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• This paper describes a community level approach to achieve zero energy objectives. • An agent-based model is developed to study renewable energy adoption by consumers. • Multiple renewable energy options are modeled simultaneously to study adoption. • The results highlight the importance of community solar to increase adoption. • Social interactions among consumers significantly affect their adoption decisions. As zero energy buildings take on an increasingly prominent role in overall efforts to reduce energy consumption, it is necessary to identify effective policies for their design and implementation. However, current zero energy building (ZEB) policies focus mainly on new buildings, primarily through on-site renewable energy generation, such as rooftop photovoltaic (PV) systems. Having a few high performing buildings will have limited impact if the community as a whole is not net zero. A more practical approach to achieve zero energy goals is to extend the zero energy boundaries beyond an individual building and have a group of buildings evaluated together as a community, such that the community in itself becomes a zero-energy community (ZEC). Successful ZEC implementation requires that community members actively participate in renewable energy and energy efficiency programs and collectively support the goal of zero energy. Hence, a consumer-oriented analysis is needed to support effective ZEC design decisions and promotion efforts. This paper describes a conceptual agent-based model for an urban neighborhood in Des Moines, Iowa, to predict household level renewable energy adoption behaviors in presence of multiple options. Specifically, the level of consumer participation before and after introducing a community solar option for the neighborhood is evaluated via experimentation with the model. Simulation results demonstrate that introducing a community solar program increases household level adoption as well as the proportion of community level electricity consumption met through renewable sources. The amount of increase in adoption, however, depends on the choice of design parameters, such as premium that households must pay to participate. The results also show that timeliness of achieving ZEC goals depends upon the frequency of social interactions in the neighborhood, indicating the importance of community events in the successful creation of a ZEC. [ABSTRACT FROM AUTHOR]

Residential consumers in the U.S. have demonstrated a growing interest in rooftop photovoltaic (PV) systems, resulting in increased adoption over the last decade. However, this has diminished utility revenues, and policymakers have expressed concerns about inequitable consumer access to publicly-funded rooftop PV adoption incentives. In response to these concerns, policymakers and utility companies are changing their policies to discourage rooftop PV adoption. Alternative renewable energy models, such as utility-provided community solar programs, offer a potential solution. However, when designing such programs, it is important to consider the potential impacts on different system stakeholders, including utilities, policymakers, and solar installers. This paper describes an agent-based model that predicts the performance of different residential distributed solar models with respect to these stakeholders' objectives. In this model, consumer agents residing in an urban utility territory decide in each time-step whether they will adopt a particular renewable energy model, and the impacts of their adoption decisions on stakeholder performance metrics are captured over time. Simulation results suggest that if community solar program premium prices are set appropriately, all stakeholders can benefit: the utility can recover part of its revenue losses even as rooftop PV adoption increases, solar installers' businesses can thrive, and increased renewable energy adoption can be achieved equitably. The proposed modeling methodology can help to inform design decisions of distributed solar energy models that avoid benefiting some stakeholders at the unnecessary expense of others. • An agent-based model is developed to study solar adoption in the residential sector. • Consumer adoption behavior is studied for multiple solar-based energy models. • System-level approach with key energy stakeholders' objectives is considered. • Results show all stakeholders can benefit within a mutually beneficial arrangement. • Empirical examples are provided in support of the simulation results. [ABSTRACT FROM AUTHOR]

Objective: Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants.Background: Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models.Method: Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability.Results: The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base.Conclusion: Results suggest that social factors, such as desire to support the community, can be more important than financial factors.Application: An ABM of food hub dynamics, based on human factors data gathered from the field, can be a useful tool for policy decisions. Similar approaches can be used for modeling customer dynamics with other sustainable organizations. [ABSTRACT FROM AUTHOR]

The U.S. food supply system relies heavily on vertically-integrated food supply chains (FSCs), which leverage large-scale production, streamlined operations, and centralized planning and control to provide consumers with a consistent supply of food. However, these FSCs were seriously disrupted upon the outbreak of the COVID-19 pandemic in spring 2020. During the height of the crisis, they were slow to respond to production system failures and sudden and widespread changes in consumer demand. By contrast, many regionalized food supply chains (RFSCs) proved to be adaptive and responsive to changes in demand and delivery requirements, quickly pivoting to distribute products directly to consumers safely. The objective of this research is to explore how RFSCs can improve the resilience of the U.S. food supply system in the face of large-scale disruptions like the COVID-19 crisis. In particular, this research seeks to gain a greater understanding of how RFSCs can leverage logistics best practices for efficient and reliable distribution to consumers in normal times and during disasters. This study presents seven case studies of RFSCs in Texas and Iowa that adopted logistics best practices to enable them to provide their customers with convenient and safe purchasing mechanisms during the COVID-19 emergency. A description of how the strategies adopted by each participant promote the achievement of the United Nations Sustainable Development goals is provided. The successes experienced by these farmers and distributors at the height of the COVID-19 pandemic were a consequence of their willingness to adopt new distribution and logistics strategies. Collaboration among RFSC actors was a particularly effective strategy, as well as the adoption of scale-appropriate information and communication technologies, which helped to facilitate collaboration. Further, these case studies demonstrate how improved logistics performance allowed RFSCs to contribute to the health and well-being of their communities in a time of need. These case studies demonstrate the potential of RFSCs to support a resilient and socially-sustainable food system that communities can rely on, even in the face of a major disruption like COVID-19. The adoption of logistics best practices helped these RFSCs to develop new organizational strengths that will likely support sustainable development in their communities after the crisis ends. [Display omitted] • Case studies demonstrate regional food system resilience during the COVID-19 crisis. • Regional food system alignment with U.N. Sustainable Development Goals is described. • Farmers rapidly pivoted to new market channels using logistics best practices. • The importance of offering consumers convenient delivery options is emphasized. • Recommendations for maintaining sustainability in the long term are discussed. [ABSTRACT FROM AUTHOR]