بهینه سازی سنسورهای کنترل و پیش بینی انرژی مبدل حرارتی زمین گرمایی
ترجمه نشده

بهینه سازی سنسورهای کنترل و پیش بینی انرژی مبدل حرارتی زمین گرمایی

عنوان فارسی مقاله: پیش بینی انرژی مبدل حرارتی زمین گرمایی بر اساس سری زمانی و بهینه سازی سنسورهای کنترل
عنوان انگلیسی مقاله: Geothermal heat exchanger energy prediction based on time series and monitoring sensors optimization
مجله/کنفرانس: انرژی - Energy
رشته های تحصیلی مرتبط: مهندسی انرژی
گرایش های تحصیلی مرتبط: انرژی های تجدیدپذیر، سیستم های انرژی
کلمات کلیدی فارسی: مدل سازی سری زمانی، TDNNA ،RIMA، رگرسیون ریج، درختان تصمیم، MLP
کلمات کلیدی انگلیسی: Time series modeling، TDNNA، RIMA، Ridge regression، Decision trees، MLP
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.energy.2018.12.207
دانشگاه: Universidad de Burgos, Departamento de Ingeniería Civil, C/ Francisco de Vitoria, s/n, 09006, Burgos, Spain
صفحات مقاله انگلیسی: 33
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 6/153 در سال 2018
شاخص H_index: 158 در سال 2019
شاخص SJR: 2/048 در سال 2018
شناسه ISSN: 0360-5442
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E11583
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1- Introduction

2- Case of study

3- Regression models description

4- Experimental set up

5- Experiment results

6- Conclusions and future work

References

بخشی از مقاله (انگلیسی)

Abstract

In recent years, the use of renewable energies has been promoted in most of developed countries due to the climate change threat. In this scenario, the importance of geothermal installations has increased. This paper focuses on a heat exchanger present on a geothermal installation. The main aim is to achieve an accurate prediction system using the previous readings of some of the sensors located along the heat exchanger. Different time series modeling techniques were applied obtaining satisfactory results in the prediction of the heat exchanger state during one year. This prediction is made 1 h, 3 h and 6 h in advance. Also, a strong correlation between the sensor readings is concluded, offering the possibility to dispense some of them.

Introduction

In last decades, the world is facing fast changes in terms of economic global instability, increase in competitiveness and climate change [1]. Under these circumstances, the rising price of raw materials and a high fossil fuels dependency, with the corresponding environment damage, led to an intensification in the use of alternative energy resources [2]. The supply of renewable energies is unlimited, and its use is relatively clean. For these reasons, during last decades, many governments have promoted policies that encourage the use of these kind of energies [3]. Usually, solar and wind are the most used alternative energies, and therefore, their technologies have experienced an intense development. However, nowadays, the field of renewable energies have presented significant advances in other disciplines such as geothermal or ocean energies [4]. These advances are aimed at narrowing the implantation costs and increasing the efficiency. Some researches are focused on developing new methods or optimizing existing ones in energy installations [5]. In some systems, different renewable energies like geothermal and solar are combined to improve the efficiency [6]. This paper focuses on a geothermal energy installation. Geothermal is defined as the energy stored in form of heat inside the earth under the ground [7]. Different works estimate that the whole amount of heat flowing from inside the earth is around 42 × 1012 W [7]. Only the 2 % of this energy comes from the crust, the 82 % comes from the mantle due to the decay of radioactive isotopes of uranium, potassium and thorium and the remaining percentage is generated at the core. Despite the vast amount of energy, its use is limited to specific areas with proper geological conditions [8]. At the beginning of twenty first century, the use of geothermal energy to produce electricity had an installed capacity of almost 9 MW, while its use in non-electrical applications represented about 15 MW. The use of nonelectrical geothermal energy is extended in applications like heat pumps, bathing, space heating, green houses, aquaculture and industrial processes [7]. A heat pump is employed to provide thermal energy obtained from an external source to a facility [9]. The external source can be hot or cold, leading the first one to higher efficiency. In geothermal heat pumps, the thermal source is hot and the heat exchanger installation can be placed in horizontal or vertical configurations [10, 11].