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The ability to (re)establish basic community infrastructure and governmental functions, such as medical and communication systems, after the occurrence of a natural disaster rests on a continuous supply of electricity. Traditional energy-generation systems consisting of power plants, transmission lines, and distribution feeders are becoming more vulnerable, given the increasing magnitude and frequency of climate-related natural disasters. We investigate the role that fuel cells, along with other distributed energy resources, play in post-disaster recovery efforts. We present a mixed-integer, non-linear optimization model that takes load and power-technology data as inputs and determines a cost-minimizing design and dispatch strategy while considering operational constraints. The model fails to achieve gaps of less than 15%, on average, after two hours for realistic instances encompassing five technologies and a year-long time horizon at hourly fidelity. Therefore, we devise a multi-phase methodology to expedite solutions, resulting in run times to obtain the best solution in fewer than two minutes; after two hours, we provide proof of near-optimality, i.e., gaps averaging 5%. Solutions obtained from this methodology yield, on average, an 8% decrease in objective function value and utilize fuel cells three times more often than solutions obtained with a straight-forward implementation employing a commercial solver. 

Energy equity and justice have become priority considerations for policymakers, practitioners, and scholars alike. To ensure that energy equity is incorporated into actual decisions and analysis, it is necessary to design, use, and continually improve energy equity metrics. In this article, we review the literature and practices surrounding such metrics. We present a working definition for energy justice and equity, and connect them to both criteria for and frameworks of metrics. We then present a large sampling of energy equity metrics, including those focused on vulnerability, wealth creation, energy poverty, life cycle, and comparative country-level dynamics.We conclude with a discussion of the limitations, gaps, and trade-offs associated with these various metrics and their interactions thereof.

 

Energy transitions and decarbonization require rapid changes to a nation’s electricity generation mix. There are many feasible decarbonization pathways for the electricity sector, yet there is vast uncertainty about how these pathways will advance or derail the nation’s energy equality goals. We present a framework for investigating how decarbonization pathways, driven by a least-cost paradigm, will impact air pollution inequality across vulnerable groups (e.g., low-income, minorities) in the US. We find that if no decarbonization policies are implemented, Black and high-poverty communities may be burdened with 0.19–0.22 μg/m³higher PM_2.5concentrations than the national average during the energy transition. National mandates requiring more than 80% deployment of renewable or low-carbon technologies achieve equality of air pollution concentrations across all demographic groups. Thus, if least-cost optimization capacity expansion models remain the dominant decision-making paradigm, strict low-carbon or renewable energy technology mandates will have the greatest likelihood of achieving national distributional energy equality. Decarbonization is essential to achieving climate goals, but myopic decarbonization policies that ignore co-pollutants may leave Black and high-poverty communities up to 26–34% higher PM_2.5exposure than national averages over the energy transition.

 

Abstract Universal access to electricity is an essential part of sub-Saharan Africa’s path to development. With the United Nations setting Goal 7 of its sustainable development goals to be universal access to clean, reliable and affordable electricity, substantial research efforts have been made to optimize electricity supply based on projected demand in sub-Saharan African (SSA) countries. Our study reviews the literature on electricity demand, with a specific focus on latent demand (i.e., electricity demand that would exist if the necessary techno-economic conditions were met) in SSA. We found that out of 57 electricity demand papers reviewed, only 3 (5%) incorporated latent demand in their electricity demand projections. Furthermore, majority of the literature on electricity consumption and demand estimation in SSA use econometric models to identify determinants of electricity consumption and project future demand. We find that population density, urbanization, household income, electricity price, market value of crops and availability of natural resources to be significant determinants of electricity consumption in SSA. We conclude the review by proposing a methodology, and providing an initial proof of concept, for more accurately projecting latent demand in sub-Saharan Africa. Incorporating latent demand in electrification models would help inform energy sector stakeholders (e.g., investors and policymakers) about which sectors and geographic locations hold potential for wealth creation via electricity access. 

Access to electricity is a crucial aspect of sub-Saharan Africa’s path towards development. In light of the potential for electricity access to improve quality of life, the United Nations aims to achieve universal access to ‘clean, reliable, affordable and modern’ electricity as Goal 7 of its Sustainable Development Goals (SDG 7). As such, governments of sub-Saharan African (SSA) countries, such as Ethiopia, have developed national electrification plans to outline their pathway to universal access to electricity. In this paper, we identify why it is essential for the national electrification plans of SSA countries to prioritize electricity access for productive uses in its agricultural sector, using Ethiopia as a case study. Reviewing existing literature and using the authors’ research, we point out that there is 3.04 terawatt-hours of latent demand for small-scale pressurized cereal-crop irrigation alone in Ethiopia. Supplying this electricity demand for small-scale irrigation could lead to a reduction in the levelized cost of electricity of up to 95%. We conclude our paper by recommending the creation of a cross-sector national productive use commission that would be tasked with collecting and sharing relevant data from each sector and collaboratively creating a national productive use program that would ensure that Ethiopia reaps the full benefits and potential for wealth creation from access to electricity.

 

Income-based energy poverty metrics ignore people’s behavior patterns, particularly reducing energy consumption to limit financial stress. We investigate energy-limiting behavior in low-income households using a residential electricity consumption dataset. We first determine the outdoor temperature at which households start using cooling systems, the inflection temperature. Our relative energy poverty metric, theenergy equity gap, is defined as the difference in the inflection temperatures between low and high-income groups. In our study region, we estimate the energy equity gap to be between 4.7–7.5 °F (2.6–4.2 °C). Within a sample of 4577 households, we found 86 energy-poor and 214 energy-insecure households. In contrast, the income-based energy poverty metric, energy burden (10% threshold), identified 141 households as energy-insecure. Only three households overlap between our energy equity gap and the income-based measure. Thus, the energy equity gap reveals a hidden but complementary aspect of energy poverty and insecurity.

 

It is inherently difficult to plan water systems for a future that is non-predictive. This paper introduces a novel perspective for the design and operation of potable water systems under increasing water quality volatility ( e.g. , a relatively rapid and unpredicted deviation from baseline water quality). Increased water quality volatility and deep uncertainty stress water systems, confound design decisions, and increase the risk of decreased water system performance. Recent emphasis on resilience in drinking water treatment has partly addressed this issue, but still establishes an adversarial relationship with change. An antifragile system benefits from volatile change. By incorporating antifragility, water systems may move beyond resilience and improve performance with extreme events and other changes, rather than survive, or fail and quickly recover. Using examples of algal blooms, wildfires, and the COVID-19 pandemic, this work illustrates fragility, resilience, and antifragility within physicochemical process design including clarification, adsorption and disinfection. Methods for increasing antifragility, both individual process options and new system design tools, are discussed. Novel physicochemical processes with antifragile characteristics include ferrate preoxidation and magnetic iron (nano)particles. New design tools that allow for systematic evaluation of antifragile opportunities include artificial neural networks and virtual jar or pilot “stress testing”. Incorporating antifragile characteristics represents a trade-off with capital and/or operating cost. We present a real options analysis approach to considering costs in the context of antifragile design decisions. Adopting this antifragile perspective will help ensure water system improved performance during extreme events and a general increase in volatility.