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At least 739 records · Page 41

Investigating the future supply distribution of industrial grade wood pellets in the global bioenergy market

This study analyzes the potential resource distribution in global competitive feedstock markets for industrial grade wood pellets. Based on historic trade patterns and expected future production and demand structures, a set of potential buyers and sellers of industrial grade wood pellets are simulated for 2022, 2030, and 2040. In contrast to previous trade modeling efforts, this study assumes a fully competitive market, i.e., excluding long-term contract arrangements, to show resource distributions under a potential future commodity market. This is done via a non-cooperative bi-level Stackelberg leader-follower game model. Of particular interest is the potential impact of international feedstock competition on the availability of US feedstock resources. The model results show that the main destinations for US wood pellet exports typically pay 10-20% more per tonne than the domestic market. The results show that domestic wood pellets are available to US industry at prices higher than the expected $88 per tonne delivered.

09 BIOMASS FUELS↗

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates↗

A Decentralized Market Mechanism for Energy Communities under Operating Envelopes

Here, we propose an operating envelopes (OEs) aware energy community market mechanism that dynamically charges/rewards its members based on two-part pricing. The OEs are imposed exogenously by a regulated distribution system operator (DSO) on the energy community's revenue meter and is subject to a generalized net energy metering (NEM) tariff design. By formulating the interaction of the community operator and its members as a Stackelberg game, we show that the proposed two-part pricing achieves a Nash equilibrium and maximizes the community's social welfare in a decentralized fashion while ensuring that the community's operation abides by the OEs. The market mechanism conforms with the cost-causation principle and guarantees community members a surplus level no less than their maximum surplus when they autonomously face the DSO. The dynamic and uniform community price is a monotonically decreasing function of the community's aggregate renewable generation. We also analyze the impact of exogenous parameters such as NEM rates and OEs on the value of joining the community. Lastly, through numerical studies, we showcase the community's welfare, and pricing, and compare its members' surplus to customers under the DSO's regime.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis of Solar Energy Aggregation Under Various Billing Mechanisms

Ongoing reductions in the cost of solar photovoltaic (PV) systems are driving increased installations by residential households. Various incentive programs such as feed-in tariff, net metering, net purchase, and sale that allow the prosumers to sell their generated electricity to the grid are also powering this trend. In this paper, we investigate sharing of PV systems among a community of households, who can also benefit further by pooling their production. Using cooperative game theory, we find conditions under which such sharing decreases their net total cost. We also develop allocation rules such that the joint net electricity consumption cost is allocated to the participants. These cost allocations are based on the cost causation principle. The allocations also satisfy the standalone cost principle and promote PV solar aggregation. Here, we also perform a comparative analytical study on the benefit of sharing under the mechanisms favorable for sharing, namely net metering, and net purchase and sale. The results are illustrated in a case study using real consumption data from a residential community in Austin, TX, USA.

14 SOLAR ENERGY↗

Impact of simultaneous activities on frequency fluctuations — comprehensive analyses based on the real measurement data from FNET/GridEye

Simultaneous human activities such as the Super Bowl game would cause certain impacts on frequency fluctuations in power systems. With the help of FNET/GridEye measurements, this work aims to give comprehensive analyses on the frequency fluctuations during Super Bowl LIV held on Feb. 2, 2020, so as to better understand several phenomena caused by simultaneous activities and help system operation and control. First, recent developments of FNET/GridEye are introduced briefly. Second, the frequency fluctuations of Eastern Interconnection (EI), western electricity coordinating council (WECC), and electric reliability council of Texas (ERCOT) power systems during Super Bowl LIV are analyzed. Third, frequency fluctuations of Super Bowl Sunday and ordinary Sundays in 2020 are compared. Finally, the differences of frequency fluctuations among different years during the Super Bowl and their change trend are also given. Furthermore, several possible explanations including the simultaneity of electricity consumption at the beginning of commercial breaks and the halftime show, the increasing usage of the Internet, and the increasing size of TV screens are illustrated in detail in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Idaho National Laboratory Site Environmental Surveillance Report: First Quarter 2022

This report for the first quarter of 2022 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and distant location environment, January 1 through March 31, 2022. All sample types (media) and the sampling schedule followed during 2022 are listed in Appendix A. This report contains results for the following sample types: • Air, including particulate air filters, charcoal cartridges, and atmospheric moisture, • Quarterly composites, • Precipitation, • Milk, and • Large game animals

99 GENERAL AND MISCELLANEOUS↗

Idaho National Laboratory Site Environmental Surveillance Program Report: Third Quarter 2022

This report for the third quarter of 2022 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and distant location environment, July 1 through September 30, 2022. All sample types (media) and the sampling schedule followed during 2022 are listed in Appendix A. This report contains results for the following sample types: • Air, including particulate air filters, charcoal cartridges, and atmospheric moisture, • Precipitation, • Milk, • Lettuce, • Grain, and • Large Game Animal Sampling.

99 GENERAL AND MISCELLANEOUS↗

Idaho National Laboratory Site Environmental Surveillance Program: Fourth Quarter 2022

This report for the fourth quarter of 2022 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s Onsite, Boundary and Offsite location environment, October 1 through December 31, 2022. All sample types (media) and the sampling schedule followed during 2022 are listed in Appendix A. This report contains results for the following sample types: • Air, including particulate air filters, charcoal cartridges, and atmospheric moisture, • Quarterly composites, • Precipitation, • Drinking and surface water, • Milk, • Potatoes, • Soil, • Large game animals, • Waterfowl, and • OSLDs.

99 GENERAL AND MISCELLANEOUS↗

Idaho National Laboratory Site Environmental Surveillance Program Report: First Quarter 2023

This report for the first quarter of 2023 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and offsite location environment, January 1 through March 31, 2023. All sample types (media) and the sampling schedule followed during 2023 are listed in Appendix A. This report contains results for the following sample types: •Air, including particulate air filters, charcoal cartridges, and atmospheric moisture •Quarterly composites •Precipitation •Milk •Large game animal sampling.

99 GENERAL AND MISCELLANEOUS↗

Idaho National Laboratory Site Environmental Surveillance Program Report: Third Quarter 2023

This report for the third quarter of 2023 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and offsite location environment, July 1 through September 30, 2023. All sample types (media) and the sampling schedule followed during 2023 are listed in Appendix A. This report contains results for the following sample types: (1) Air, including particulate air filters, charcoal cartridges, and atmospheric moisture; (2) Precipitation; (3) Surface water; (4) Milk; (5) Agricultural; and (6) Large game animal sampling.

54 ENVIRONMENTAL SCIENCES↗

Idaho National Laboratory Site Environmental Surveillance Program Report: Second Quarter 2023

This report for the second quarter of 2023 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s onsite, boundary and offsite location environment, April 1 through June 30, 2023. All sample types (media) and the sampling schedule followed during 2023 are listed in Appendix A. This report contains results for the following sample types: (1) Air, including particulate air filters, charcoal cartridges, and atmospheric moisture; (2) Precipitation; (3) Drinking/surface water; (4) Milk; (5) OSLDs; and (6) Large Game Animal Sampling.

54 ENVIRONMENTAL SCIENCES↗

A Blockchain and PKI-Based Secure Vehicle-to-Vehicle Energy-Trading Protocol

With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.

Stackelberg game↗

Spinning the Facts against Genetically Engineered Foods?

A signaling game is developed in order to derive the equilibrium conditions under which special interest groups (SIGs) involved in the controversial debate over genetically engineered (GE) foods have the incentive to truthfully reveal their information or spin facts regarding the health impact of GE foods. Consumers can choose to inspect information provided by SIGs at a cost. The risk of spinning facts is much higher for pro-GE groups, because if it turns out that a certain GE food is unsafe, the penalty will be severe. However, anti-GE groups can still spin facts at low risk even if consumers choose to inspect. This helps explain why some pro-GE groups, particularly the biotech industry, tend to remain silent. Revealing information regarding the safety of GE foods could be counterproductive given pre-existing public skepticism. Consumers may not make “better” decisions with more information provided because more information increases their inspection costs. When it is costlier for consumers to inspect, it is more likely that anti-GE groups will continue to spin facts about the negative health impact of GE foods.

59 BASIC BIOLOGICAL SCIENCES↗

Playing Nice Across Time and Space

Presentation will cover elements of modeling and simulation technologies, including game technologies, as applied to maturation of new and disruptive technologies.

technology development↗

A Survey of Mathematical Structures for Lunar Networks

To sustain the current and increasing accessibility of space, a scalable communications infrastructure (i.e. the Solar System Internet, SSI) is necessary. The goal of this paper is to begin the discovery of the fundamental underlying mathematical structure of space networks to help the research community harness these structures for algorithm development and optimization. To ensure the applicability of the research, the approaches are considered through the lens of simulated scenarios inspired by the Artemis Back-to-the-Moon mission set for 2024. We note that any approach to an SSI must fit under the umbrella of Delay Tolerant Networking (DTN), due to celestial mobility, high link latencies, high variance in link latencies, disconnections, lack of end-to-end paths, and so on. These difficulties are exacerbated by the fact that the underlying structure of a space network is a time-evolving network and may experience multiple discontinuities in its topology. In this paper we propose several novel approaches to a mathematical foundation for Delay Tolerant Networking Theory that fall outside the traditional scope of temporal network theory. These techniques include methods from Topological Data Analysis, Dynamic Graph Analysis, Applied Algebraic Geometry, Probability Theory, and Game Theory. Some of these methods include tools adapted to the study of dynamic metric spaces, such as zigzag persistent homology and their higher parameter analogs. We find that several of these methods target desired engineering outcomes such as discovery and automatic sub-netting. While each approach is theoretical, they are also algorithmic in nature and offer immediate practical applications. The paper concludes with comparisons of the various methods along with suggestions for future work.

Delay tolerant networking↗

Cooperative Clustering Techniques For Space Network Scalability

Routing in the space internet must face many unique challenges - from unplanned disconnections and interruptions to predictable intermittent connectivity due to high network mobility and long propagation delays. NASA’s current approach to such routing is Contact Graph Routing (CGR), using a graph formed of prescheduled communication contacts to compute routes through the network. While this approach manages to tackle issues of connectivity and propagation delays, it is a global approach that requires continuous knowledge of the entire network. In a potential future Solar Space Internet (SSI) such an approach on its own cannot scale to large networks with thousands of members. In this paper we propose clustering as a solution to CGR scalability. Clustering has been used in many networking problems as a way to subdivide the network and allow for localized routing and better scalability. Using techniques from graph theory and game theory, we explore various existing clustering algorithms and adapt them to the Contact Graph Routing setting. We propose a way to combine multiple algorithms to create a Delay Tolerant Clustering Protocol (DTCP). In addition, we explore the underlying networking mechanisms such as multicast, neighbor discovery, and software defined networking that may be used to enable DTCP.

Delay Tolerant Networking↗

The Kalai-Smorodinsky solution for many-objective Bayesian optimization

An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations, recovering the set of optimal compromise solutions generally requires numerous observations and is less interpretable since this set tends to grow larger with the number of objectives. We thus propose to focus on a specific solution originating from game theory, the Kalai-Smorodinsky solution, which possesses attractive properties. In particular, it ensures equal marginal gains over all objectives. We further make it insensitive to a monotonic transformation of the objectives by considering the objectives in the copula space. A novel tailored algorithm is proposed to search for the solution, in the form of a Bayesian optimization algorithm: sequential sampling decisions are made based on acquisition functions that derive from an instrumental Gaussian process prior. Our approach is tested on four problems with respectively four, six, eight, and nine objectives. The method is available in the R package GPGame available on CRAN at https://cran.r-project.org/package=GPGame.

Game theory↗

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗