An Interactive Decision Support System for Energy Management in Process Industry

Industrial energy accounts for roughly one-third of total global energy consumption and is expected to continue with a similar share in the foreseeable future, therefore the efficient use of energy and energy saving are important issues for the industrial sectors. Energy Efficiency EE is a crucial factor for energy cost-benefits and waste reduction also environmental management, and can be improved by different approaches. Especially in this study the energy saving through management system will be illustrated. EE is achieved by use of an energy management system which presents various strategies, tools, methods, technologies, and effective measures to face energy saving and consumption issues, that also includes energy audits, monitoring, control and continuous improvement of the system. In particular in this work energy saving through maintenance (corrective and preventive) and operative procedures were addressed. Maintenance operations are fundamental in granting machineries and processes energy saving, given the capability of optimising them thanks to the predictive models. The major challenge of maintenance optimization is to implement a maintenance strategy, which maximizes availability and efficiency of the equipment, controls the rate of equipment deterioration, ensures the safe and environmentally friendly operation, and minimizes the total cost of the operation which means the both production and energy cost. In this work, an energy efficiency analysis model was developed formed by integration of a deterministic and probabilistic model of the system, based on a balance of cost/benefits, to optimize maintenance interventions and operative procedures as the first aim of maximizing energy efficiency. In particular, as an element of novelty with respect to literature models, the maintenance influence has been explicitly modeled and used as an optimization parameter. The decision making model and data analysing were shown through application to a case study in an industrial production process in Bitumtec Ltd. plant, which produces bituminous materials for road paving. The motor-driven equipment accounts for approximately 60% of manufacturing final electricity use worldwide. A major barrier to effective policymaking, and to more global acceptance of the energy efficiency potential in industrial motor systems, is the lack of a transparent methodology for quantifying the magnitude and cost-effectiveness of these energy savings. Therefore the power consumption was analyzed, as an example, for the most critical system (the greater energy consumption system) or the three phases electric motor system (160 kW) “Siefer” which drives the homogenization mill during production. Bottom-up energy efficiency supply curve models is used to estimate the cost-effective electricity efficiency potentials, also CO2 emission reduction, for the motor system. Using a combination of expert opinions and available data, from our selected industrial case study, there was introduced an analysis approach where is used the concept of a “conservation supply curve CSC” to capture the cost effective as well as the technical potential for energy efficiency. The curve shows the energy conservation potential as a function of the marginal Cost of Conserved Energy. This approach is explained in details; further the results were illustrated and discussed. The first step of this study was a literature review to develop a base line of information, through of research in the field of energy management systems, industrial energy efficiency technologies. That included general review of energy saving models, also optimization of energy consumption in industrial production process. Because of the importance of the maintenance activities and reliability of the systems, also was reviewed maintenance optimization models and their impacts on energy cost-effectiveness, productivity benefits and environments. A part of these studies are introduced in this work and illustrated as the theoretical parts. Analysis has been emphasized, the importance of optimizing maintenance activities and operating procedures to increase the performance of the system. Energy efficiency was evaluated for three different base case scenarios; Low, Medium and High with their related potential energy recovery, performance and environmental benefits. Maximizing efficiency of the system that is our goal is achieved through the use of this model, which also based on analysis of historical data, expert inputs and analysis of the economic impacts that was discussed and demonstrated by the results. In this work the proposed framework with flowing steps are introduced: • Identification of the Most Important System MIS Specially, in this study a motor-driven system in a production process of bituminous materials in Bitumtec Ltd. plant, is addressed. • Identification of the most critical component MCC Particularly, in this study is addressed the electrical motor (160 kWh) that drives homogenization mill “Siefer” during production process of bituminous materials. • Life time and energy consumption data collection and observation, also data related to maintenance activities (corrective and preventive) and failures data collection. • Estimated costs of maintenance and the economic evaluation of maintenance policies (based on balanced cost and risk of inefficiency). • Maintenance optimization (in terms of probability and consequences). • Estimated operating costs of the system. • Analysis of energy efficiency through maintenance optimization and operating procedures, by using of bottom-up energy efficiency supply curve analysis model, where it was introduced; Expert inputs (based on the information of the expert of the system), and data assumption. • Definition of three base case scenarios In this case, were defined three efficiency base case scenarios; low, Medium and High, base case levels with related potential for recovery of electricity. Further, was proposed the related efficiency measures o adequate solutions (cost-effective) to increase the efficiency, based on the maintenance activities, operating procedures and the conditions of the system. • Determination of the impact of these measures on the performance.