Utilising the Cross Industry Standard Process for Data Mining to reduce uncertainty in the Measurement and Verification of energy savings

This paper investigates the application of Data Mining (DM) to predict baseline energy consumption for the improvement of energy savings estimation accuracy in Measurement and Verification (M&V). M&V is a requirement of a certified energy management system (EnMS). A critical stage of the M&V process is the normalisation of data post Energy Conservation Measure (ECM) to pre-ECM conditions. Traditional M&V approaches utilise simplistic modelling techniques, which dilute the power of the available data. DM enables the true power of the available energy data to be harnessed with complex modelling techniques. The methodology proposed incorporates DM into the M&V process to improve prediction accuracy. The application of multi-variate regression and artificial neural networks to predict compressed air energy consumption in a manufacturing facility is presented. Predictions made using DM were consistently more accurate than those found using traditional approaches when the training period was greater than two months

Комплексна оцінка споживання електроенергії в промисловості

Проаналізовано особливості застосування математичних моделей споживання електроенергії для оцінки ефективності використання енергії на підприємствах, яка передбачає функціонування систем контролю енергоефективності за рахунок зіставлення фактичних енерговитрат з планованими. Визначено, що при аналізі споживання енергоресурсів окремими підрозділами підприємства за кожним фактором підприємства не завжди враховують взаємозв’язок процесів, що відбуваються в різних підрозділах, і, як наслідок, знижується ефективність використання математичних моделей як для прогнозування споживання електроенергії, так і для оцінки ефективності споживання. Враховуючи фактори, що визнані вагомими при визначенні споживання електроенергії окремими підрозділами за даними спостережень відділу головного енергетика (з урахуванням їх взаємного впливу) знайдено рівняння регресії та проведено його оцінку. Встановлено, що використання уточнених математичних моделей із звуженим довірчим інтервалом розширює потенціал енергозбереження підприємства та спонукає до більш детального аналізу, пошуку додаткових контрольованих і неконтрольованих факторів впливу на ефективність споживання електроенергії.The peculiarities of mathematical models’ application of electricity consumption for estimation of energy use efficiency in enterprises which provides operation of energy efficiency control systems by comparing actual energy consumption with planned ones are analyzed. Differentiated unit consumption rates were calculated by the chief power engineer's department of the enterprise based on calculated data received from the energy services of the divisions. These rates were used to identify factors that affect electricity consumption. At the same time, the existing equipment in the workshop, its capacity, load and working time were taken into account to fulfill the given production plan, including account repairs, maintenance and the implementation of energy-saving measures. It is determined that in the analysis of energy consumption by individual divisions of the enterprise for each factor enterprises do not always take into account the interconnection of processes taking place in different departments, and as a result, the effectiveness of using mathematical models for both forecasting electricity consumption and assessing consumption efficiency is reduced. Taking into account the factors that are considered as important in determining the electricity consumption of individual units according to the observations of the Department of Chief Energy (taking into account their mutual influence), the regression equation was found and evaluated. It was established that the use of refined mathematical models with a narrowed confidence interval expands the potential for energy saving of the enterprise and prompts a more detailed analysis, the search for additional controlled and uncontrolled factors of influence on the efficiency of electricity consumption. An analysis of mathematical models of power consumption of the catching workshop and the boiler turbine workshop as the main consumers showed that the factors affecting electricity consumption are uncontrolled. By changing them it is possible to achieve a decrease in electricity consumption, but not an increase in its efficiency. The main disadvantage of mathematical models of electricity consumption used in the enterprise to forecast the volume of electricity consumption and estimate the efficiency of energy use is their additivity for various departments. It resulted in a regression model of electricity consumption to estimate the relationship between the energy consumption value and their defining parameters (coke production, coke gas, steam production, electricity). The estimation of the electricity consumption model, using the coefficient of determination, has done