Nalin B. Dev Choudhury

Transaction based power flow solution and transmission loss allocation using neural network

Recovering transmission loss cost accurately and transparently is an important challenge in deregulated power market. Though a generally acceptable method for transmission loss allocation is yet to be found out, proportional allocation technique has some popularity due to its uniqueness in the sense that it can neither be proved nor disproved. This method however is not applicable to transaction based power system structure, due to lack of a power flow tool for transaction based operation of power system. This paper proposes an application of proportional sharing principle to transmission loss allocation for transaction based power system. The unavailability of a power flow method for transaction based power system operation is addressed by framing a neural network. The neural network allocates losses to transactions and also generates the bus voltage magnitudes. Thus, it serves the purpose of both loss allocation and transaction based power flow tool.

Prioritization of load points in distribution system considering multiple load types using fuzzy theory

The power shortages and/or outages in the distribution system enables the need of load shedding or curtailment, where the important loads are given high priority. This paper presents a novel method to solve the load point prioritization problem. The load points in the distribution system contains different types of loads and each load type has certain importance over other load type. The inclusion of load types in the load point ranking, increases the complexity in the problem. The proposed ranking method based on the fuzzy theory resolves this complexity and evaluates the weights of load points and thereupon ranking. The proposed method is validated on a test system considering a natural disaster situation.

Available Transfer Capability enhancement in constrained network conditions using TCSC

FACTS devices have been successfully used for many years in order to enhance the stability and loadability of transmission network. Available transfer Capability (ATC) is a measure of the remaining power transfer capability of the transmission network for further transactions. ATC accurately reflects the physical realities of the transmission network, all system conditions, uses, and limits in a consistent manner. It depends on other parameters namely Total Transfer Capability (TTC), Capacity Benefit Margin (CBM), Transmission Reliability Margin (TRM), and Existing Transmission Commitments (ETC) that are described in this study thoroughly. This paper investigates the optimized use of FACTS devices and mainly Thyristor Controlled Series Capacitor (TCSC) to improve ATC and maximize TTC considering thermal limit and voltage limit of the transmission lines including the line outages in the power system without any power system physical constraints violations. This study also uses the repeated power flow (RPF) algorithm for the real-time calculation of the transfer capability. The case study has been implemented on modified IEEE 24-bus reliability test system.

Fuzzy Based Approach for Restoration of Distribution System During Post Natural Disasters

Distribution systems are inevitably vulnerable to natural disasters, which causes multiple damages within or outside the system. The disruption of supply demands microgrid formation, where the objective is to maximize the restoration of critical loads. The complete restoration requires repair of damaged regions which brings the need for an efficient crew selection, repair time estimation, and crew dispatch. Ranking of load points and location are important considerations for strategic placement of distributed generation units. Prioritization of damaged regions is required for efficient crew dispatch. These ranking depends on multiple criteria based on subjective opinions of the experts. However, the existing methods fail to take account of the same. This paper presents fuzzy approaches which fill the gap present in the existing methods by explaining the theoretical solutions to ranking of load points, locations, crew selection, estimation of repair times, and prioritization of the damaged regions.

Power transformer failure analysis using interval type-2 fuzzy set theory based fault tree analysis

Reliable power supply depends on proper equipment functioning. Power transformer keeps up voltage and power level of the system. Power transformer failure is caused by insulation failure, low voltage bushing, frequent tap change, tank leakage etc. These causes are analysed with the help of probability of occurrence of each event. The value of probability is assigned to fault tree analysis (FTA). The uncertainties and the randomness of reasons of power failure are handled by fuzzy numbers. Normal distribution concept is applied to deal with fuzzy numbers. Interval type 2 fuzzy system (IT2FS) fuzzifies failure probability and uncertainty of occurrence of failure events more accurately than type 1 fuzz system (T1FS) and conventional FTA do. Thus IT2FS helps to ascertain the chances of failure of power transformer in different conditions.