The energy supply security pyramid: A quantitative framework for planning and policy making
Not Available
Sulzer, Matthias (ORCID:0000000320942460)↗
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Results for “Policy Making”
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Method and apparatus for constructing informative outcomes to guide multi-policy decision making
In Multi-Policy Decision-Making (MPDM), many computationally-expensive forward simulations are performed in order to predict the performance of a set of candidate policies. In risk-aware formulations of MPDM, only the worst outcomes affect the decision making process, and efficiently finding these influential outcomes becomes the core challenge. Recently, stochastic gradient optimization algorithms, using a heuristic function, were shown to be significantly superior to random sampling. In this disclosure, it was shown that accurate gradients can be computed-even through a complex forward simulation—using approaches similar to those in dep networks. The proposed approach finds influential outcomes more reliably, and is faster than earlier methods, allowing one to evaluate more policies while simultaneously eliminating the need to design an easily-differentiable heuristic function.
Olson, Edwin↗
Why Terminology Matters for Successful Rollout of Carbon Dioxide Utilization Technologies
To realize their full sustainability potential, carbon dioxide utilization technologies (carbon capture and utilization/CCU) presently require policy support. Consequently, they require acceptance among a variety of stakeholders in industry, policy making, and in the public sphere alike. While CO 2 utilization is already a topic of discourse among these stakeholders, there is a lack of common terminology to describe such technologies. On the contrary: The present article shows that terminology in the field of CO 2 utilization technologies is currently used inconsistently, and that different designations such as CCU, CCUS, or CDR convey different meanings and contexts. These ambiguities may cause communication problems with regard to policy making, funding proposals, and especially in public discourse. In order to initiate and accompany a goal-oriented and knowledge-based debate on CO 2 utilization technologies in the future, actors in the field are asked to question their own choices of terminology and to assess its accuracy. Acronyms and technical abbreviations are the chief cause of potential misunderstandings, and so should be avoided whenever possible or else include a brief explanation. Consistent and precise use of terminology will facilitate transparent dialogue concerning CO 2 utilization in the future.
54 ENVIRONMENTAL SCIENCES↗
Developing a common approach for classifying building stock energy models
Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
How churches make education policy: the churchification of Hungarian education and the social question under religious populism
Not Available
Neumann, Eszter (ORCID:0000000219154769)↗
Defining pathways to healthy sustainable urban development
Goals and pathways to achieve sustainable urban development have multiple interlinkages with human health and wellbeing. However, these interlinkages have not been examined in depth in recent discussions on urban sustainability and global urban science. This paper fills that gap by elaborating in detail the multiple links between urban sustainability and human health and by mapping research gaps at the interface of health and urban sustainability sciences. As researchers from a broad range of disciplines, we aimed to: 1) define the process of urbanization, highlighting distinctions from related concepts to support improved conceptual rigour in health research; 2) review the evidence linking health with urbanization, urbanicity, and cities and identify cross-cutting issues; and 3) highlight new research approaches needed to study complex urban systems and their links with health. This novel, comprehensive knowledge synthesis addresses issue of interest across multiple disciplines. Our review of concepts of urban development should be of particular value to researchers and practitioners in the health sciences, while our review of the links between urban environments and health should be of particular interest to those outside of public health. We identify specific actions to promote health through sustainable urban development that leaves no one behind, including: integrated planning; evidence-informed policy-making; and monitoring the implementation of policies. We also highlight the critical role of effective governance and equity-driven planning in progress towards sustainable, healthy, and just urban development.
54 ENVIRONMENTAL SCIENCES↗
Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making
One of the great challenges with decision making tasks on real world systems is the fact that data is sparse and acquiring additional data is expensive. In these cases, it is often crucial to make a model of the environment to assist in making decisions. At the same time, limited data means that learned models are erroneous, making it just as important to equip the model with good predictive uncertainties. In the context of learning sequential decision making policies, these uncertainties can prove useful for informing which data to collect for the greatest improvement in policy performance \citep{mehta2021experimental, mehta2022exploration} or informing the policy about unsure regions of state and action space to avoid during test time \citep{yu2020mopo}. Additionally, assuming that realistic samples of the environment can be drawn, an adaptable policy can be trained that attempts to make optimal decisions for any given possible instance of the environment \citep{ghosh2022offline, chen2021offline}. In this work, we examine the so-called ``probabilistic neural network'' (PNN) model that is ubiquitous in model-based reinforcement learning (MBRL) works. We argue that while PNN models may have good marginal uncertainties, they form a distribution of non-smooth transition functions. Not only are these samples unrealistic and may hamper adaptability, but we also assert that this leads to poor uncertainty estimates when predicting multiple step trajectory estimates. To address this issue, we propose a simple sampling method that can be implemented on top of pre-existing models.We evaluate our sampling technique on a number of environments, including a realistic nuclear fusion task, and find that, not only do smooth transition function samples produce more calibrated uncertainties, but they also lead to better downstream performance for an adaptive policy.
Offline Reinforcement Learning↗
Decision-support and Emissions Prediction Interactive Cities Tool
The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building–integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials. Information about all the developers
Ravache, Baptiste↗
The Study of Environmental Arctic Change (SEARCH) Arctic Futures 2050 Conference. Final Report
The Arctic Futures 2050 Conference was designed as a novel convening of Arctic scientists, Indigenous people, and decision makers, including policy makers at all levels of government. The conference was held 4–6 September 2019 in Washington, D.C. and gathered nearly 400 participants to explore six questions: What do we know, and what do we need to know about the Arctic—and why does it matter? What challenges confront policy makers in the rapidly changing Arctic? What basic research is needed to inform responses to Arctic change? What applied research is needed to inform responses to change? What tools can facilitate informing policy making with science and Indigenous knowledge? What opportunities exist for partnerships between policy makers and scientists? A conference report (see: https://www.searcharcticscience.org/arctic-2050/conference-2019/products) detailed all conference discussions. The main conference conclusion was that holistic understanding and useful adaptation to rapid Arctic change requires bringing together scientists, Indigenous Knowledge holders, and policy makers in all phases of defining the problems, conducting research, and sharing knowledge.
54 ENVIRONMENTAL SCIENCES↗
The Energizer Bunny: Dual-Use Photovoltaic and Pasture-Raised Rabbit Farms (Final Report)
This case study project lays the groundwork for the broader realization of agrivoltaics by considering the techno-economic, environmental, and social aspects of system development and assessing a novel rabbit-based concept. Research on the social and political barriers to agrivoltaic development is sparse, which emphasizes the importance of this project as it provides key insight into the consequential socio-political challenges that may hinder the diffusion of agrivoltaic technology. Additionally, the rabbit agrivoltaic concept is novel and has not been applied in experimental or commercial applications to date. This project advances our understanding of the viability of this co-location scheme through empirical assessment of integrating grazing rabbits with solar. A total of five manuscripts (3 published in peer-reviewed journals, 2 under review) have resulted from this project. The techno-economic component of the project included a) a pilot test study investigating the feasibility of the rabbit agrivoltaic concept and b) an economic analysis of the advantages available to solar operators who leverage grazing animals for lawn maintenance and a dual-revenue stream. Our calculations indicate that the co-location of solar and rabbit farms is a viable form of agrivoltaics, increasing overall site revenue by 2.5%-24.0% above projected electricity revenue. The environmental component of the project entailed an ISO 14040 and 14044 compliant life cycle assessment to quantify the impacts of the rabbit agrivoltaic concept. The results indicate pasture-based agrivoltaic systems provide a dual synergy that produces 69.3% less emissions and demands 82.9% less fossil energy per functional unit of cumulative MWh output of electricity and cumulative kg of meat compared to non-integrated production. The social component of the project included conducting two separate interview studies with agriculture and solar industry professionals and the distribution of a public survey. The interview findings identify the key socio-political opportunities for agrivoltaics include: the retention of agricultural land and rural interests, and increased local level acceptance of solar development. The key barriers to agrivoltaics include: ensuring long term agricultural productivity is not compromised, and subnational zoning strategies. The survey results indicate that support for local solar projects increase by 10% when an agricultural function is incorporated. Survey respondents prefer agrivoltaic projects that are a) designed to provide economic opportunities for farmers and the local community b) located on private property or existing agricultural land, and c) do not threaten local interests. Cumulatively, this project can inform agrivoltaic decision making, solar development practices, rabbit-based applications, land use management, and policy making in a way that supports the furtherance of the renewable energy transition, conserves arable land, and utilizes innovative solar photovoltaic technologies.
14 SOLAR ENERGY↗
Next-Generation Reverse Logistics Networks of Photovoltaic Recycling: Perspectives and Challenges
With the growing adoption of solar energy as a key component of the global energy transition and its new industrial policy (the Inflation Reduction Act and others), the United States is witnessing a significant increase in solar investments. This surge in installations and domestic and reshored manufacturing of solar photovoltaic (PV) panels brings with it a pressing issue: the proper management of end-of-life (EoL) PV panels. As these panels are decommissioned, either due to reaching the end of their lifespans or due to breakage across the various stages of the forward supply chain, it becomes crucial to establish efficient reverse supply chain logistics systems to address the challenges associated with their disposal, while also unlocking the value of the inherent materials that are of critical value for other forward supply chains. This perspective article examines the challenges regarding EoL PV panels and relevant reverse supply chain and logistics networks, and proposes future research directions based on the gaps observed among academic research, industry, and policy-making challenges. We identify the main bottlenecks and hurdles including, among others, the lack of supportive regulations and absence of structured, optimized recycling infrastructure. To this end, it is proposed that the key to achieving a sustainable reverse supply chain network for solar PV panels lies in relentless end-to-end supply chain cost optimization efforts supported by enabling policies. Moreover, it is proposed that designing systematic decision-making modeling frameworks is vital for examining different possibilities and scenarios for state, region or nation-wide optimization of solar PV reverse supply chain networks. Indicative to this effect, we discuss the development of a Resource-Task-Network (RTN)-based model and demonstrate its application and benefits through a case study. We wrap up with conclusions and future research directions.
circular economy↗
PoliMOR
PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.
Brumgard, Christopher↗
Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing
Highlights: • We combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. • Beijing is selected as a case study. • Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. • Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.
54 ENVIRONMENTAL SCIENCES↗
Solar PV on U.S. Houses of Worship: Overview of Market Activity and Trends [Slides]
Rooftop solar photovoltaic systems on houses of worship can provide unique community benefits and can raise local awareness and acceptance of solar energy. Recognizing that potential, a stakeholder team selected under DOE’s Solar Energy Innovation Network is working to develop a scalable model for recruiting and installing solar PV on houses of worship in underserved communities. Berkeley Lab is providing analytical support to this stakeholder team through several work products, including this report, which provides a data-oriented overview of market activity and trends related to solar PV installations on U.S. houses of worship (HoW). Drawing on Berkeley Lab’s project-level dataset of U.S. solar PV installations, the report describes: -market size and growth trends for PV on HoW -demographic characteristics of the communities in which HoW with PV are located, including income, race and ethnicity, and educational levels -key characteristics of the PV systems installed on HoW, including system size, installed costs, prevalence of third-party ownership, and pairing with storage -characteristics of the installer network servicing PV installations on HoW The purpose of the market overview is to inform business development and policy-making efforts aimed at supporting solar adoption by HoW.
14 SOLAR ENERGY↗
Transmission Interface Limits for High-Spatial Resolution Capacity Expansion Modeling
Large-scale capacity expansion models typically rely on estimates of the power transfer limits between modeled zones. Accurate estimation of these interface transfer limits (ITLs) requires modeling the underlying transmission network. Here we expand on a maximum flow optimization method that uses linearized power flow to estimate transfer limits. We apply this method to a data set of the U.S. transmission network to estimate ITLs between U.S. counties. By calculating ITLs using different subsets of the network, we evaluate how the size of the network used in the estimation affects the results. The results show diminishing returns to ITL accuracy after six hops, suggesting that a network subset can reasonably be used to approximate ITLs. The county-level estimates produced in this study will support more spatially resolved capacity expansion modeling and will help inform policy making at local and national levels.
capacity planning↗
Applying a science‐based systems perspective to dispel misconceptions about climate effects of forest bioenergy
Abstract The scientific literature contains contrasting findings about the climate effects of forest bioenergy, partly due to the wide diversity of bioenergy systems and associated contexts, but also due to differences in assessment methods. The climate effects of bioenergy must be accurately assessed to inform policy‐making, but the complexity of bioenergy systems and associated land, industry and energy systems raises challenges for assessment. We examine misconceptions about climate effects of forest bioenergy and discuss important considerations in assessing these effects and devising measures to incentivize sustainable bioenergy as a component of climate policy. The temporal and spatial system boundary and the reference (counterfactual) scenarios are key methodology choices that strongly influence results. Focussing on carbon balances of individual forest stands and comparing emissions at the point of combustion neglect system‐level interactions that influence the climate effects of forest bioenergy. We highlight the need for a systems approach, in assessing options and developing policy for forest bioenergy that: (1) considers the whole life cycle of bioenergy systems, including effects of the associated forest management and harvesting on landscape carbon balances; (2) identifies how forest bioenergy can best be deployed to support energy system transformation required to achieve climate goals; and (3) incentivizes those forest bioenergy systems that augment the mitigation value of the forest sector as a whole. Emphasis on short‐term emissions reduction targets can lead to decisions that make medium‐ to long‐term climate goals more difficult to achieve. The most important climate change mitigation measure is the transformation of energy, industry and transport systems so that fossil carbon remains underground. Narrow perspectives obscure the significant role that bioenergy can play by displacing fossil fuels now, and supporting energy system transition. Greater transparency and consistency is needed in greenhouse gas reporting and accounting related to bioenergy.
54 ENVIRONMENTAL SCIENCES↗
Overcoming barriers to improved decision-making for battery deployment in the clean energy transition
Decarbonization plans depend on the rapid, large-scale deployment of batteries to sufficiently decarbonize the electricity system and on-road transport. This can take many forms, shaped by technology, materials, and supply chain selection, which will have local and global environmental and social impacts. Current knowledge gaps limit the ability of decision-makers to make choices in facilitating battery deployment that minimizes or avoids unintended environmental and social consequences. These gaps include a lack of harmonized, accessible, and up-to-date data on manufacturing and supply chains and shortcomings within sustainability and social impact assessment methods, resulting in uncertainty that limits incorporation of research into policy making. These gaps can lead to unintended detrimental effects of large-scale battery deployment. To support decarbonization goals while minimizing negative environmental and social impacts, we elucidate current barriers to tracking how decision-making for large-scale battery deployment translates to environmental and social impacts and recommend steps to overcome them.
25 ENERGY STORAGE↗