Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

Abstract

The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM), which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost of consumed electric power without increasing forecast accuracy of its demand.

Keywords

• mathematical forecast model
• time series models
• consumption graph variation
• electricity market
• price relations forecast