سامانه مدیریت انرژی ریزشبکه‌های مبتنی بر انرژی‌های تجدیدپذیر

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی مکانیک بیوسیستم، دانشگاه تربیت مدرس، تهران، ایران

2 دانشکده مدیریت صنعتی، دانشگاه تهران، تهران، ایران

چکیده

انرژی‌های تجدیدپذیر پایدار، پاک و اقتصادی هستند و آینده تأمین انرژی را برعهده دارند. این منابع به دلیل الگوی تولید غیرقطعی و تصادفی، قابلیت اطمینان پایین دارند. استفاده از منابع تولید انرژی ترکیبی به همراه منابع ذخیره کننده و پشتیبان، راه حل مسئله قابلیت اطمینان سامانه‌های تجدیدپذیر می‌تواند باشد. در این مقاله یک ریزشبکه ترکیبی مستقل از شبکه، متشکل از منابع تولید اولیه انرژی بادی و خورشیدی و یک سامانه پشتیبان باتری و ژنراتور با بکارگیری الگوریتم تصمیم‌گیری پویا، مدلسازی، ساخته، ارزیابی و سیزده طرح برای تأمین برق واحد مسکونی پیشنهاد شده است. نتایج نشان داد، استفاده از مدل تصمیم‌گیری پویا موجب افزایش کیفیت و بهره‌وری شده سامانه‌ها شده و در طرح استفاده 24 درصدی از انرژی‌های تجدیدپذیر، مصرف سوخت فسیلی روزانه 1/11 لیتر بوده و انرژی سالانه تولیدی سامانه تبدیل انرژی تجدیدپذیر ترکیبی معادل kWh/yr 1697 با خالص ارزش فعلی 553/68 دلار و نرخ بازگشت سرمایه داخلی 49/21 درصد با دوره بازگشت سرمایه 15/71 سال است. با افزایش ضریب انرژی تجدیدپذیر به 54 درصد، مصرف سوخت فسیلی 0/694 لیتر و انرژی تولیدی سالانه kWh/yr 1652 با دوره بازگشت سرمایه 17/61 سال محاسبه بدست آمد. مدیریت انرژی مصرف کننده‌ها با ضریب %100 انرژی تجدیدپذیر، سالانه kWh/yr 1933 انرژی بدون انتشار آلاینده‌های زیست محیطی و خالص ارزش فعلی 372/09- دلار است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Energy Management Model for a Standalone Hybrid Microgrid Using a Dynamic Decision-Making Algorithm

نویسندگان [English]

  • Mostafa Esmaeili shayan 1
  • Gholamhassan Najafi 1
  • Sahra Esmaeili Shayan 2
1 Department of Biosystem Engineering (Renewable Energy Engineering), Tarbiat Modares University, Tehran, Iran
2 Department of Industrial Management, University of Tehran, Tehran, Iran,
چکیده [English]

Renewable energy is vital for the future of the energy supply because of its properties, which include sustainability, affordability, and environmental friendliness. The low dependability of these sources is a disadvantage due to their nondeterministic and unpredictable production patterns. Utilizing several energy production sources in conjunction with energy storage and backup sources could relieve the problem of system dependability. This study recommends a hybrid microgrid that is independent of the grid and consists of primary sources of wind and solar energy production in addition to a battery and generator backup system. This is achieved through the use of dynamic decision-making algorithms, modeling, construction, and assessment, as well as thirteen distinct strategies for the electrical supply of residential units. Under the scenario to use 24% renewable energies, the consumption of fossil fuel is 1,1 liters per day, and the yearly production energy of the total renewable energy conversion system is comparable to 1,697 kWh with a net present value of $553.68. By increasing the renewable energy factor to 54 percent, the consumption of fossil fuel is reduced to 0.69 liters, and the annual production energy is increased to 1,652 kWh. Consumer energy management with a renewable energy factor of 100 percent, an annual energy usage of 1,933 kWh, and a net present value of -$379.

کلیدواژه‌ها [English]

  • Renewable energy
  • Sustainability
  • Energy storage
  • Microgrid
  • Strategies
[1] X.L. W. Cai, A. Maleki, F. Pourfayaz, M.A. Rosen, M. Alhuyi Nazari, D.T. Bui, Optimal sizing and location based on economic parameters for an off-grid application of a hybrid system with photovoltaic, battery and diesel technology, Energy, 201 (2020) 117480.
[2] O.M.A. O.I. Awad, R. Mamat, A.A. Abdullah, G. Najafi, M.K. Kamarulzaman, I.M. Yusri, M.M. Noor, Using fusel oil as a blend in gasoline to improve SI engine efficiencies: A comprehensive review, Renewable and Sustainable Energy Reviews, 69 (2017) 1232–1242.
[3] M. Esmaeili Shayan, G. Najafi, S. Gorjian, Design Principles and Applications of Solar Power Systems (In Persian), ACECR Publication- Amirkabir University of Technology Branch, Tehran, 2020.
[4] A.K. V., Verma, A., Optimal techno-economic sizing of a solar-biomass-battery hybrid system for off-setting dependency on diesel generators for microgrid facilities, Journal of Energy Storage, 36 (2021) 102251.
[5] R.Z. Zhong, Cheng, L., Wang, Y.Q., Sun, X.Z., Luo, D.W., Fang, Y., Bush, R.D., Zhou, D.W., Effects of anthelmintic treatment on ewe feed intake, digestion, milk production and lamb growth, SPRINGER Verlag, SINGAPOR, 2017.
[6] O. Erixno, Rahim, N.A., Ramadhani, F., and Adzman, N.N.,, Energy management of renewable energy-based combined heat and power systems: A review, Sustainable Energy Technologies and Assessments, 51 (2022) 101944.
[7] A. Chakir, Abid, M., Tabaa, M., and Hachimi, H.,, Demand-side management strategy in a smart home using electric vehicle and hybrid renewable energy system, Energy Reports, 8 (2022) 383–393.
[8] M. Esmaeili Shayan, Najafi, G., Ghobadian, B., Gorjian, S., Mamat, M., Fairusham Ghazali, M., Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm, Renewable Energy, 201(2) (2022) 179-189.
[9] R. Madhana, Mani, G., Power enhancement methods of renewable energy resources using multiport DC-DC converter: A technical review, Sustainable Computing: Informatics and Systems, 35 (2022) 100689.
[10] A. Jouda, Elyes, F., Rabhi, A., Abdelkader, M., Optimization of Scaling Factors of Fuzzy–MPPT Controller for Stand-alone Photovoltaic System by Particle Swarm Optimization, Energy Procedia, 111 (2017) 954–963.
[11] M. Esmaeili Shayan, Hayati, M.R., Thermal Performance and Heat Dynamics Energy and Exergy of Integrated Asphalt Collector Storage: Sources of Thermal Energy, and Thermoelectric Energy, Iranian Journal of Energy and Environment, 14 (2023) 17–25.
[12] M. Esmaeili Shayan, Najafi, G., Ghobadian, B., Gorjian, S., Mazlan, M., A novel approach of synchronization of the sustainable grid with an intelligent local hybrid renewable energy control, International Journal of Energy and Environmental Engineering,  (2022) 1–12.
[13] M. Esmaeili shayan, Najafi, G., Banakar, A. , Power Quality in Flexible Photovoltaic System on Curved Surfaces, Journal of Energy Planning And Policy Research, 3(17) (2017) 105–136.
[14] R. Gnanaselvam, Vasanthi, M.S., Signal coverage analysis with link adaptation in Narrowband-IoT, Sustainable Computing: Informatics and Systems, 33 (2022) 100644.
[15] M. Esmaeili Shayan, Esmaeili Shayan, S., and Nazari, A., Possibility of supplying energy to border villages by solar energy sources, Energy Equipment and Systems, 9(3) (2021) 279–289.
[16] B. Yang, Wang, J., Zhang, X., Yu, L., Shu, H., Yu, T., Sun, L., Control of SMES systems in distribution networks with renewable energy integration: A perturbation estimation approach, Energy, 202 (2020) 117753.
[17] G. Renjini, and Devi, V., Artificial neural network controller based cleaner battery-less fuel cell vehicle with EF2 resonant DC-DC converter, Sustainable Computing: Informatics and Systems, 35 (2022) 100667.
[18] S. Sulaeman, Brown, E., Quispe-Abad, R., and Müller, N., Floating PV system as an alternative pathway to the amazon dam underproduction, Renewable and Sustainable Energy Reviews, 135 (2021) 110082.
[19] Y. Li, Gao, W., and Ruan, Y., Performance investigation of grid-connected residential PV-battery system focusing on enhancing self-consumption and peak shaving in Kyushu, Japan, Renewable Energy, 127 (2018) 514–523.
[20] M. Esmaeili Shayan, Hayati, M.R., Najafi, G., Esmaeili Shayan, S., The Strategy of Energy Democracy and Sustainable Development: Policymakers and Instruments, Iranian (Iranica) Journal of Energy & Environment, 13(2) (2022) 185–201.
[21] M. Esmaeili Shayan, Najafi, G., Ghobadian, B., Gorjian, S., Mazlan, M., Samami, M., Flexible Photovoltaic System on Non-Conventional Surfaces: A Techno-Economic Analysis, Sustainability 14 (2022) 3566.
[22] A. Alarifi, Ali AlZubi, A., Alfarraj, O., and Alwadain, A., Automated control scheduling to improve the operative performance of smart renewable energy systems, Sustainable Energy Technologies and Assessments, 45 (2021) 101036.
[23] A.K. PG, P, A.J., and D, D., Hybrid CAC-DE in optimal reactive power dispatch (ORPD) for renewable energy cost reduction, Sustainable Computing: Informatics and Systems, 35 (2022) 100688.
[24] W. Anupong, Azhagumurugan, R., Sahay, K.B., Dhabliya, D., Kumar, R., Vijendra Babu, D., Towards a high precision in AMI-based smart meters and new technologies in the smart grid, Sustainable Computing: Informatics and Systems, 35 (2022) 100690.
[25] F. Alassery, Advanced metering infrastructure smart metering based on cloud architecture for low voltage distribution networks in application of smart grid monitoring, Sustainable Computing: Informatics and Systems, 35 (2022) 100747.
[26] M. Esmaeili Shayan, Najafi, G., Lorenzini, G., Phase change material mixed with chloride salt graphite foam infiltration for latent heat storage applications at higher temperatures and pressures, International Journal of Energy and Environmental Engineering,  (2021) 1-11.
[27] P.S. Pravin, Misra, S., Bhartiya, S., Gudi, R.D., A reactive scheduling and control framework for integration of renewable energy sources with a reformer-based fuel cell system and an energy storage device, Journal of Process Control, 87 (2020) 147–165.
[28] X. Dong, Lu, J., Sun, B., Min-max Operation Optimization of Renewable Energy Combined Cooling, Heating, and Power Systems Based on Model Predictive Control, IFAC-PapersOnLine, 53(2) (2020) 12809–12814.
[29] M. Esmaeili Shayan, Najafi, G., Ghobadian, B., Gorjian, S., Modeling the Performance of Amorphous Silicon in Different Typologies of Curved Building-integrated Photovoltaic Conditions, Iranian (Iranica) Journal of Energy & Environment, 13(1) (2022) 87–97.
[30] E. Noghreian, Koofigar, H.R., Power control of hybrid energy systems with renewable sources (wind-photovoltaic) using switched systems strategy, Sustainable Energy, Grids and Networks, 21 (2020) 100280.
[31] M.T. Quasim, Sulaiman, A., Shaikh, A., Younus, M., Blockchain in churn prediction based telecommunication system on climatic weather application, Sustainable Computing: Informatics and Systems, 35 (2022) 100705.
[32] J. Jeyaranjani, Devaraj, D., Improved genetic algorithm for optimal demand response in smart grid, Sustainable Computing: Informatics and Systems, 35 (2022) 100710.