a feedback linearization scheme, which is made adaptable by hybridizing the behavior of E.coli bacteria during foraging. Its prime goal is the coordinated control of AC and DC voltage for a D-STATCOM installed in a power distribution system. First, the nonlinear mathematical model of D-STATCOM along with the distribution system is derived. Then, by using input-output feedback linearization, a state feedback control law is obtained by pole placement. The coefficients used for placing the poles at desired location are made adaptable in an online fashion according to operating condition thorough foraging strategy of E.coli bacteria. Digital computer simulations on the complete system for various types of loads and/or disturbances evaluate the efficacy of the control strategy. The comparative study of these results with those obtained in feedback linearization scheme with constant coefficient pole placement technique establishes the elegance of this new adaptable control scheme.

Optimizing Voltage Stability Limit and Real Power Loss in a Large Power System using Bacteria Foraging

An optimal allocation of transformer taps and reactive power injections at some selected locations is carried out with a view to maximize the voltage stability limit (VSL) of a multi machine power system, simultaneously with the objective of real power loss minimization. This issue is formulated as a non-linear equality and inequality constrained multi-objective optimization problem. A new evolutionary algorithm known as bacteria foraging is applied for solving, first the optimum settings of the transformer taps only and then with selected reactive power injections at some buses, so that the power system operates more securely achieving both the objectives.

Optimal reactive power compensation for improvement of steady state voltage stability limit under stressed system condition using BF algorithm

Power system operation under stressed condition, can lead to voltage instability problem if subjected to additional load increase or contingency. Suitable amount of reactive power compensation at proper location in the system improves the loadability. This work aims at obtaining optimal size and location of compensation in the 39- bus New England system with the help of Bacteria Foraging and Genetic algorithms. To reduce the computational time the work first, identifies weak candidate buses in the system, and then picks only few of them to take part in the optimization. The objective function is based on a recently proposed voltage stability index which takes into account the local equivalent network, which is a simpler and faster approach than the conventional CPF algorithm. BFA has been found to give better results compared to GA.

Estimating wind speed probability distribution based on measured data at Burla in Odisha, India

ABSTRACT In this work, the wind speed probability distribution is estimated for Burla location in the state of Odisha in the east coast of India. For this purpose, 10 min averaged wind speed data collected over one year period at Burla is utilized. Specifically, Weibull, Gamma, Lognormal, Inverse Gaussian distributions; mixture distributions such as Weibull-Weibull, Gamma-Weibull, Normal-Weibull, and Normal-Normal are examined to evaluate their suitability to represent the measured wind speed. The non-parametric kernel density method is also used to represent the measured wind speed wherever the parametric distributions are not suitable. Chi-square test and Kolmogorov-Smirnov goodness-of-fit tests are used to evaluate the suitability of each of the above distributions.

Emission reduction estimation for wind integrated smart grids

In the face of energy crisis and environmental impact of conventional power plants, renewable energy sources come to the rescue. The international flexible mechanisms like Clean Development Mechanism (CDM) evaluate sustainable development contribution and hence emission reduction of the energy projects for granting financial assistance. Continuous and expanded growth of renewable requires making full use of smart grids. The present study illustrates a methodology to estimate emission reduction from a wind energy project prior to integration with smart grid thus providing a benchmark for comparison for further power system studies. A suitable location is selected and appropriate probability distribution if fitted for the wind regime. Turbine Performance Index is used to rank the turbines. Finally, emission reduction is estimated using energy capture estimates and emission factor of the power system.

Impacts of wind generators penetration in power systems towards voltage stability

The power systems have become complex in current years as the existing transmission lines operate closer to their limits, use flexible AC transmission system devices (FACTS), and also latest types of generators that have more sporadic characteristics and lower inertial response, such as wind generators are being penetrated. This changing nature of a power system has significant effect on its steady state voltage stability limit (SSVSL). This work presents some analyses of this changing environment of power systems and their behaviours to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this work addresses some general concerns towards high compensations in different grid topologies. The studies in this paper are conducted on the New England power system model under both small and large disturbances. From the analyses, it can be accomplished that high compensation can improve the security limits (SL) under certain operating situation, as well as contingencies

A novel approach for load margin improvement with optimal location and size of static capacitor using BFO algorithm

Power systems are forced to operate under stressed condition because of continuous increase in load as well as constraints of network expansion and generations. This can lead to voltage instability when it faces further load increase or any contingency in the form of line outage or generator outage. In order to avoid voltage instability VAR compensating devices are employed. These are at optimal location and of optimal size which improve the load margin. This work aims at obtaining optimal size as well as location of compensation in the 39-bus New England system with the help of Bacteria Foraging optimisation and Genetic algorithms. To reduce the computational time the work identifies weak candidate buses in the system, and then picks only two of them to take part in the optimization. The objective function is based on a recently proposed voltage stability index which takes into account the weighted average sensitivity index is a simpler and faster approach than the conventional CPF algorithm. BFA has been found to give better results compared to GA.