Price: 0
Number of applications: 11
07.10.26 (inclusive)
by agreement of the parties
Idea
ICT tasks
Electric power industry
ML
Software/ IS
When working in the wholesale electricity market of the Republic of Kazakhstan, market participants are required to generate and provide hourly planned volumes of electricity production and/or consumption in advance. At the same time, the actual values almost always differ from the approved daily schedule due to changes in production load, weather conditions, technological modes, emergencies, seasonality and other factors. The resulting difference between the PLAN and the FACT creates an hourly imbalance, which is subject to financial settlement in the Balancing Electric Energy Market. The higher the absolute value of the deviation, the higher the potential financial costs of the enterprise. At the moment, the formation of planned values in many cases is based mainly on historical consumption, manual adjustments by specialists, production plans and expert assessment. This approach has a number of limitations: it is not always able to take into account a large number of factors simultaneously, respond quickly to changes in the operating mode of an object, and identify complex dependencies in historical data.
The implementation of the forecasting system should ensure an increase in the accuracy of hourly planning of production and/or consumption of electric energy and reduce deviations between the PLAN and the FACT. The main expected effect is a reduction in the volume and cost of imbalances in the Balancing Electricity Market due to more accurate formation of the daily schedule and prompt forecast adjustments. Expected project results: reduction of average absolute hourly deviations PLAN / FACT; reducing the number of hours with critical deviations from the approved schedule; reduction of financial costs for resolving imbalances in the BDT; improving the accuracy of forecasting consumption/output for the day ahead; identifying hours and periods with an increased risk of imbalance; automating hourly forecast preparation and reducing the influence of the human factor; reducing the time of specialists for the formation and adjustment of daily schedules; the ability to take into account weather, calendar, production and technological factors in a single model; automatic improvement of forecasting quality as new evidence accumulates.; increase planning transparency by monitoring PLAN/FORECAST / FACT/DEVIATION/cost of imbalance indicators; formation of a base for further optimization of the purchase and sale of electricity on the wholesale market.
Daniyar Dzhemogulov
Purpose and description of task (project)
The aim of the project is to develop and implement a forecasting system for hourly production and/or consumption of electric energy to minimize deviations between planned and actual values when operating in the wholesale electricity market of the Republic of Kazakhstan. As part of the project, it is planned to create an analytical solution based on machine learning methods, statistical forecasting and optimization algorithms, which will generate the most accurate hourly forecast of energy consumption/output for the day ahead and, if necessary, update it as new data becomes available. The system must take into account historical hourly data, calendar factors, seasonality, day of the week, holidays and weekends, weather conditions, temperature dependencies, production schedules, technological modes of facilities, scheduled shutdowns, repairs, emergency events and other factors affecting the actual consumption or production of electricity. The main objective is to reduce the magnitude and frequency of hourly PLAN/FACT deviations, which lead to imbalances and financial settlement in the Balancing Electricity Market. The result of the project should be a decision support system that will allow: automatically generate a forecast for each hour of the estimated day; determine the expected deviation of the actual volume from the stated schedule; identify hours with an increased risk of significant imbalance; calculate the recommended target value, taking into account the projected consumption/output; compare several forecasting models and automatically select the most accurate one; implement regular retraining of models based on new evidence; display the indicators PLAN / FORECAST / FACT / DEVIATION in the analytical interface; evaluate the accuracy of forecasting and the potential economic effect of reducing imbalances. The key business effect of the project is to reduce financial costs associated with deviations in the BRE, increase the accuracy of daily planning and automate the process of generating hourly orders in the wholesale electricity market.
Whatsapp
