A Heuristic Method for Short Term Load Forecasting Using Historical Data
Keywords:
HM-Holt's Method, CACM-Chow's Adaptive Control Method, BOPAM-Brown's One- Parameter Adaptive Method, RTL-Real time load Mean Absolute Percentage
Abstract
Load forecasting plays an important role in power system planning and operation. In the present complex power system network under deregulated regime, power generating companies must be able to forecast their system demand and the corresponding price in order to make appropriate market decisions. Therefore, load forecasting, specially the short-term load forecasting (STLF) plays an important role for energy efficient and reliable operation of a power system. It provides input data for many operational functions of power systems such as unit commitment, economic dispatch, and optimal power flow and security assessment. This paper proposes a new and simple technique to calculate short term load forecasting using historical data and applied it to the Damodar Valley Corporation (DVC) grid operating under Eastern Grid (ERLDC-Eastern Regional Load Despatch Centre), India. This gives load forecasts half an hour in advance. The forecast error i.e. difference between calculated forecast load and real time load is a measure of the accuracy of the system, is found to be lower than other existing techniques like Holt's Method, Chow's Adaptive Control Method, Brown's One-Parameter Adaptive Method.
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Published
2011-07-15
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Copyright (c) 2011 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.