-This paper presents a new method of Fuzzy Particle Swarm Optimization (FPSO)-based Congestion Management (CM) by optimal rescheduling of active powers of generators. In the proposed method, generators are selected based on their sensitivity to the congested line for efficient utilization. The task of optimally rescheduling the active powers of the participating generators to reduce congestion in the transmission line is attempted by FPSO, Fitness Distance Ratio PSO (FDR-PSO), and conventional PSO. The FPSO and FDR-PSO algorithms are tested on the IEEE 30-bus and Practical Indian 75-bus systems, after which the results are compared with conventional PSO to determine the effectiveness of CM. Compared with FDR-PSO and PSO, FPSO can better perform the optimal rescheduling of generators to relieve congestion in the transmission line.
In this paper Dynamic ATC has been calculated using energy function based Potential Energy Boundary Surface (PEBS) method. For the effective use of power system under the deregulated environment, it is important to make a fast and accurate evaluation of the maximum available transfer capability (ATC). Transient stability assessment by time domain simulation method is a time consuming process. A novel Dynamic contingency screening method is discussed and critical contingencies are selected for the computation of Dynamic ATC in order to reduce the computational time. The information about the ATC is to be continuously updated in real-time and made available to the market participants through Open Access Same time Information System (OASIS). On the basis of ATC, Independent System Operator (ISO) evaluates the transaction. Thus the ATC must be computed fast and accurately. In this paper ATC has been computed for real time applications using two different neural networks viz., i) Back Propagation Algorithm (BPA) and ii) Radial Basis Function (RBF) Neural Network These two methods are tested on WSCC 3 Machine 9 bus system and New England 10 machine 39 bus system and results are compared with the conventional energy function based PEBS method.
-In this paper, a novel dynamic available transfer capability (DATC) has been computed for real time applications using three different intelligent techniques viz. i) back propagation algorithm (BPA), ii) radial basis function (RBF), and iii) adaptive neuro fuzzy inference system (ANFIS) for the first time. The conventional method of DATC is tedious and time consuming. DATC is concerned with calculating the maximum increase in point to point transfer such that the transient response remains stable and viable. The ATC information is to be continuously updated in real time and made available to market participants through an internet based Open Access Same time Information System (OASIS). The independent system operator (ISO) evaluates the transaction in real time on the basis of DATC information. The dynamic contingency screening method [1] has been utilized and critical contingencies are selected for the computation of DATC using the energy function based potential energy boundary surface (PEBS) method. The PEBS based DATC has been utilized to generate patterns for the intelligent techniques. The three different intelligent methods are tested on New England 68-bus 16 machine and 39-bus 10 machine systems and results are compared with the conventional PEBS method.
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