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The COVID-19 outbreak not only threatened global health, it has also –affected the energy markets around the world. This paper studies the impact of the pandemic on Ontario's electricity market assessing the demand and supply balance over three distinct periods: pre-pandemic, start of the pandemic and during the period 2020–2021. The paper also evaluates the contribution of work-from-home and other mandates in reducing GHG emission. Furthermore, the impact of such rare events is studied on load forecasting. Our analysis shows that although demand dropped by 12% during the beginning of pandemic, it started rising to levels higher than the previous years. Consequently, due to the changes in the daily load profile, primarily due to the changes in consumers' behavior, the emissions declined significantly during the lockdown and increased afterwards. Finally, this paper provides a short-term Feed Forward Neural Network (FFNN) model to predict future demand. The model performance was evaluated during the three distinct periods and showed high accuracy even in the initial stages of the pandemic: MAPE of 3.21% pre-pandemic, 13.86% beginning of pandemic and 4.23% during pandemic. [ABSTRACT FROM AUTHOR]

For decades, countries, states, and municipalities have established energy policies to address local air pollution and global climate change goals. The thousands of policies and measures enacted globally take various forms but are aimed at different sectors of the economy. These policies are the result of a complicated process of analysis, budgeting, management, and politics. Still, greenhouse gas emissions have continued to rise globally. Good models remain rare that bridge the gap between high level aspirations and implementation. The U.S. state of Colorado offers an example over the last two years for bridging the aspiration and implementation gap. This paper provides an overview of the recent legislative sessions, and how the policies enacted support the Colorado Climate Change Roadmap. [ABSTRACT FROM AUTHOR]