Abstract
The paper presents a new vision on the energy consumption management in the case of the small and medium enterprises (SMEs), integrated into an advanced decision support platform, with technical and economic benefits on increasing the energy efficiency, with four modules for database management, profiling, forecasting, and production scheduling. Inside each module, artificial intelligence and data mining techniques were proposed to remove the uncertainties regarding the dynamic of technological flows. Thus, the data management module includes the data mining techniques, that extract the technical details on the energy consumption needed in the development of production scheduling strategies, the profiling module uses an original approach based on clustering techniques to determine the typical energy consumption profiles required in the optimal planning of the activities, the forecasting module contains a new approach based on an expert system to forecast the total energy consumption of the SMEs, and production scheduling module integrates a heuristic optimization method to obtain the optimal solutions in flattening the energy consumption profile. The testing was done for a small enterprise from Romania, belonging to the domain of trade and repair of vehicles. The obtained results highlighted the advantages of the proposed decision support platform on the decrease in the intensity of energy consumption per unit of product, reduction of the purchase costs, and modification of the impact for which energy bills have on the operational costs.
Highlights
Combating climate change is one of the five main themes of the Europe 2020 comprehensive strategy [1], adopted by the European Council in 2010, for smart, sustainable, and inclusive growth.The specific targets of the strategy consider that by 2020, greenhouse gas emissions to be reduced by20%, 20% of electricity to be covered from renewable sources, and energy efficiency to be improved by 20%
small and medium enterprises (SMEs) have needed software products to monitor and control the consumption and to identify solutions that allow the adoption of measures to increase energy efficiency
(ii) The profiling module integrates an original approach based on clustering techniques to determine the typical energy consumption profiles (TECPs) assigned to different activities necessary for establishing the type of tariffs that will lead to the reduction of energy bills and optimal planning of the activities
Summary
Combating climate change is one of the five main themes of the Europe 2020 comprehensive strategy [1], adopted by the European Council in 2010, for smart, sustainable, and inclusive growth. A decision support platform is proposed, having the modules with characteristics that differentiate it and offer more advantages compared to the other approaches which treated the energy management at the SMEs, whatever the industrial activity branch: The data management module is based on the data mining technique that extracts the technical details on energy consumptions used to develop production scheduling strategies. It allows the analysis of large size databases regarding the daily, monthly, and yearly energy consumption or technical and operating characteristics for equipment and installations.
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