دانلود مقاله مدیریت سمت تقاضا برای برق در ایران
چکیده
مقدمه
مروری بر مطالعات پیشین
روش
الگوریتم LEAP
طراحی سناریو
نتایج
خطی مشی و پیاده سازی مدیریتی
بحث
نتیجه گیری
منابع
Abstract
Introduction
Literature review
Method
LEAP algorithm
Scenario design
Results
Policy and managerial implementation
Discussion
Conclusions
References
چکیده
در سال های اخیر، افزایش هزینه های تولید برق، سرمایه گذاری های قابل توجه با هدف ساخت نیروگاه ها و آلودگی های زیست محیطی مرتبط با تولید برق بر اهمیت مدیریت بهینه عرضه و تقاضا تاکید کرده است. با توجه به اینکه با استفاده از نرم‌افزار برنامه‌ریزی جایگزین‌های انرژی دوربرد (LEAP)، پژوهش حاضر با هدف بهینه‌سازی سیستم انرژی ایران از طریق دو قابلیت مدل بهینه‌سازی بخش الکتریکی و شبیه‌سازی انجام شد. برای انجام این کار، سیستم انرژی ابتدا با بهینه سازی تقاضای برق ایران توسط سناریوی مدیریت سمت تقاضا (DSM) مورد ارزیابی قرار گرفت. سپس با تعیین سقف انتشار با سناریوهای مختلف به ویژه سناریوی Optimized، بخش برق ایران برای تولید برق با کمترین هزینه بهینه شد. هزینه اجتماعی و انتشار GHG در هر دو مرحله مورد ارزیابی قرار گرفت. هزینه‌های اجتماعی آینده بخش تولید برق بر اساس سناریوهای Optimized و DSM 5.1 و 4.8 میلیارد دلار آمریکا در سال 2035 محاسبه شد. برای همان سال 144 و 429 MtCO2 باشد.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
In recent years, escalating cost of generating electricity, substantial investments with the purpose of building power plants, and environmental pollution related to the power generation have underlined the importance of optimal power supply and demand management. Given that, by employing Long-range Energy Alternatives Planning (LEAP) software, the present study set out to optimize the energy system of Iran through two model capabilities, namely electric sector optimization and simulation. To do so, the energy system was initially evaluated by optimizing Iran's demand for electricity by the Demand Side Management (DSM) scenario. Then, Iran's electricity sector was optimized to generate electricity at the lowest cost by setting emission roof with different scenarios, especially the Optimized scenario. The social cost and GHG emission were evaluated in both steps. The prospective social costs of the electricity generation sector based on Optimized and DSM scenarios were calculated to be 5.1 and 4.8 Billion U.S. Dollars in 2035. Regarding the environmental results of the study, the emission rates of pollutants based on Optimized and DSM scenarios were reported to be144 and 429
Introduction
Energy efciency increase, greenhouse gas (GHG) reduction, and energy cost decrease can be achieved by the energy management and standardization. Energy management lowers costs, carbon emissions, and the risks. It also raises efcient energy consumption by the help of activities, processes and techniques promoting higher efcient energy consumption (Ates, 2015). With the steady growth of the world population and the advent and popularization of energy hungry technologies in the past few decades, the need for such solutions and strategies to control the ever-increasing consumption of energy, particularly electricity has become more apparent (Statistical Review of World, BP global 2017).
In Iran, easy access to relatively cheap electricity has reduced the incentive for electricity conservation and energy efciency. This unfortunate pattern of electricity consumption in Iran stresses the necessity of new policies to improve the situation. Given that, the present study examines the energy system of Iran between 2013 and 2035 in diferent optimization scenarios using Long-range Energy Alternatives Planning (LEAP) software. In the frst part of the study, the electricity demand is optimized by DSM policies.
Conclusions
In this study, the capabilities of the LEAP software were used with the purpose of optimizing both electricity supply and electricity demand in Iran. The results showed that in the electric sector, optimization scenarios, i.e., Combined-cycle Only, Steam Only, Diesel Only, Gas-turbine Only, Optimized, and Limit, the social costs of power plants in 2035 would be 5.7, 9.5, 6.9, 4.1, 5.1, and 5.1 Billion U.S. Dollars, respectively; however, in the DSM scenario, this cost would be only 4.8 Billion U.S. Dollars. The results obtained in the present study showed that using DSM scenario (5% decrease in electricity consumption of sectors and 5% decrease in transmission and distribution losses) and the least-cost optimization of Iran’s electric sector in order to produce 745.9