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بهره برداری بهینۀ پارکینگ هوشمند خودروهای الکتریکی مجهز به منابع انرژی تجدیدپذیر تحت عدم قطعیتهای مختلف | ||
| فصلنامه سیستم های انرژی پایدار | ||
| دوره 1، شماره 1، دی 1400، صفحه 83-95 اصل مقاله (1.17 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ses.2021.88278 | ||
| نویسندگان | ||
| امیر میرزاپور کمانج1؛ مسعود آقابالائی رهور1؛ امیر طالبی1؛ کاظم زارع* 2؛ بهنام محمدی ایواتلو2 | ||
| 1دانشجوی دکتری تخصصی مهندسی برق قدرت، دانشگاه تبریز، دانشکدۀ مهندسی برق و کامپیوتر | ||
| 2استاد مهندسی برق قدرت، دانشگاه تبریز، دانشکدۀ مهندسی برق و کامپیوتر | ||
| چکیده | ||
| با حضور گستردۀ خودروهای الکتریکی در جوامع امروزی لازم است مدیریت هوشمند خودروهای الکتریکی مورد بررسی قرار بگیرد. از طرفی، ادغام منابع انرژی تجدیدپذیر در پارکینگ خودروهای هوشمند سبب کاهش وابستگی به شبکۀ بالادستی و کاهش هزینههای بهرهبرداری میشود. در همین زمینه، در مقالۀ پیش رو بهرهبرداری بهینۀ پارکینگ هوشمند خودروهای الکتریکی مجهز به منابع انرژی تجدیدپذیر مورد بررسی و بحث قرار گرفته است. همچنین، به منظور مدلسازی عدم قطعیت منابع انرژی تجدیدپذیر، قیمت برق شبکۀ بالادستی و رفتار صاحبان خودروهای الکتریکی از روش برنامهریزی تصادفی استفاده شده است. منظور از عدم قطعیت رفتار صاحبان خودروهای الکتریکی شامل زمان ورود خودرو به پارکینگ، زمان خروج از پارکینگ و انرژی اولیۀ آنها هنگام ورود به پارکینگ هستند که به صورت پارامتر دارای عدم قطعیت در نظر گرفته شدهاند. مسئلۀ بهینهسازی یادشده به صورت یک مدل برنامهنویسی آمیخته با اعداد صحیح (MILP1) ارائه شده و توسط حلکنندۀ CPLEX در نرمافزار GAMS حل شده است. نتایج شبیهسازی نشان میدهد بهرهبردار پارکینگ هوشمند با شارژ و دشارژ هوشمند خودروهای الکتریکی میتواند سود کسب کند. همچنین، در حضور سناریوها و عدم قطعیتهای مختلف، استراتژی عملکرد پارکینگ هوشمند متفاوت است، به طوری که بیشترین و کمترین سود کسبشده برابر با 84/1740 و 22/1359 دلار حاصل شد، ولی با در نظر گرفتن احتمال تمام سناریوها سود مورد انتظار برابر با 31/1571 دلار حاصل شد. در نتیجۀ عدم قطعیتهای مختلف، سود حاصل از پارکینگ هوشمند را تحت تأثیر قرار میدهند. | ||
| کلیدواژه‌ها | ||
| برنامه ریزی تصادفی؛ پارکینگ هوشمند خودروهای الکتریکی؛ عدم قطعیت؛ منابع انرژی تجدیدپذیر | ||
| عنوان مقاله [English] | ||
| Optimal Operation of Smart Electric Vehicle Parking Lots Equipped with Renewable Energy Sources under Various Uncertainties | ||
| نویسندگان [English] | ||
| Amir Mirzapour-Kamanaj1؛ Masoud Agabalaye-Rahvar1؛ Amir Talebi1؛ Kazem Zare2؛ Behnam Mohammadi-Ivatloo2 | ||
| 1PhD Student in Power Electrical Engineering, University of Tabriz, Faculty of Electrical and Computer Engineering | ||
| 2Professor of Power Electrical Engineering, University of Tabriz, Faculty of Electrical and Computer Engineering | ||
| چکیده [English] | ||
| Introduction By the extensive presence of electric vehicles (EVs) in today’s communities, the smart management of EVs should be completely investigated. On the other hand, the integration of renewable energy sources (RESs) in the smart electric vehicles parking lot (SEVsPL) reduces the dependency on the upstream network and also the whole operation costs. So, under finite energy sources around the world, in order to supply various demands along with generating low greenhouse gas emissions (GHGEs), policymakers and different scholars seek to find cost-effective, eco-friendly, efficient, and sustainable solutions. With investigating the literature review in the field of management and optimal operation of SEVsPL can be obviously concluded that multiple approaches and strategies from different perspectives were used to improve the efficient usage of energy based on smart grids (SGs) framework in SEVsPL. It was indicated that none of the analyzed references, addressee the simultaneous effects of different uncertainties, i.e., the random behavior of EVs owners, RES, and the upstream network electricity price on the charging and discharging processes for the operation of SEVsPL. Certainly, applying the nature of such uncertainty sources in an appropriate path will have significant impacts on the bringing results as close as possible to the real-world solutions. Model description and method of solution Therefore, in the current paper, a stochastic scheduling methodology for the optimal operation of SEVsPL has been proposed as an interactive user interface between the respective operator and EVs owners to facilitate charging and discharging activities and operation costs. The total capacity of SEVsPL is 50 in which three various EVs’ models with 10 scenarios for the arrival time, departure time, and initial state of energy (SoE) were considered. Furthermore, the other uncertainties oriented from RES and the upstream network electricity price have also taken into account with relative 10 scenarios. It is worth to mention that Mont Carlo simulation (MCS) implemented in MATLAB software to produce 1000 scenarios and then reduce them to 10 scenarios with the assistance of SCENRED algorithm in GAMS software. This stochastic optimization model of SEVsPL was formulated as mixed integer linear programming (MILP) problem, which was solved by CPLEX solver in GAMS software. Simulation results and discussion According to the obtained results in different scenarios, it was obviously seen that the lowest profit of SEVsPL was occurred in scenario 8, which can be considered as the worst case scenario, although, the highest profit has been achieved in scenario 9 and can be taken as the best case scenario. So, it can be mentioned that the optimal utilization of SEVsPL in the presence of RES uncertainty and the unpredictable behavior of EVs can be different. By considering the probabilities of the aforementioned uncertainties, the expected profit for SEVsPL was $ 1571.31. For the plotted figures of photovoltaic (PV) and wind turbine (WT) power plants in scenario 9, the generated WT power can be sold to the upstream network within the period in which EVs have not yet entered the SEVsPL and also for the PV generated power can be utilized to charge EVs. To realize the aim of the SEVsPL operator in maximizing his/her profit, the smart operating strategy was accomplished in purchased /sold power from /to the upstream network, which were indicated in relative figures for two worst case and best case scenarios. These outcomings highlighted that sold power has happened when electricity price is high (e.g., 10 o'clock in scenario 8 and 17 o'clock in scenario 9); however, the purchased power has taken place when electricity price is low (e.g., 10 o'clock in Scenario 9 and 12 o'clock in Scenario 8). This strategy is true for all EVs in all scenarios such that results to gain profit from electricity price arbitrage by the SEVsPL operator. If the EVs owners are looking for the maximum charge when leaving the SEVsPL, the respective operator will earn less profit according to different gamma coefficients presented in relevant expected SEVsPL profit’s figure. In other words, the chance of discharging EVs will be less when attending SEVsPL. Conclusions The proposed stochastic optimal operation strategy of SEVsPL in this paper has been accomplished to flatten charging and discharging processes along with operation costs. In the presence of different considered uncertainties, the optimal operation strategy of SEVsPL can be diverse for different scenarios such that the highest and lowest profits were equal to $1740.84 and $1359.22, respectively. Although by considering the probability of all scenarios, the expected profit was equal to $ 1571.31. These various uncertainties affect the obtained profit of SEVsPL which the respective operator seeks to charge EVs at low price hours and discharge EVs at high price hours under the smart performance strategy. | ||
| کلیدواژه‌ها [English] | ||
| Stochastic programming, smart electric vehicle parking lots, uncertainty, renewable energy sources | ||
| مراجع | ||
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