IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i9p2446-d169947.html
   My bibliography  Save this article

Analyzing the Impact of Renewable Energy Incentives and Parameter Uncertainties on Financial Feasibility of a Campus Microgrid

Author

Listed:
  • Vu Ba Hau

    (School of Electrical Engineering, Kookmin University, 861-1, Jeongneung-dong, Seongbuk-gu, Seoul 02707, Korea)

  • Munir Husein

    (School of Electrical Engineering, Kookmin University, 861-1, Jeongneung-dong, Seongbuk-gu, Seoul 02707, Korea)

  • Il-Yop Chung

    (School of Electrical Engineering, Kookmin University, 861-1, Jeongneung-dong, Seongbuk-gu, Seoul 02707, Korea)

  • Dong-Jun Won

    (Department of Electrical Engineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 402-751, Korea)

  • William Torre

    (University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA)

  • Truong Nguyen

    (University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA)

Abstract

The popularity of microgrids is increasing considerably because of their environmental and technical advantages. However, the major challenge in microgrid integration is its financial feasibility due to high capital costs. To address this obstacle, renewable energy incentive programs, which are the motivation of this study, have been proposed in many countries. This paper provides a comprehensive evaluation of the technical and financial feasibility of a campus microgrid based on a techno-economic analysis using the Microgrid Decision Support Tool, which was implemented to support decision-making in the context of microgrid project investment. A method for microgrid design aiming to maximize system profitability is presented. The optimal microgrid configuration is selected depending on financial indices of the project, which directly address the returns on an investment. Most importantly, this analysis captures all the benefits of financial incentives for microgrid projects in California, U.S., which presents a key difference between the California market and other markets. The impact of incentives and uncertain financial parameters on the project investment is verified by sensitivity analysis. The outcomes show that the optimal configuration generates significant electricity savings, and the incentives strongly determine the financial feasibility and the optimal design of a microgrid.

Suggested Citation

  • Vu Ba Hau & Munir Husein & Il-Yop Chung & Dong-Jun Won & William Torre & Truong Nguyen, 2018. "Analyzing the Impact of Renewable Energy Incentives and Parameter Uncertainties on Financial Feasibility of a Campus Microgrid," Energies, MDPI, vol. 11(9), pages 1-24, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2446-:d:169947
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/9/2446/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/9/2446/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amrollahi, Mohammad Hossein & Bathaee, Seyyed Mohammad Taghi, 2017. "Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response," Applied Energy, Elsevier, vol. 202(C), pages 66-77.
    2. Reza Arghandeh & Jeremy Woyak & Ahmet Onen & Jaesung Jung & Robert P. Broadwater, 2014. "Economic Optimal Operation of Community Energy Storage Systems in Competitive Energy Markets," Papers 1407.0433, arXiv.org, revised Sep 2014.
    3. Haghi, Ehsan & Raahemifar, Kaamran & Fowler, Michael, 2018. "Investigating the effect of renewable energy incentives and hydrogen storage on advantages of stakeholders in a microgrid," Energy Policy, Elsevier, vol. 113(C), pages 206-222.
    4. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
    5. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    6. Pless, Jacquelyn & Arent, Douglas J. & Logan, Jeffrey & Cochran, Jaquelin & Zinaman, Owen, 2016. "Quantifying the value of investing in distributed natural gas and renewable electricity systems as complements: Applications of discounted cash flow and real options analysis with stochastic inputs," Energy Policy, Elsevier, vol. 97(C), pages 378-390.
    7. Hanna, Ryan & Ghonima, Mohamed & Kleissl, Jan & Tynan, George & Victor, David G., 2017. "Evaluating business models for microgrids: Interactions of technology and policy," Energy Policy, Elsevier, vol. 103(C), pages 47-61.
    8. Vahid Amir & Shahram Jadid & Mehdi Ehsan, 2017. "Optimal Design of a Multi-Carrier Microgrid (MCMG) Considering Net Zero Emission," Energies, MDPI, vol. 10(12), pages 1-22, December.
    9. Abdul Motin Howlader & Hidehito Matayoshi & Saeed Sepasi & Tomonobu Senjyu, 2018. "Design and Line Fault Protection Scheme of a DC Microgrid Based on Battery Energy Storage System," Energies, MDPI, vol. 11(7), pages 1-22, July.
    10. Björn Nykvist & Måns Nilsson, 2015. "Rapidly falling costs of battery packs for electric vehicles," Nature Climate Change, Nature, vol. 5(4), pages 329-332, April.
    11. Han, Xiaojuan & Zhang, Hua & Yu, Xiaoling & Wang, Lina, 2016. "Economic evaluation of grid-connected micro-grid system with photovoltaic and energy storage under different investment and financing models," Applied Energy, Elsevier, vol. 184(C), pages 103-118.
    12. Jung, Jaesung & Villaran, Michael, 2017. "Optimal planning and design of hybrid renewable energy systems for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 180-191.
    13. Arghandeh, Reza & Woyak, Jeremy & Onen, Ahmet & Jung, Jaesung & Broadwater, Robert P., 2014. "Economic optimal operation of Community Energy Storage systems in competitive energy markets," Applied Energy, Elsevier, vol. 135(C), pages 71-80.
    14. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2016. "The potential role of solid biomass for rural electrification: A techno economic analysis for a hybrid microgrid in India," Applied Energy, Elsevier, vol. 169(C), pages 370-383.
    15. Van-Hai Bui & Akhtar Hussain & Hak-Man Kim, 2017. "Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System," Energies, MDPI, vol. 10(10), pages 1-16, September.
    16. Ou, Ting-Chia & Hong, Chih-Ming, 2014. "Dynamic operation and control of microgrid hybrid power systems," Energy, Elsevier, vol. 66(C), pages 314-323.
    17. Ting-Chia Ou & Kai-Hung Lu & Chiou-Jye Huang, 2017. "Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller)," Energies, MDPI, vol. 10(4), pages 1-16, April.
    18. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
    2. Eva González-Romera & Mercedes Ruiz-Cortés & María-Isabel Milanés-Montero & Fermín Barrero-González & Enrique Romero-Cadaval & Rui Amaral Lopes & João Martins, 2019. "Advantages of Minimizing Energy Exchange Instead of Energy Cost in Prosumer Microgrids," Energies, MDPI, vol. 12(4), pages 1-18, February.
    3. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    4. Krzysztof Zagrajek & Mariusz Kłos & Desire D. Rasolomampionona & Mirosław Lewandowski & Karol Pawlak & Łukasz Baran & Tomasz Barcz & Przemysław Kołaczyński & Wojciech Suchecki, 2023. "Investing in Distributed Generation Technologies at Polish University Campuses during the Energy Transition Era," Energies, MDPI, vol. 16(12), pages 1-24, June.
    5. Vu, Ba Hau & Chung, Il-Yop, 2022. "Optimal generation scheduling and operating reserve management for PV generation using RNN-based forecasting models for stand-alone microgrids," Renewable Energy, Elsevier, vol. 195(C), pages 1137-1154.
    6. Tomasz Rokicki & Piotr Bórawski & Barbara Gradziuk & Piotr Gradziuk & Aldona Mrówczyńska-Kamińska & Joanna Kozak & Danuta Jolanta Guzal-Dec & Kamil Wojtczuk, 2021. "Differentiation and Changes of Household Electricity Prices in EU Countries," Energies, MDPI, vol. 14(21), pages 1-21, October.
    7. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    8. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    9. Kourgiozou, Vasiliki & Commin, Andrew & Dowson, Mark & Rovas, Dimitrios & Mumovic, Dejan, 2021. "Scalable pathways to net zero carbon in the UK higher education sector: A systematic review of smart energy systems in university campuses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    10. Pablo Benalcazar & Adam Suski & Jacek Kamiński, 2020. "The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems," Energies, MDPI, vol. 13(4), pages 1-23, February.
    11. Incheol Shin, 2020. "Approximation Algorithm-Based Prosumer Scheduling for Microgrids," Energies, MDPI, vol. 13(21), pages 1-16, November.
    12. Hak-Ju Lee & Ba Hau Vu & Rehman Zafar & Sung-Wook Hwang & Il-Yop Chung, 2021. "Design Framework of a Stand-Alone Microgrid Considering Power System Performance and Economic Efficiency," Energies, MDPI, vol. 14(2), pages 1-28, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Athila Quaresma Santos & Zheng Ma & Casper Gellert Olsen & Bo Nørregaard Jørgensen, 2018. "Framework for Microgrid Design Using Social, Economic, and Technical Analysis," Energies, MDPI, vol. 11(10), pages 1-22, October.
    2. Pablo Benalcazar & Adam Suski & Jacek Kamiński, 2020. "The Effects of Capital and Energy Subsidies on the Optimal Design of Microgrid Systems," Energies, MDPI, vol. 13(4), pages 1-23, February.
    3. Yongsheng Cao & Guanglin Zhang & Demin Li & Lin Wang & Zongpeng Li, 2018. "Online Energy Management and Heterogeneous Task Scheduling for Smart Communities with Residential Cogeneration and Renewable Energy," Energies, MDPI, vol. 11(8), pages 1-20, August.
    4. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim & Huy Nguyen-Duc, 2018. "Direct Phase Angle and Voltage Amplitude Model Predictive Control of a Power Converter for Microgrid Applications," Energies, MDPI, vol. 11(9), pages 1-21, August.
    5. Resch, Matthias & Bühler, Jochen & Klausen, Mira & Sumper, Andreas, 2017. "Impact of operation strategies of large scale battery systems on distribution grid planning in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1042-1063.
    6. Il-Seok Choi & Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2018. "A Multi-Agent System-Based Approach for Optimal Operation of Building Microgrids with Rooftop Greenhouse," Energies, MDPI, vol. 11(7), pages 1-24, July.
    7. Gopinath Subramani & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg & Josep M. Guerrero, 2017. "Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving," Energies, MDPI, vol. 10(11), pages 1-17, November.
    8. Gao, Zhikun & Yu, Junqi & Zhao, Anjun & Hu, Qun & Yang, Siyuan, 2022. "A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine," Energy, Elsevier, vol. 238(PC).
    9. Qian Liu & Rui Wang & Yan Zhang & Guohua Wu & Jianmai Shi, 2018. "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, MDPI, vol. 11(1), pages 1-16, January.
    10. Mamun, A. & Sivasubramaniam, A. & Fathy, H.K., 2018. "Collective learning of lithium-ion aging model parameters for battery health-conscious demand response in datacenters," Energy, Elsevier, vol. 154(C), pages 80-95.
    11. Lorenzi, Guido & Silva, Carlos Augusto Santos, 2016. "Comparing demand response and battery storage to optimize self-consumption in PV systems," Applied Energy, Elsevier, vol. 180(C), pages 524-535.
    12. Deng Xu & Yong Long, 2019. "The Impact of Government Subsidy on Renewable Microgrid Investment Considering Double Externalities," Sustainability, MDPI, vol. 11(11), pages 1-15, June.
    13. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    14. Nikos Kampelis & Elisavet Tsekeri & Dionysia Kolokotsa & Kostas Kalaitzakis & Daniela Isidori & Cristina Cristalli, 2018. "Development of Demand Response Energy Management Optimization at Building and District Levels Using Genetic Algorithm and Artificial Neural Network Modelling Power Predictions," Energies, MDPI, vol. 11(11), pages 1-22, November.
    15. Ahmed Belila & Mohamed Benbouzid & El-Madjid Berkouk & Yassine Amirat, 2018. "On Energy Management Control of a PV-Diesel-ESS Based Microgrid in a Stand-Alone Context," Energies, MDPI, vol. 11(8), pages 1-23, August.
    16. Fei Wang & Lidong Zhou & Hui Ren & Xiaoli Liu, 2017. "Search Improvement Process-Chaotic Optimization-Particle Swarm Optimization-Elite Retention Strategy and Improved Combined Cooling-Heating-Power Strategy Based Two-Time Scale Multi-Objective Optimizat," Energies, MDPI, vol. 10(12), pages 1-23, November.
    17. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
    18. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    19. Pengfei Wang & Jialiang Yi & Mansoureh Zangiabadi & Pádraig Lyons & Phil Taylor, 2017. "Evaluation of Voltage Control Approaches for Future Smart Distribution Networks," Energies, MDPI, vol. 10(8), pages 1-17, August.
    20. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2446-:d:169947. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.