Journal Paper

Paper Title - LMP Based Optimal Location of DG in Deregulated Environment


Abstract
This dissertation is about determination of optimal location by Locational marginal price In the first part of the dissertation, the focus is to predict LMP values in Day ahead market. To direct market participants to make efficient use of transmission and generation resources, energy for both day-ahead and real-time markets is priced by Locational Marginal Price (LMP). Good LMP forecasting will help market participants make effective decisions when preparing offers and bids and making bilateral contracts. The second part of dissertation is description of DG (definition, advantages etc.)which is a fairly new trend in the electricity market, and deregulated system. distributed generator can be defined as an electric power source connected directly to the distributed network or on the customer side of meter. DG is a feasible alternative for new capacity especially in the competitive electricity market environment and has immense benefit The third part of the dissertation treats the LMP based settlement strategy which is used to determine the amount of money earned from ISO by the energy sellers and paid to ISO by the energy buyers. Thus, depending on different market designs, two different calculation models and corresponding properties on LMP are discussed. The new model achieves more defendable and predictable market clearing results by introducing sensitivity factors such as Generation Shift Factors for congestion and Loss Distribution Factors to explicitly balance the consumed losses in the lossless DC power system model. The models used in this dissertation are IEEE- 30 bus system. Index Terms - Distributed generation, Genetic Algorithm, Locational Marginal Price


Author - Poushali Pal

Citation - Poushali Pal   ,   Poushali Pal " LMP Based Optimal Location of DG in Deregulated Environment " , International Journal of Industrial Electronics and Electrical Engineering , Volume-5,Issue-3  ( Mar, 2017 )

Indexed - Google Scholar


| PDF |
Viewed - 1
| Published on 2017-05-31