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At least 631 records · Page 35

Hamilton: Flexible, Open Source $10 Wireless Sensor System for Energy Efficient Building Operation

Sensors for improving building performance are rapidly populating the market, driven in part by the drive to reduce greenhouse gas emissions resulting from energy production as well as improve the interior environment for healthy and more productive spaces. UC Berkeley has led wireless sensor development over the past 25 years (e.g., Telos mote), with the Hamilton (named after Alexander Hamilton on the US $10 bill) as the most recent. The Hamilton sensor was designed as a low-cost high-performance sensor that is modular and interoperable. The objective of the Hamilton project was to create, evaluate and establish the technological foundations for secure and easy to deploy building energy efficiency applications utilizing pervasive, low-cost wireless sensors integrated with traditional Building Management Systems (BMS), consumer-sector building components, and powerful data analytics. The project included iterative hardware design, incorporating a high-performance database (BTrDb, http://btrdb.io/), creating and iterating the development of secure data middleware (BOSSwave, WAVE/WAVEMQ), working with and pushing the development of an open-source tiny operating system RiotOS, and implementing and improving protocols such as Thread/OpenThread and TCP/IP. The hardware benefited from careful design to drive down the cost; the design included a System-on-a-Chip (SoC), chip antenna, single crystal and five passive components. Careful design of the operating system created a low-power design to enable a long life with small batteries. The hardware included several sensors: temperature, radiant temperature, relative humidity, magnetometer, accelerometer, and light, with an optional occupancy (Passive InfraRed) sensor. The project was the basis of several applications, both internal to the research team and other researchers and professionals at other institutions. Several applications used the sensor hardware as the basis for other complex devices. Other applications used the sensors to improve building performance through interoperating with the building Heating Ventilation and Air-Conditioning (HVAC) system, such as using occupancy and/or distributed temperature sensing to reduce HVAC zone energy while still providing thermal comfort and to reduce peak loads in small commercial buildings. We demonstrated cloud-based energy analytics, implemented a schedule and a Model Predictive Controller in a small commercial building to optimize HVAC energy, occupancy and electricity price. Initial integration of these technological innovations was performed through the creation of execution containers containing the WAVE agent and various driver, proxy, or building system function logic. The research added to the understanding of efficient sensor hardware, secure middleware, time-series data management (high performance database), efficient communication protocols, and interoperating with applications and building systems. The project showed the technical effectiveness and economic feasibility of creating a low-cost, modular, and easy-to-deploy sensor. Through conversations with multiple end users, the research team discovered that many customers wanted data management and services in addition to the sensors. HamiltonIOT developed packages of sensors, border router, and data services to provide a seamless “plug-and-play” sensor deployment. Some customers were willing to pay for higher quality sensors (such as light); some customers wanted a robust enclosure (waterproof).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-Energy Solid-State Lithium Batteries with Organic Cathode Materials (Final Report)

Organic materials made from abundant elements via low-energy processes are emerging as sustainable and low-cost alternatives to transition metal oxides as the electrode materials for high- energy batteries in the wake of supply chain and environmental issues associated with critical materials during the transition to clean energy. Organic insertion materials (OIMs) offer material- level energy comparable to transition metal oxides, but they have durability difficulties owing to dissolving in common liquid electrolytes. Combining ceramic-based solid electrolytes with organic electrode materials is one intriguing solution. The goal of this project is to design and synthesize high-energy OIMs, to understand the chemical dynamics and mechanical properties at the OIM-sulfide interface during electrochemical cycling, and to develop methods for constructing the optimum cathode microstructure, which will lead to improved electrochemical performance. The project team has accomplished the following over the last four years: (a) demonstrating that the mechanical softness of organic electrode materials is uniquely beneficial in suppressing crack formation at the electrode-electrolyte interface during cell operation; (b) understanding the interaction between cathode microstructure and the mechanical properties of individual components; and (c) establishing predictive control of cathode microstructure by tuning the mechanical properties of solid electrolytes and OIMs; (d) determining the chemical combability of sulfide electrolyte with high-energy OIMs and finally (f) laying out a road map toward a specific energy of 500 Wh kg -1 for solid-state lithium batteries. 14 publications resulted from this project.

25 ENERGY STORAGE↗

Real-Time Optimization Workflow Status Update

Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.

97 MATHEMATICS AND COMPUTING↗

Exploiting Task Tolerances in Mimicry-based Telemanipulation

We explore task tolerances, i.e., allowable position or rotation inaccuracy, as an important resource to facilitate smooth and effective telemanipulation. Task tolerances provide a robot flexibility to generate smooth and feasible motions; however, in teleoperation, this flexibility may make the user’s control less direct. In this work, we implemented a telema nipulation system that allows a robot to autonomously adjust its configuration within task tolerances. We conducted a user study comparing a telemanipulation paradigm that exploits task tolerances (functional mimicry) to a paradigm that requires the robot to exactly mimic its human operator (exact mimicry), and assess how the choice in paradigm shapes user experience and task performance. Our results show that autonomous adjustments within task tolerances can lead to performance improvements without sacrificing perceived control of the robot. Additionally, we find that users perceive the robot to be more under control, predictable, fluent, and trustworthy in functional mimicry than in exact mimicry.

42 ENGINEERING↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Community Resilience Through Rapid Restoration Leveraging Distributed Energy Resources (DERs) and Low-Cost Sensors

Equitable and automated bottoms-up power restoration following an extreme event will be demonstrated at a site in Puerto Rico. To do so, the team will develop enhanced grid situational awareness techniques integrating behind-the-meter (BTM) distributed energy resources (DER) discovery, impedance sweeping based outage boundary detection, and feasible restoration path identification algorithms. Resilience metric will be developed and incorporated along with situational awareness information in a distributed Model Predictive Control (MPC)-based restoration optimization algorithm to control and mobilize grid assets. These algorithms will be validated through power hardware-in-the-loop experiments and ultimately, a site demonstration to show that outage recovery time and total recovered load could be improved by >20% over the baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantification of Load Flexibility in Residential Buildings Using Home Energy Management Systems

With increasing penetration of renewable energy resources, the flexibility of operating behind-the-meter (BTM) resources plays a key role in enhancing grid reliability and resilience. Residential buildings with home energy management systems (HEMS) can provide desired flexibility for the distribution system operator (DSO) while considering customer comfort and preferences. This paper discusses a methodology to quantify the flexibility of BTM resources of residential buildings using HEMS. First, we propose a model predictive control framework to formulate the flexibility band comprising nominal, upper, and lower demand profiles. Second, the paper proposes a dispatch method for HEMS to compute the control signals for each BTM resource (e.g., air conditioner, water heater, home battery system) upon receiving a flexibility service request from the DSO. The case study provides insight into the flexibility provided at the whole-home level with different user preferences and seasons. The results demonstrate that HEMS is capable of providing flexibility service at the request of the DSO while delivering primary services to the building occupants.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗

Lawrence Berkley National Laboratory Building 59

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Lawrence Berkley National Laboratory Building 59 (Raw)

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management. Raw data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Lawrence Berkeley National Lab Building 59

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗

Digital Twin Applications in the Water Sector: A Review

As cities develop and resource demands rise, the water sector faces crucial challenges to deliver reliable, sustainable, and efficient services. Digital Twins (DTs), virtual replicas of physical systems, offer a promising tool to transform how we manage water infrastructure. Originally developed in the aerospace industry, DTs are now gaining traction in the water sector, enabling real-time monitoring, simulation, and predictive control of water and wastewater treatment, collection and distribution networks, and water reclamation and reuse systems. While still emerging in the water sector, DTs have shown potential to enhance operational efficiency, reduce environmental impacts, and support smarter, more resilient water management. This review study provides a comprehensive overview of current DT applications in the water sector, highlighting successful case studies, technical challenges, and knowledge gaps. It also explores how DTs can help bridge the water–energy nexus by optimizing resources utilized across interconnected systems. By synthesizing recent advances and identifying future research directions, this paper illustrates how DTs can play a central role in building sustainable, adaptive, and digitally-enabled water infrastructure.

digital twin↗

ATS-F spacecraft - An EMC challenge

The Applications Technology Satellite F (ATS-F) is the latest of a series of satellites for communications, scientific experiments, and data collection. The physical configuration of the spacecraft is examined along with operational characteristics and EMC management and control. Predicted and encountered problems are discussed, giving attention to wiring pick-up and reradiation, input rectification and bias off-set, intermodulation products, harmonics, component degradation, electroexplosive devices, spacecraft test complex vulnerability, and launch environment testing. Approaches used for locating the problems are considered and a description is given of the key factors and constraints in achieving EMC.

Kampinsky, A.↗

Integrated utility system design concept

Conceptual design studies are performed to investigate the feasibility of the MIUS concept as an alternate method of providing utility services to communities and/or community facilities having advantages over current practices. Procured and operated is a large scale testbed of the MIUS concept in order to evaluate and test those integrated system technical details that do not lend themselves to analysis. These include materials compatibility, process instrumentation and control, predictability of water and air effluents, techniques of heat recovery, method of thermal distribution, etc.

Hays, E. L.↗

Transonic small disturbances equation applied to the solution of two-dimensional nonsteady flows

Transonic nonsteady flows are of large practical interest. Aeroelastic instability prediction, control figured vehicle techniques or rotary wings in forward flight are some examples justifying the effort undertaken to improve knowledge of these problems is described. The numerical solution of these problems under the potential flow hypothesis is described. The use of an alternating direction implicit scheme allows the efficient resolution of the two dimensional transonic small perturbations equation.

Couston, M.↗