دانلود مقاله ISI انگلیسی شماره 29164
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل اقتصادی جایگزین برای بهینه سازی مصرف انرژی در شرکت های تولیدی

عنوان انگلیسی
Economic analysis of alternatives for optimizing energy use in manufacturing companies
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
29164 2013 9 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Economics, Volume 40, November 2013, Pages 146–154

ترجمه کلمات کلیدی
تجزیه و تحلیل اقتصادی - بهینه سازی انرژی - مدل سازی ریاضی -
کلمات کلیدی انگلیسی
Economic analysis, Energy optimization, Mathematical modeling,
پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل اقتصادی جایگزین برای بهینه سازی مصرف انرژی در شرکت های تولیدی

چکیده انگلیسی

The manufacturing companies are one of the main consumers of energy. The increment in global warming and the instability in the petroleum oil market have motivated companies to find alternatives to reduce energy use. In the academic literature several researchers have demonstrated that optimization models can be successfully used to reduce energy use. This research presents the use of an optimization model to identify feasible economic alternatives to reduce energy use. The economic analysis methods used were the payback and the internal rate of return. The optimization model developed in this research was applied and validated using an electronic manufacturing company case study. The results demonstrate that the main variables affecting the economic feasibility of the alternatives are the economic analysis method and the initial implementation costs. Several scenarios were analyzed and the best results show that the manufacturing company could save up to $78,000 in three years if the recommendations based on the optimization model results are implemented

مقدمه انگلیسی

The increase in global temperatures and the volatility of the petroleum oil market share a common factor, energy use. These are two of the principal reasons for governments and manufacturing companies to seek alternatives to reduce energy use. An Environmental Protection Agency (EPA) 2010 in study on CO2 emissions demonstrates that since the Industrial Revolution in the 1700s the concentration of CO2 in the atmosphere has increased by 35% (Climate change — Greenhouse gas emissions, 2010). This study further demonstrates that the principal emitters of CO2 are manufacturing companies. This is one of many problems that companies face today. In addition, the instability in the petroleum market causes increases in the price of fuel thus affecting the energy costs and, therefore, the cost of the manufacturing processes. For these reasons, many companies are considering the use of alternate methods of energy generation to reduce the energy they use. Currently, it is a common practice for manufacturing companies to hire a consulting agency to evaluate alternative energy projects that allow companies to save on energy use with the possibility of risking a considerable investment. However, using external consultants represents an additional investment in which the subsequent benefits are uncertain. The analyses that were examined were based on the investment, economic benefits, and the period of return on investment and included studying the variables related to energy costs, the equipment necessary for the alternatives, and the cost of the appropriate equipment. However, companies also have the option of in-house analyses to identify energy-saving alternatives that use systems and tools for monitoring the energy performance of their equipment. Therefore, manufacturing companies need to evaluate whether any analysis of energy use should be in-house or external by a consulting company. Studies related to energy use show that optimization models are effective tools for reducing energy use in many industries thereby reducing CO2 emissions. These optimization methods are presented in the following literature review. In addition to analyzing alternatives for reducing energy use, an economic analysis has to be considered for the analysis to have an effect on the results. The most commonly used economic analysis methods for this type of problems are the internal rate of return (IRR) and the payback method. The difference between these two economic analysis methods and examples of application will be presented in the literature review. The objective of this study is to analyze the application of optimization models in the process of selecting alternatives to reduce energy use within a manufacturing environment. For this purpose, an optimization algorithm was developed to identify feasible economic alternatives for replacing current equipment with that which reduces energy use in the following areas of the company: offices, production, warehouse, and exterior. Five systems were identified as major energy consumers in manufacturing companies; which are air conditioner, compressed air, lighting, exhaust, and machines. The optimization models presented in this study focus on alternatives for the first three of these five systems: air conditioner, compressed air, and lighting since these systems use most of the energy in a manufacturing facility. The objective function of the optimization models is to maximize the net economic benefits by saving on energy use after implementation of the identified alternatives. Constraints associated with the systems in the analyzed areas (i.e. offices, production, warehouse, and exterior) were considered in the model. Also, constraints related to established limits of energy demand were included. This optimization model represents an efficient and cost effective tool for companies to internally monitor alternatives to reduce their energy use. This paper is organized as follows: Section 2 summarizes the relevant literature; Section 3 describes the optimization algorithms for the selected systems; and Section 4 presents the algorithm performance evaluation and sensitivity analyses. The last section includes the conclusions and opportunities for future research.

نتیجه گیری انگلیسی

Currently, there exist many studies that demonstrate that mathematical models can be used to optimize the energy used by manufacturing processes in companies, but not to reduce energy used throughout the plant. Through this research it was demonstrated that economic analysis methods, such as the internal rate of return, can be used in optimization models to identify economic feasible alternatives to replace the current equipment with that which consume less energy. This model was applied to the electronic manufacturing company case study and the solution was generated with the Lingo 12.0 program. These results were compared, validated, and proven as correct. Some advantages manufacturing companies may have if the optimization models showed in this research are used are: • The manufacturing companies can identify alternatives to improve the energy used at their facilities without hiring an external consulting firm. • The manufacturing companies can continuously monitor the alternatives to reduce energy use considering the continued advances in the market as part of a continuous improvement program. • The manufacturing companies have the flexibility to analyze different scenarios to obtain the best results and make informed decisions considering all relevant factors. This study focused on the analysis of alternatives for reducing energy use of the air conditioner, compressed air, and lighting systems. For future studies, it will be interesting to evaluate alternatives for exhaust systems and inefficient motors. In addition, this study only evaluates the alternative of replacing existing systems. Therefore, future analyses that evaluate replacing alternatives versus other energy efficient alternatives would be a significant contribution to the subject. These analyses may include replacing parts of the systems with focus on reducing the required investment instead of replacing the systems as a whole. Another possible future work would be to include external factors in the analysis (i.e., externality analysis) and their corresponding benefits and costs to create a more detailed analysis of optimizing energy use in a manufacturing environment