3 research outputs found

    Provision for reactive power market in the reactive power control groups

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    Implementation of electricity market is facing many challenges in developing countries like India. The market for real power is gaining more interest of investors while the market for reactive power has less incentive due to its technical limitation. But reactive power is of importance for system security and improving the line transmission capacity. The system operator is therefore willing to buy reactive power from different sources to ensure the necessary potential at each node of the system. The paper discusses an approach for market for reactive power in reactive power control groups using the concept of electrical distances. The approach does not involve any optimal power flow (OPF) algorithm for avoiding the complexity and non-convergence for large systems but discusses a simple and economical market provision for reactive power. The approach is illustrated with the transmission system of Uttar Pradesh Power Corporation Limited (UPPCL)

    Combining forecasts in short term load forecasting: Empirical analysis and identification of robust forecaster

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    We present an empirical analysis to show that combination of short term load forecasts leads to better accuracy. We also discuss other aspects of combination, i.e., distribution of weights, effect of variation in the historical window and distribution of forecast errors. The distribution of forecast errors is analyzed in order to get a robust forecast. We define a robust forecaster as one which has consistency in forecast accuracy, lesser shocks (outliers) and lower standard deviation in the distribution of forecast errors. We propose a composite ranking (CRank) scheme based on a composite score which considers three performance measures-standard deviation, kurtosis of distribution of forecast errors and accuracy of forecasts. The CRank helps in identification of a robust forecasts given a choice of individual and combined forecaster. The empirical analysis has been done with the real life data sets of two distribution companies in India
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