M. A. Piette

University of California, Berkeley | UCB · Lawrence Berkeley Laboratory

Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting bo...

Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure th...

This paper presents the curation of a monitored dataset from an office building constructed in 2015 in Berkeley, California. The dataset includes whole-building and end-use energy consumption, HVAC system operating conditions, indoor and outdoor environmental parameters, and occupant counts. The data were collected during a period of three years fr...

Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the ur...

Although the thermal mass of floors in buildings has been demonstrated to help shift cooling load, there is still a lack of information about how floor covering can influence the floor’s load shifting capability and buildings’ demand flexibility. To fill this gap, we estimated demand flexibility based on the daily peak cooling load reduction for di...

Accurate electricity demand forecasts that account for impacts of extreme weather events are needed to inform electric grid operation and utility resource planning, as well as to enhance energy security and grid resilience. Three common data-driven models are used to predict city-scale daily electricity usage: linear regression models, machine lear...

The evaluation of natural ventilation potential for cooling indoor spaces during the early design phases is of great interest to researchers and practitioners. Among various definitions and usages for natural ventilation potential (NVP) in early design evaluation, this paper reviews and identifies the key performance indicators, and proposes two ne...

This paper optimizes opening positions on building facades to maximize the natural ventilation’s potential for ventilation and cooling purposes. The paper demonstrates how to apply computational fluid dynamics (CFD) simulation results to architectural design processes, and how the CFD-driven decisions impact ventilation and cooling: (1) background:...

Thermal adaptation in low-income housing of Mumbai, India is investigated using a longitudinal field study and in-situ field measurements. 705 set of responses from two different neighbourhoods were analysed to understand the patterns of behavioural adaptation. Spatial configuration, temporal factors and underlying societal norms influenced the com...

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building therma...

There is growing interest in city and community scale energy efficiency goals across the US and around the world [1]. Forward thinking developers are expressing interest in developing methods to track the actual operations of new urban developments and campuses. Local governments and developers are exploring how to ensure that the built infrastruct...

Predictive control has gained increasing attention for its ability to reduce energy consumption and improve occupant comfort in buildings. The plug loads prediction is a key component for the predictive building controls, as plug loads is a major source of internal heat gains in buildings. This study proposed a novel method to apply the Long-Short-...

An important approach to curtail building energy consumption is to optimize building control based on occupancy information. Various studies proposed to estimate occupant counts through different approaches and sensors. However, high cost and privacy concerns remain as major barriers, restricting the practice of occupant count detection. In this st...

This report describes research to characterize the status of, and trends in, big-data analytics for the electricity grid. The research focused on 1) identifying power-grid big-data sources, types, and characteristics; and 2) characterizing big-data architecture, analytic methods, technology applications, and challenges. The first part of this repor...

Heating, Ventilation, and Air Conditioning (HVAC) is a major energy consumer in buildings. The predictive control has demonstrated a potential to reduce HVAC energy use. To facilitate predictive HVAC control, internal heat gains prediction is required. In this study, we applied Long Short-Term Memory Networks, a special form of deep neural network,...

This chapter provides an overview of demand response (DR) technologies, including standards and end uses, in the United States and describes resource characteristics and the attributes of 14 specific DR resources in the US commercial, residential, and industrial sectors. The attributes reviewed for the end uses being considered are response frequen...

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to t...

Energy Management and Information Systems are a family of analytics technologies that include energy information systems, fault detection and diagnostics (FDD), and automated system optimization tools. Such systems have the potential to enable buildings to meet energy management goals of reducing total energy consumption and cost. Most current mark...

Currently over $300B is spent in US city economies to pay for energy. Many US cities are taking leading roles in exploring and promoting activities to improve energy efficiency and reduce green house gas (GHG) emissions. This paper summarizes a series of interviews with several leading cities regarding their needs, methods and tools they are using...

BayREN Integrated Commercial Retrofits (BRICR) is a DOE-funded project which aims to enhance the capacity of energy efficiency programs to recruit participants, develop retrofits, and measure outcomes in small and medium-sized commercial buildings, a sector notoriously hard to reach and expensive to serve, that accounts for ⅔ of US commercial floor...

Buildings in San Francisco consumed 52% of total primary energy. Improving building energy efficiency is one of the key strategies cities are adopting towards their energy and climate goals. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures for investment and to design effective in...

Building retrofits provide a large opportunity to significantly reduce energy consumption in the buildings sector. Traditional building retrofits focus on equipment upgrades, often at the end of equipment life or failure, and result in replacement with marginally improved similar technology and limited energy savings. The Integrated System (IS) ret...

This paper presents a case study using CityBES to analyze potential retrofit savings of different energy conservation measures for city-scale building stocks. CityBES is a web-based tool designed to support city-scale building energy efficiency, including currently implemented features of energy retrofit analysis, and visualization of city building...

Buildings in cities consume 30 to 70% of the cities’ total primary energy. Retrofitting the existing building stock to improve energy efficiency and reduce energy use is a key strategy for cities to reduce green-house-gas emissions and mitigate climate change. Planning and evaluating retrofit strategies for buildings requires a deep understanding o...

Commercial Building Energy Saver (CBES), intended use for small and medium office and retail buildings in California, provides energy benchmarking and three levels of retrofit analysis considering the project goal, data availability, and user experience. CBES offers prototype building models for seven building types, six vintages, in 16 California...

Small commercial buildings in the United States consume 47% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commer...

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a database of energy efficiency perfor...

Retrofit analysis toolkits can be used to optimize energy or cost savings from retrofit strategies, accelerating the adoption of energy conservation measures (ECMs) in buildings. This paper provides an up-to-date review of the features and capabilities of 18 energy retrofit toolkits, including ECMs and the calculation engines. The fidelity of the c...

This paper describes a step-by-step procedure for using measured end-use energy data from a campus building to calibrate a simulation model developed in EnergyPlus. This process included identification of key input parameters for reducing uncertainties in the model. Building thermal zones were modeled to match the actual heating ventilation and air...

This paper introduces the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, developed by Lawrence Berkeley National Laboratory. The CBES Toolkit evaluates the energy use of a building, identifies and evaluates retrofit measures. The toolkit provides a rich set of features for energy benchmarking and retrofit analysis, as...

The goal of this study is to provide an overview of demand response ( DR ) technologies, including standards and end uses, in the United States and describe resource characteristics and the attributes of 14 specific DR resources in the U.S. commercial, residential, and industrial sectors. The attributes reviewed for the end uses being considered ar...

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targetin...

Provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers Organizations in need of high-speed connectivity and nonstop systems operations depend upon data centers for a range of deployment solutions. A data center is a facility used to house computer systems...

Electricity transmission and distribution (T&D) networks carry electricity from generation sites to demand sites. With the increasing penetration of decentralised and renewable energy systems, in particular variable power sources such as wind turbines, and the rise in demand-side technologies, the importance of innovative products has never been gr...

Energy simulation programs are increasingly used to assess the energy performance of buildings and heating, ventilation, and air conditioning (HVAC) systems during design. Faults during operation can lead to considerable increase in energy use and associated operating costs. In 2009, 13 of the most common energy faults in U.S. commercial buildings...

The need for and concepts behind demand response are evolving. As the electric system changes with more intermittent renewable electric supply systems, there is a need to allow buildings to provide more flexible demand. This paper presents results from field studies and pilots, as well as engineering estimates of the potential capabilities of fast...

Low-cost automation and communication smart grid systems will be critical to the success of demand-response (DR) programs. The efforts at formal standardization of DR and distributed energy resources signals produced a set of communication specifications that is known as OpenADR 2.0. OpenADR 2.0 uses different terminology for clients and servers th...

This work presents a robust and computationally efficient algorithm for both whole-building and component-level energy fault detection and diagnosis (FDD). The algorithm is able to provide reliable estimation of multiple and simultaneous fault conditions, even in the presence of noisy and sometimes erroneous sensor data, and to provide uncertainty...

The goal of this work is to review the currently available retrofit tools for small and medium commercial buildings. Researchers investigated retrofit tools both in the public domain as well as in the private sector to better understand the diverse approaches currently in use to evaluate retrofit options: in particular calculation methods, retrofit...

Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems. This paper provides a framework linking continuous energy management and continu...

The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office buildi...

Energy information systems comprise software, data acquisition hardware, and communication systems that are intended to provide energy information to building energy and facilities managers, financial managers, and utilities. This technology has been commercially available for over a decade, however recent advances in Internet and other information...

This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automating demand response (DR). Automating DR allows greater levels of participation and improved reliability and repeatability of the demand response and customer facilities. Automated DR syste...

This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California’s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard—OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensur...

The Transactional Network Project is a multi-lab activity funded by the US Department of Energy’s Building Technologies Office. The project team included staff from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The team designed, prototyped and tested a transactional network (TN) pla...

There are growing strains on the electric grid as cooling peaks grow and equipment ages. Increased penetration of renewables on the grid is also straining electricity supply systems and the need for flexible demand is growing. This paper summarizes results of a series of field test of automated demand response systems in large buildings in the Paci...

This report details the operations of the Demand to Grid Laboratory (D2G Lab) demonstrations at Lawrence Berkeley National Laboratory (LBNL) since 2011, or Phase 1. Its purpose is to list the D2G Lab demonstration activities and results, and identify next steps to advance grid-integrated technologies and demand response research.

This paper describes work in progress toward an urban-scale system aiming to reduce energy use in neighboring buildings by providing three components: a database for accessing past and present weather data from high quality weather stations; a network for communicating energy-saving strategies between building owners; and a set of modeling tools fo...

An overview of research on intelligent energy information and control systems is discussed. New tools can organize data into actionable information and automated control, enabling a continuum of integrated energy efficiency and demand response (DR). As the speed of DR increases with better controls and telemetry, the value of the DR is higher for r...

The energy use in data centers is increasing and, in particular, impacting the data center energy cost and electric grid reliability during peak and high price periods. As per the 2007 U.S. Environmental Protection Agency (EPA), in the Pacific Gas and Electric Company territory, data centers are estimated to consume 500 megawatts of annual peak ele...

Fundamental analysis methods for heating and cooling systems from the 'Energy Information Handbook: Applications for Energy-Efficient Building Operations' is discussed. It includes 18 methods of analyzing utility, interval-meter, and submetered energy and control-system data, as well as overviews of manual and automated fault detection and diagnost...

In 2009, a pilot program was conducted to investigate the technical feasibility of bidding non-residential demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead ancillary services market as non-spinning reserves product. Three facilities, a retail store, a local government office building, and a bakery,...

Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory has developed an information-exchange specification, Open Automated Demand Response (OpenADR), which enables fully automated DR. OpenADR uses utility-provided price, reliability, or DR-event signals to trigger preprogrammed energy-management strategies automatically. Op...

We present methods for analyzing commercial and industrial facility 15-minute-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy e...

Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric C...

The focus of this study is energy information systems, broadly defined as performance monitoring software, data acquisition hardware, and communication systems used to store, analyze, and display building energy data. At a minimum, an EIS provides hourly whole-building electric data that are web-accessible, with analytical and graphical capabilitie...

Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy managemen...

This study examines the use of the OpenADR communications specification version 1.0 (OpenADR v1.0), related data models, technologies, and strategies to send dynamic prices such as real-time prices and peak prices and time-of-use rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open informatio...

California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implement...

Measured energy performance data are essential to national efforts to improve building efficiency, as evidenced in recent benchmarking mandates, and in a growing body of work that indicates the value of permanent monitoring and energy information feedback. This paper presents case studies of energy information systems (EIS) at four enterprises and...

This study examines the use of the OpenADR communications specification version 1.0 (OpenADR v1.0), related data models, technologies, and strategies to send dynamic prices such as real-time prices and peak prices and time-of-use rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open informatio...

This paper discusses how to optimize pre-cooling strategies for buildings in a hot California climate zone with the Demand Response Quick Assessment Tool (DRQAT), a building energy simulation tool. This paper outlines the procedure used to develop and calibrate DRQAT simulation models, and applies this procedure to eleven field test buildings. The...