Development and Validation of a Load Flow Based Scheme for Optimum Placing and Quantifying of Distributed Generation for Alleviation of Congestion in Interconnected Power Systems

Abstract

The energy supply entities widely adopt distributed generators (DG) to meet the additional power requirement due to scheduled or unscheduled interruptions. The expansion of transmission and distribution systems via the inclusion of loads and generators and the occurrence of line interruptions are significant causes of congestion of transmission lines in interconnected systems. The management and alleviation of congested lines is a primary requirement for a power system network’s reliable and efficient operation. The researchers investigated the potential scope of distributed generation (DG) to alleviate the congested branches in interconnected transmission systems. The development of a reliable scheme to arrive at the best location and size of local generators for alleviating congestion deserves considerable importance. This paper attempted to develop a simple and reliable strategy for the optimum placement and sizing of DGs to be integrated with a transmission line system of DGs for congestion relief in transmission lines by analyzing power flow solutions. This research work considered the 14-bus system of IEEE for the preliminary analysis to identify the parameters employed for assessing the severity of line congestion and the best placement and sizing of DGs for congestion relief. This work analyzed power flows by load flow algorithms using ETAP software in the 14-bus IEEE system for different line outage cases. The analysis of power flow solutions of the 14-bus system of IEEE revealed that the percentage violation of the system can be regarded as an essential parameter to assess the extent of congestion in an interconnected system. A detailed power flow analysis of the system with various capacities of DG integration at several buses in the system revealed the application of two indices, namely the index of severity (SI) and sensitivity factor (SF), for optimum placement with the best capacity of DGs for congestion alleviation in the system. This work proposed a reliable algorithm for the best siting and sizing of DGs for congestion relief by using the identified indices. The proposed methodology is system indices allied load flow-based algorithm. This work produced a fast simulation solution without any mismatch through this developed scheme. The approximations linked with the algorithm were very minute, resulting in comprehensive bests instead of inexact limited bests with less simulation time and more convergence probability and availing the benefits of the mathematical approach. The work investigated the feasibility of the proposed methodology for optimum placing and quantifying DGs for congestion solutions for a practical interconnected bus system in the supply entity of the Kerala grid with many buses. Any transmission system operator can adopt this method in similar connected systems anywhere. The proposed algorithm determined the most severe cases of congestion and the optimum site and size of DGs for managing congested feeders in the grid system. The analysis of the losses in the system for different cases of DG penetration by load flow analysis validated the suitability of the obtained results.

Study on Data Center Network Topologies for Monitoring Data using Edge/Fog Computing

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State-Space Load Flow Calculation of an Energy System with Sector-Coupling Technologies

“…Instead of relying on current state-of-the-art load-flow analysis tools and methods, e.g., the current iteration (Gauss-Seidel) or the Newton-Raphson approaches presented in [11][12][13], which are applied in varying research topics, as illustrated by contributions. e.g., [14][15][16][17], a novel load-flow calculation method, based on a statespace approach, is introduced and applied to calculate the system-defining flows. The aforementioned novel algorithm differs from the established state-of-the-art algorithms and uses the mathematical state-space representation to directly calculate a system's load flow, as shown by the overview given by Blenk in [18].…”

“…The constraints that must be adhered to by the optimization layer are characterized by the ESS fundamental parameters, including the minimum and maximum charge and discharge currents I min,n , I max,n (typically defined by the C-rate) and the charging boundaries C min,n , C rated,n . Accordingly, the ESS power values specified by the optimization, must comply with ( 15), (16).…”