ANALYSIS OF THE ECONOMIC AGREEMENTS AND ENERGY MANAGEMENT SYSTEMS FOR THE ADOPTION OF ROOFTOP PHOTOVOLTAIC MICROGRID SYSTEMS USING GAME-THEORY AND FUZZY Q-LEARNING
Keywords:
Microgrid, Reinforcement Learning, Q-Learning, Game Theory, Fuzzy Logic, Economic, ControlAbstract
Many cities have formed policy goals to achieve clean energy by 2030, but the engineering and economic processes to do so remain unclear. The adoption of renewable energy through solar powered microgrids is a rising solution for cities. Microgrids operate near the end user and reduce transmission losses, transformation losses, and increase power reliability. Investing in local microgrid infrastructure reduces the congestion in the existing power grid. Building new power generation infrastructure and satisfying local consumer demand results in a complex economic and engineering game. Utility companies are dependent on third party solar developers to invest in power generation infrastructure and are limited to investing in only distribution infrastructure updates. Solar developers must find and lease land within the city to build solar power generation field sites. Once the infrastructure is in place, the microgrid is able to provide high quality power to its local community. The power provided to the local community is sold at a fixed price determined by the solar developer. The microgrid is integrated with the main grid to request and bid electricity at a price agreed upon by the utility company and solar developer. The microgrid should be able to act independently of other agents and maximize its rewards. This paper investigates the required economic agreements between: property developers and solar developers, and solar developers and utility companies. Furthermore, the control and operation of a 2 player microgrid system is proposed for the local community of Ward 6 - Washington, DC.
References
Budi, R. F., Sarjiya, & Hadi, S. P. (2021). Multi-level game theory model for partially deregulated generation expansion planning. Energy, 237, 121565. https://doi.org/10.1016/j.energy.2021.121565
DOEE: Department of Energy & Environment. (n.d.). Clean Energy DC omnibus amendment act. Clean Energy DC Omnibus Amendment Act. Retrieved March 1, 2023, from https://doee.dc.gov/service/clean-energy-dc-omnibus-amendment-act
An exelon company. Pepco. (n.d.). Retrieved March 1, 2023, from https://www.pepco.com/MyAccount/MyService/Pages/DC/GreenPowerConnection.aspx
Fenston, J. (2018, July 31). Pepco 'systematically mishandling' solar projects, says DC AG. DCist. Retrieved March 1, 2023, from
https://dcist.com/story/22/03/23/pepco-systematically-mishandling-solar-projects-ag-racine/
Huang, W., & Li, H. (2022). Game theory applications in the Electricity Market and Renewable Energy Trading: A Critical Survey. Frontiers in Energy Research, 10. https://doi.org/10.3389/fenrg.2022.1009217
DCPSC: Public Service Commission. (n.d.). Renewable energy portfolio standard (RPS) report. DCPSC. Retrieved March 1, 2023, from
https://dcpsc.org/Orders-and-Regulations/PSC-Reports-to-the-DC-Council/Renewable-Energy-Po rtfolio-Standard.aspx
Avalonbay Communities Inc (NYSE:AVB). AlphaSpread.com. (2023a, May 8). https://www.alphaspread.com/security/nyse/avb/discount-rate
EIA. (2023, April 25). Electricity Monthly Update - U.S. energy information administration (EIA). Electricity Monthly Update - U.S. Energy Information Administration (EIA).
https://www.eia.gov/electricity/monthly/update/wholesale-markets.php
Environmental Protection Agency. (2023, February 5). Green Power Pricing. EPA.
https://www.epa.gov/green-power-markets/green-power-pricing
Esri, CGIAR, & USGS. (2023, April 4). Energy Community Tax Credit Bonus. US Department of Energy.
https://arcgis.netl.doe.gov/portal/apps/experiencebuilder/experience/?id=a2ce47d4721a477a8701 bd0e08495e1d
Evans, B. (2023, January 24). Ira update: It’s a go for green building tax incentives. U.S. Green Building Council. https://www.usgbc.org/articles/ira-update-it-s-go-green-building-tax-incentives
Marsh, J. (2023, May 4). What are Renewable Energy Credits (RECs)?. EnergySage. https://www.energysage.com/other-clean-options/renewable-energy-credits-recs/
Nextera Energy (NEE) - basic shares outstanding. CompaniesMarketCap.com - companies ranked by market capitalization. (2023, May 8).
https://companiesmarketcap.com/nextera-energy/shares-outstanding/#:~:text=Number%20of%20 shares%20outstanding%20as,company%20had%201%2C987%2C000%2C000%20shares%20out standing.
Nextera Energy Partners LP (NYSE:NEP). AlphaSpread.com. (2023b, May 8). https://www.alphaspread.com/security/nyse/nep/discount-rate
NextEra Energy. (2021). Cash flow quality and leverage. – NextEra Energy, Inc.
https://www.investor.nexteraenergy.com/fixed-income-investors/cash-flow-quality-and-leverage
SOLAR LEASE AGREEMENT City of Auburn and Abundant Solar Power (A2) LLC . (2019,
August).
https://legistarweb-production.s3.amazonaws.com/uploads/attachment/pdf/412933/FINAL_DRA FT_LEASE_AGREEMENT_8-15-19.pdf
Batty, S. E. (1977). Game-theoretic approaches to urban planning and Design. Environment and Planning B: Planning and Design, 4(2), 211–239. https://doi.org/10.1068/b040211
Bompard, E., Ma, Y. C., & Ragazzi, E. (2006). Micro-economic analysis of the physical constrained markets: Game theory application to competitive electricity markets. The European Physical Journal B - Condensed Matter and Complex Systems, 50(1-2), 153–160.
https://doi.org/10.1140/epjb/e2006-00122-1
Bowling, M., & Veloso, M. (2000). An analysis of stochastic game theory for multiagent reinforcement learning. Carnegie Mellon University - School of Computer Science. Retrieved February 13, 2023, from https://www.cs.cmu.edu/~mmv/papers/00TR-mike.pdf
A fuzzy approach to strategic games - fuzzy systems, IEEE ... - auth. (n.d.). Retrieved February 13, 2023, from
https://users.auth.gr/kehagiat/Research/GameTheory/05PapersAdvanced/Fuzzy00811230.pdf
Iea. (n.d.). Challenges and opportunities beyond 2021 – renewable energy market update – analysis. IEA. Retrieved February 12, 2023, from https://www.iea.org/reports/renewable-energy-market-update/challenges-and-opportunities-beyon d-2021
Kumar, S., & Dwivedi, B. (2019). Techno-Economical Study of Power System market- a game theory approach. 2019 International Conference on Automation, Computational and Technology Management (ICACTM). https://doi.org/10.1109/icactm.2019.8776743
Loni, A., & Parand, F.-A. (2017). A survey of game theory approach in smart grid with emphasis on cooperative games. 2017 IEEE International Conference on Smart Grid and Smart Cities
(ICSGSC). https://doi.org/10.1109/icsgsc.2017.8038583
A survey of game theory applications in electrical power micro-grid systems. Research Gate. (n.d.). Retrieved February 13, 2023, from
https://www.researchgate.net/publication/339329405_A_Survey_of_Game_Theory_Applications _in_Electrical_Power_Micro-Grid_Systems
Ahmad Alzahrania, Mehdi Ferdowsia, Pourya Shamsia, Cihan H.Daglib, C., b, & AbstractComplex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes. (2017, October 9). Modeling and simulation of Microgrid. Procedia Computer Science. Retrieved December 14, 2022, from
https://www.sciencedirect.com/science/article/pii/S1877050917318574
A. Llria, O. Curea, J. Jimenez, H. Camblong, Survey on microgrids: unplanned islanding and related inverter control techniques, Int. J. Renew. Energy 36 (2011) 2052–2061.
Degeilh, Y., & Gross, G. (2014, August 15). Stochastic simulation of power systems with integrated intermittent renewable resources. International Journal of Electrical Power & Energy Systems. Retrieved December 9, 2022, from https://www.sciencedirect.com/science/article/pii/S0142061514004840.
Global wind atlas. Global Wind Atlas. (n.d.). Retrieved December 9, 2021, from https://globalwindatlas.info/.
Girgis, L., & Bernton, H. (2022, December 8). PSE substations among six attacked in Pacific Northwest in November. The Seattle Times. Retrieved December 14, 2022, from
https://www.seattletimes.com/seattle-news/law-justice/pse-substations-among-five-attacked-in-pa cific-northwest-in-november/
Kofinas, P., Dounis, A., & Vouros, G. (1970, January 1). Fuzzy Q-learning for multi-agent decentralized energy management in microgrids: Semantic scholar. Applied Energy. Retrieved December 14, 2022, from
https://www.semanticscholar.org/paper/Fuzzy-Q-Learning-for-multi-agent-decentralized-in-Kofin as-Dounis/069f6760e7e45df6cccb006905b64742607ff55f
M.S. Mahmouda, Azher Hussaina M.A. Abidob (2014, February 6). Modeling and control of microgrid: An overview. Journal of the Franklin Institute. Retrieved December 14, 2022, from https://www.sciencedirect.com/science/article/pii/S0016003214000180
NOAA Solar Position calculator. (n.d.). Retrieved December 14, 2022, from https://gml.noaa.gov/grad/solcalc/azel.html
P. Barker, D. Herman, Technical and economic feasibility of microgrid- based power systems, in: Proceedings of the Seventh EPRI Distributed Resources Conference and Exhibition Dallas, TX, 20–22 March 2002.
Real-time operating grid - U.S. Energy Information Administration (EIA). Real-time Operating Grid - U.S. Energy Information Administration (EIA). (n.d.). Retrieved December 9, 2022, from https://www.eia.gov/electricity/gridmonitor/dashboard/electric_overview/regional/REG-MIDA.
Research on autonomous operation control of microgrid based on deep ... (n.d.). Retrieved December 14, 2022, from https://ieeexplore.ieee.org/document/9713298/references
Škiparev, Vjatšeslav & Machlev, Ram & Chowdhury, Nilanjan & Levron, Yoash & Petlenkov, Eduard & Belikov, Juri. (2021). Virtual Inertia Control Methods in Islanded Microgrids. Energies. 14. 1562. 10.3390/en14061562.
Sutton, R. S., & Barto, A. G. (2020). Reinforcement learning: An introduction. The MIT Press.
U.S. Bureau of Labor Statistics. (n.d.). Average energy prices - washington DC. U.S. Bureau of Labor Statistics. Retrieved December 14, 2022, from
https://www.bls.gov/regions/mid-atlantic/data/averageenergyprices_washingtondc_table.htm
U.S. Energy Information Administration - EIA - independent statistics and analysis. District of Columbia - State Energy Profile Overview - U.S. Energy Information Administration (EIA). (n.d.). Retrieved December 9, 2021, from https://www.eia.gov/state/?sid=DC#tabs-2.
US/vertex 670W+ module. Trina Solar. (2021, September 30). Retrieved December 9, 2021, from https://www.trinasolar.com/us/product/VERTEX-DEG21C.20.
V. Skiparev, J. Belikov and E. Petlenkov, "Reinforcement Learning based Approach for Virtual Inertia Control in Microgrids with Renewable Energy Sources," 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 2020, pp. 1020-1024, doi:
1109/ISGT-Europe47291.2020.9248777.
Vallée, F., Lobry, J., & Deblecker, O. (n.d.). (PDF) System Reliability Assessment Method for wind power ... Retrieved December 9, 2021, from https://www.researchgate.net/publication/3268561_System_Reliability_Assessment_Method_for _Wind_Power_Integration.
Zakaria, A., Ismail, F. B., Lipu, M. S. H., & Hannan, M. A. (2019, July 16). Uncertainty models for stochastic optimization in renewable energy applications. Renewable Energy. Retrieved December 9, 2021, from https://www.sciencedirect.com/science/article/pii/S0960148119311012.
James & Anthony. (2022, October 21). Asking Pepco Electricians about Power Generation and Distribution within the District. personal.
SEIA.Solar Power Purchase Agreements. SEIA. (2023). https://www.seia.org/research-resources/solar-power-purchase-agreements
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