Minimizing Grid Reliance: A Power Model Approach for Peak Hour Demand Based on Hybrid Solar Systems

Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Electrical energy demands have increased due to population growth and the variety of new electrical load technologies. This increase demand has nearly doubled during peak hours. Consequently, that necessitates the construction of new power plant infrastructures, which is a costly approach due to the expense of construction building, future preservation like maintenance, and environmental impact. As an alternative approach, most electrical utilities increase the price of electrical usage during peak hours, encouraging consumers to use less electricity during peak periods under Time-Of-Use programs, which may not be universally suitable for all consumers. Furthermore, in some areas, the excessive demand and the lack of supply cause an electrical outage, posing considerable stress and challenges to electrical utilities and consumers. However, control systems, artificial intelligence (AI), and renewable energy (RE), when effectively integrated, provide new solutions to mitigate excessive demand during peak hours. This paper presents a power model that reduces the reliance on the power grid during peak hours by utilizing a hybrid solar system connected to a residential house with a power management controller, that prioritizes the power drives between Photovoltaic (PV) production, battery backup, and the utility electrical grid. As a result, dependence on utility grid was from 3% to 18% during peak hours, improving energy stability safely and efficiently for electrical utilities, consumers, and communities, providing a viable alternative to conventional approaches such as Time-Of-Use programs.

Keywords: Artificial intelligence, AI, control system, photovoltaic, PV, renewable energy.

References:

[1] “Greenhouse gas reporting program (ghgrp),” U.S. Environmental Protection Agency 2022. https://www.epa.gov/ghgreporting/ghgrp-power-plants Accessed: 15 Feb. 2024.
[2] “How Much Does Electricity Cost by State?” EnergySage, www.energysage.com/local-data/electricity-cost/ Accessed 07 Apr. 2024.
[3] “What Is Peak Demand and How It Affects You.” Titan Energy, 23 July 2021, www.titanenergyne.com/peak-demand/ Accessed 07 Apr. 2024.
[4] Torriti, Jacopo. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy." Energy 44.1 (2012): 576-583
[5] Cole, Matthew A., et al. "Power outages and firm performance in Sub-Saharan Africa." Journal of Development Economics 134 (2018): 150-159.
[6] Kotková, Barbora, and Martin Hromada. "Adverse event in a medical facility-blackout." International Journal of Power Systems 5 (2020).
[7] Molinari, Noelle Angelique M., et al. "Who's at risk when the power goes out? The at-home electricity-dependent population in the United States, 2012." Journal of public health management and practice 23.2 (2017): 152-159
[8] Matthewman, Steven, and Hugh Byrd. "Blackouts: a sociology of electrical power failure." (2014).
[9] Andresen, Adam X., et al. "Understanding the social impacts of power outages in North America: a systematic review." Environmental Research Letters 18.5 (2023): 053004.
[10] Cousins, Terry. "Using time of use (TOU) tariffs in industrial, commercial and residential applications effectively." TLC Engineering Solutions (2009).
[11] Hussin, N. S., et al. "Residential electricity time of use (ToU) pricing for Malaysia." 2014 IEEE Conference on Energy Conversion (CENCON). IEEE, 2014.
[12] Herter, Karen, Patrick McAuliffe, and Arthur Rosenfeld. "An exploratory analysis of California residential customer response to critical peak pricing of electricity." Energy 32.1 (2007): 25-34.
[13] Yunusov, Timur, and Jacopo Torriti. "Distributional effects of Time of Use tariffs based on electricity demand and time use." Energy Policy 156 (2021): 112412.
[14] Alam, M. J. E., K. M. Muttaqi, and Darmawan Sutanto. "Mitigation of rooftop solar PV impacts and evening peak support by managing available capacity of distributed energy storage systems." IEEE transactions on power systems 28.4 (2013): 3874-3884.
[15] Henri, Gonzague, et al. "pymgrid: An open-source python microgrid simulator for applied artificial intelligence research." arXiv preprint arXiv:2011.08004 (2020).
[16] “Solar Software.” HelioScope, helioscope.aurorasolar.com/. Accessed 16 Jan. 2024.
[17] “How Much Electricity Does an American Home Use?” U.S. Energy Information Administration (EIA), 8 Jan. 2024, www.eia.gov/tools/faqs/faq.php?id=97&t=3. Accessed 11 Mar. 2024.