Mitigating and adapting to climate change requires decarbonizing electricity while ensuring resilience of supply, since a warming planet will lead to greater extremes in weather and, plausibly, in power outages. Although it is well known that long-duration outages severely impact economies, such outages are usually not well characterized or modeled in grid infrastructure planning tools. Here, we bring together data and modeling techniques and show how they can be used to characterize and model long-duration outages.
A growing number of governments are pledging to achieve net-zero greenhouse gas emissions by mid-century. Despite such ambitions, realized emissions reductions continue to fall alarmingly short of modeled energy transition pathways for achieving net-zero. This gap is largely a result of the difficulty of realistically modeling all the techno-economic and sociopolitical capabilities that are required to deliver actual emissions reductions.
The COVID-19 pandemic has exacerbated energy insecurity and economic hardship among vulnerable populations. This paper provides robust empirical evidence of the degree to which COVID-19 mitigation measures, especially the mandates of school closure and limiting business operations, have impacted electricity consumption behavior in low-income and ethnic minority groups in the United States. We use a regression discontinuity design applied to individual-consumer-level high-frequency smart meter data in Arizona and Illinois to highlight the disparities in mitigation measure impacts.
The COVID-19 pandemic has exacerbated energy insecurity and economic hardship among vulnerable populations. This paper provides robust empirical evidence of the degree to which COVID-19 mitigation measures, especially the mandates of school closure and limiting business operations, have impacted electricity consumption behavior in low-income and ethnic minority groups in the United States. We use a regression discontinuity design applied to individual-consumer-level high-frequency smart meter data in Arizona and Illinois to highlight the disparities in mitigation measure impacts.
Low- and moderate-income (LMI) households remain less likely to adopt rooftop solar photovoltaics (PV) than higher-income households. A transient period of inequitable adoption is common among emerging technologies but stakeholders are calling for an accelerated transition to equitable rooftop PV adoption. To date, researchers have focused on demand-side drivers of PV adoption inequity, but supply-side factors could also play a role. Here, we use quote data to explore whether PV installers implement income-targeted marketing and the extent to which such strategies drive adoption inequity.
As large renewable capacities penetrate the European energy system and the climate faces significant alterations, the future operation of hydropower reservoirs might deviate from today. In this work, we first analyze the changes in hydropower operation required to balance a wind- and solar-dominated European energy system. Second, we apply runoff data obtained from combining five different global circulation models and two regional climate models to estimate future reservoir inflow at three CO2 emissions scenarios (RCP2.6, RCP4.5, and RCP8.5).
Economically viable electric vehicle lithium-ion battery recycling is increasingly needed; however routes to profitability are still unclear. We present a comprehensive, holistic techno-economic model as a framework to directly compare recycling locations and processes, providing a key tool for recycling cost optimization in an international battery recycling economy. We show that recycling can be economically viable, with cost/profit ranging from (−21.43 - +21.91) $·kWh−1 but strongly depends on transport distances, wages, pack design and recycling method.
Owing to its versatility, biomass can be used for a range of CO2 mitigation and removal options. The recent adoption of end-of-century temperature targets at the global scale, along with mid-century economy-wide net zero emission targets in Europe, has boosted demand forecasts for this valuable resource. Given the limited nature of sustainable biomass supply, it is important to understand most efficient uses of biomass, both in terms of avoided CO2 emissions (i.e., substituted energy and economic services) and CO2 removal.
In this paper, an integrated blockchain-based energy management platform is proposed that optimizes energy flows in a microgrid whilst implementing a bilateral trading mechanism. Physical constraints in the microgrid are respected by formulating an Optimal Power Flow (OPF) problem, which is combined with a bilateral trading mechanism in a single optimization problem. The Alternating Direction Method of Multipliers (ADMM) is used to decompose the problem to enable distributed optimization and a smart contract is used as a virtual aggregator.
Equality between economic progress and environmental sustainability is essential for a developing country like India. In the present time, the economy of India is growing rapidly in a vibrant mode and an efficient way, which in turn demands huge uninterrupted energy supplies. The country's energy needs are met mostly by the usage of fossil fuels and nearly 70% of electricity is generated from coal based power plants. In India, nearly 840 million people depend on traditional biomass to satisfy their energy necessities.
