Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/3085
Authors: Anandraj, J. Emmanuel
Issue Date: 2012
Abstract: A load flow solution is an important and basic tool for the analysis of power system, as they carryout for the planning and designing purposes and for daily operation of power system. Deterministic load flow carries out the analysis of the power system without considering the uncertainty in the load demand, outage of generating unit and changes in the network configuration. The Probabilistic load flow takes the uncertain input variables distributed around its mean and the solution is obtained in a range of values with its probability of occurrence. The modernization of power system has increased the number of distributed generation system (DG) connected to distribution network. Most of these DGs are non-conventional, taking environmental conditions into concern. The energy generations of such DGs (Photovoltaic (PV) or Wind energy generators) are uncertain as their prime sources of generation are also uncertain or intermittent. An appropriate analysis must be carried out to check the distribution network operating conditions. In such scenarios Probabilistic Load Flow (PLF) calculations are used to obtain the accurate as well as possible solutions. This report deal with the solution for the load flow problems in distribution network with Photovoltaic DG unit. Suitable models for the prediction of active power produced by PV DG units and the power absorbed by the loads are used to represent the uncertainty of solar energy available and load variation. The proposed model is incorporated in a radial network and the PLF using 2PEM as well as 3PEM schemes of point estimate are carried out and their performance is compared with the Monte-Carlo simulation which is a conventional method of PLF.
Other Identifiers: M.Tech
Research Supervisor/ Guide: Das, Biswarup
Pant, Vinay
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (Electrical Engg)

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