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Wu, Di

Publications and source records attributed to Wu, Di.

At least 55 records · Page 3
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DOE OSTI2022

Optimal Coordination of Distributed Energy Resources Using Deep Deterministic Policy Gradient

Recent studies showed that reinforcement learning (RL) is a promising approach for coordination and control of distributed energy resources (DER) under uncertainties. Many existing RL approaches, including Q-learning and approximate dynamic programming, are based on lookup table methods, which become inefficient when the problem size is large and infeasible when continuous states and actions are involved. In addition, when modeling battery energy storage system (BESS), the loss of life is not reasonably considered into the decision-making process. This paper proposes an innovative deep RL method for DER coordination considering BESS degradation. The proposed deep RL is designed based on an adaptive actor-critic architecture and employs an off-policy deterministic policy gradient method for determining the dispatch operation that minimizes the operation cost and BESS life loss. Case studies were performed to validate the proposed method and demonstrate the effects of incorporating degradation models into control design.

Das, Avijit↗
DOE OSTI2022

Molecular basis for antiviral activity of two pediatric neutralizing antibodies targeting SARS-CoV-2 Spike RBD

Neutralizing antibodies (NAbs) hold great promise for clinical interventions against SARS-CoV-2 variants of concern (VOCs). Understanding NAb epitopedependent antiviral mechanisms is crucial for developing vaccines and therapeutics against VOCs. Here we characterized two potent NAbs, EH3 and EH8, isolated from an unvaccinated pediatric patient with exceptional plasma neutralization activity. EH3 and EH8 cross-neutralize the early VOCsandmediatestrong Fc-dependent effector activity in vitro. Structural analyses of EH3 and EH8 in complex with the receptor-binding domain (RBD) revealed the molecular determinantsoftheepitope-drivenprotectionandVOCevasion.WhileEH3represents the prevalent IGHV3-53 NAb whose epitope substantially overlaps with the ACE2 binding site, EH8 recognizes a narrow epitope exposed in both RBD-up and RBD-down conformations. When tested in vivo, a single-dose prophylactic administration of EH3 fully protected stringent K18-hACE2 micefrom lethal challenge with Delta VOC. Our study demonstrates that protective NAbs responses converge in pediatric and adult SARS-CoV-2 patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells toward optimal system-level performance. An optimal power management approach is developed to extensively exploit the merits of the proposed design. Based on receding-horizon convex optimization, this approach aims to minimize the total power losses in charging/discharging while allocating the power in line with each cell’s condition to achieve state of-charge (SoC) and temperature balancing. By appropriate design, the approach manages to regulate the power of a cell across its full SoC range and guarantee the feasibility of the optimization problem. Here, we perform extensive simulations and further develop a lab-scale prototype to validate the proposed system design and power management approach.

25 ENERGY STORAGE↗
DOE OSTI2022

Evaluating Grid Strength under Uncertain Renewable Generation

The increasing displacement of synchronous generators with renewable resources such as wind and solar via power electronic interfaces causes a reduction in short-circuit strength and weak grid issues. The variation and uncertainty of renewable energy increase challenges for identifying weak grid conditions. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses the probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce computational burden without compromising result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.

grid strength↗
DOE OSTI2022

Predicting peak day and peak hour of electricity demand with ensemble machine learning

Battery energy storage systems can be used for peak demand reduction in power systems, leading to significant economic benefits. Two practical challenges are 1) accurately determining the peak load days and hours and 2) quantifying and reducing uncertainties associated with the forecast in probabilistic risk measures for dispatch decision-making. In this study, we develop a supervised machine learning approach to generate 1) the probability of the next operation day containing the peak hour of the month and 2) the probability of an hour to be the peak hour of the day. Guidance is provided on preparation and augmentation of data as well as selection of machine learning models and decision-making thresholds. The proposed approach is applied to the Duke Energy Progress system and successfully captures 69 peak days out of 72 testing months with a 3% exceedance probability threshold. On 90% of the peak days, the actual peak hour is among the 2 h with the highest probabilities.

25 ENERGY STORAGE↗
DOE OSTI2022

An Efficient Distributed Reinforcement Learning for Enhanced Multi-Microgrid Management

Economic dispatch in multi-microgrid (MMG) systems requires coordinating distributed energy resources (DERs) of different microgrids, which leads to a significant increase in the number of states for energy management. In these cases, traditional reinforcement learning (RL) approaches become computationally expensive or output a solution that causes extra-operating costs for the system. This paper proposes an RL approach that employs local learning agents to interact with microgrid environments in a distributed manner and aggregates the outcomes to train the global agent to learn the policy for the MMG system. This distributed exploration and aggregation process provides an effective solution and guides the global agent to learn the dispatch policy efficiently. Case studies are performed on a system with three microgrids with different types of DERs. Results obtained using the proposed RL and comparisons with conventional methods substantiate the effectiveness of the proposed approach in terms of operation costs, computation time, and peak-to-average ratio.

Das, Avijit↗
DOE OSTI2022

Energy Northwest – Horn Rapids Solar and Storage: A Techno-economic Assessment

In 2017, as part of the second round of funding from the Washington State Clean Energy Fund, the Washington State Department of Commerce granted up to $\$3$ million in matching funds to develop an estimated $6.5 million project that deployed a 4-MW, 20-acre solar generating array of photovoltaic (PV) panels coupled with a 1 MW/4 MWh (nameplate capacity) lithium-iron-phosphate battery energy storage system (BESS) in Richland, Washington. The combination of PV and BESS will provide a predictable, renewable generating source and will also serve as a training ground for solar and battery technicians throughout the nation. This report documents the techno-economic assessment of the integrated system, including the definition of use cases and applications, collection and preparation of data and input parameters, development of modeling and optimization methods, case studies, and analysis results.

14 SOLAR ENERGY↗
DOE OSTI2022

Engineered ACE2-Fc counters murine lethal SARS-CoV-2 infection through direct neutralization and Fc-effector activities

Soluble angiotensin-converting enzyme 2 (ACE2) constitutes an attractive antiviral capable of targeting a wide range of coronaviruses using ACE2 as their receptor. Using structure-guided approaches, we developed a series of bivalent ACE2-Fcs harboring functionally and structurally validated mutations that enhance severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain recognition by up to ~12-fold and remove angiotensin enzymatic activity. The lead variant M81 potently cross-neutralized SARS-CoV-2 variants of concern (VOCs), including Omicron, at subnanomolar half-maximal inhibitory concentration and was capable of robust Fc-effector functions, including antibody-dependent cellular cytotoxicity, phagocytosis, and complement deposition. When tested in a stringent K18-hACE2 mouse model, Fc-enhanced ACE2-Fc delayed death by 3 to 5 days or effectively resolved lethal SARS-CoV-2 infection in both prophylactic and therapeutic settings via the combined effects of neutralization and Fc-effector functions. These data add to the demonstrated utility of soluble ACE2 as a valuable SARS-CoV-2 antiviral and indicate that Fc-effector functions may constitute an important component of ACE2-Fc therapeutic activity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Optimal operation and sizing of pumped thermal energy storage for net benefits maximization

Abstract Current trends in the modern grid are leading to the development and deployment of energy storage to help integrate increasing variable renewable energy sources into the grid. This paper studies a pumped thermal energy storage (PTES) system for multiple grid services including energy arbitrage, frequency regulation, spinning and non‐spinning reserve, and resource adequacy. Optimal dispatch methods are proposed for individual services as well as value stacking from multiple services to maximize the economic benefits. Assessment results demonstrate the superiority of value stacking. Specifically, the study shows the maximum revenue from an individual grid service with a 30‐MWh PTES system was $522,520, while the value stacking could increase the benefits to $678,477. In addition, sensitivity analyses were conducted to explore the cost‐effectiveness of a PTES system with different combinations of power transfer limits and energy capacity. It was found that the power transfer limit had a greater impact than the energy capacity on the benefits. The proposed method could help determine the optimal duration of a future PTES system.

25 ENERGY STORAGE↗
DOE OSTI2022

Nontechnical Barriers to Geothermal Development

Geothermal energy presents a significant opportunity for the United States (US). The US has the largest known geothermal resource in the world, with over 31 GW of conventional geothermal (i.e., hydrothermal) potential. Despite this, the development of geothermal power plants has lagged other renewable resources. Though some of the gaps stem from technical barriers numerous non-technical barriers are preventing geothermal energy from reaching its full potential. The gaps include a need to reduce the cost impacts of seismic risk, environmental risk, exploration, drilling and permitting cost risk, and reduced summer capacity on plant profitability. This report identifies pathways to overcome these barriers. We find that geothermal energy could increase its market presence by acting as a complement to lower cost renewables, providing flexible or baseload power in low carbon scenarios. We also outline several contractual and operational strategies (including the use of hybrid systems) that plant operators can pursue to improve the value of their resource, such as multi part remuneration mechanisms that guarantee revenue (e.g., availability payments or a Contract for Differences approach) or resource risk hedging approaches (e.g., shaped market products and portfolio resource approaches).

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Avista’s Shared Energy Economy Model Pilot: A Techno-economic Assessment

As part of the second round of the Washington Clean Energy Fund, Avista Corp received a $3.5 million matching grant in support of a shared energy economy project to test the integration of energy assets–from rooftop solar and battery storage to building energy management systems–that can be shared and used for multiple purposes. The goal of this project is to demonstrate how both the customer and the utility can benefit from this shared energy economy model and demonstrate that the electric grid can become more reliable, efficient, resilient, and flexible. Pacific Northwest National Laboratory was engaged by the U.S. Department of Energy and the Washington State Department of Commerce to work with Avista in assessing the benefits of the shared energy economy model. This report documents the techno-economic assessment of the shared energy economy model, including the definition of use cases and applications, collection and preparation of data and input parameters, development of modeling and optimization methods, and case studies and analysis results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Unconventional excitonic states with phonon sidebands in layered silicon diphosphide

Complex correlated states emerging from many-body interactions between quasiparticles (electrons, excitons and phonons) are at the core of condensed matter physics and material science. In low-dimensional materials, quantum confinement affects the electronic, and subsequently, optical properties for these correlated states. Here, by combining photoluminescence, optical reflection measurements and ab initio theoretical calculations, we demonstrate an unconventional excitonic state and its bound phonon sideband in layered silicon diphosphide (SiP 2 ), where the bound electron–hole pair is composed of electrons confined within one-dimensional phosphorus–phosphorus chains and holes extended in two-dimensional SiP 2 layers. The excitonic state and emergent phonon sideband show linear dichroism and large energy redshifts with increasing temperature. Our ab initio many-body calculations confirm that the observed phonon sideband results from the correlated interaction between excitons and optical phonons. With these results, we propose layered SiP2 as a platform for the study of excitonic physics and many-particle effects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Energy Storage Valuation: A Review of Use Cases and Modeling Tools

An enticing prospect that drives adoption of energy storage systems (ESS) is its ability to be used in a diverse set of use cases and the potential to take advantage of multiple unique value streams. The Energy Storage Grand Challenge (ESGC) technology development pathways for storage technologies draw from a set of use cases in the electrical power system, each with their own specific cost and performance needs. In addition to the need for cost and performance improvements for storage technologies, there a need for robust valuation methods to enable effective policy, investment, business models, and resource planning. There are numerous storage valuation tools available to the public, many of which can analyze the value of an ESS project with inputs and characteristics that reflect a specific storage use case. To effectively reach ESS stakeholders that may be interested in learning about valuation models, this report will draw from publicly available tools developed by the Department of Energy (DOE) and frame their functionalities and capabilities within the context of three distinct use case families. This report examines three of the ESGC use case families in depth and provides a methodology in which interested stakeholders can determine which DOE modeling tool is best suited to value ESS for their specific case. The high-level objectives for this report include: (1) Provide specific sub use-cases for each use case family for further characterization; (2) Provide technical parameters and relevant data for three example use cases that could be used in a valuation tool; (3) Identify a list of publicly available DOE tools that can provide energy storage valuation insights for ESS use case stakeholders; (4) Provide information on the capabilities and different options in each modeling tool; (5) Make conclusions on which are best suited for valuing certain functional/performance requirements and which tools might be applicable to other use cases; and (6) Show the methodology that informs a Model Selection Platform (MSP) framework that educates stakeholders on different DOE models and provides a streamlined way to choose the right model that most closely matches their needs.

25 ENERGY STORAGE↗
DOE OSTI2022

Energy Northwest - Horn Rapids Solar and Storage: An Assessment of Battery Technical Performance

Chartered in 1957 as a joint action agency of the state, Energy Northwest (ENW) is a consortium of 27 public utility districts and municipalities across Washington state. ENW takes advantage of economies of scale and shared services to help utilities run their operations more efficiently and at lower cost, to the benefit of more than 1.5 million customers. ENW develops, owns, and operates a diverse mix of electricity generating resources, including hydro, solar, and wind projects – and the Northwest’s only active nuclear energy facility. These projects provide enough reliable, affordable, and environmentally responsible energy to power more than a million homes each year, and that carbon-free electricity is provided at the cost of generation. The agency continually explores new generation projects to meet its members’ needs. In 2017, as part of the second round of funding from the Washington state Clean Energy Fund, the Washington State Department of Commerce granted up to $3 million in matching funds to develop an estimated $6.5 million project that deployed a 4-MW, 20-acre solar generating array of photovoltaic (PV) panels coupled with a 1 MW/5.5 MWh lithium-iron-phosphate battery energy storage system (BESS) in Richland, Washington. The combination of PV and BESS will provide a predictable, renewable generating source and will also serve as a training ground for solar and battery technicians throughout the nation. The City of Richland will purchase the power from the project and utilize the benefits of the energy storage. The project provides Washington state with its first opportunity to integrate a large-scale solar and storage facility into its clean mix of hydro, nuclear, and wind resources. This first-of-its-kind facility combines solar generation with battery storage and technician training. In 2019, Pacific Northwest National Laboratory (PNNL) worked with ENW to assess the integrated PV and BESS in representative use cases that could benefit the City of Richland. Between March and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (A) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline), and they are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (B) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with ENW. Five use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) transmission charge reduction, 4) Volt-VAR service, and 5) outage mitigation. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help ENW understand the performance of the Horn Rapids BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗