Judy Lai

Effect of Heat and Electricity Storage and Reliability on Microgrid Viability:A Study of Commercial Buildings in California and New York States

E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY Effect of Heat and Electricity Storage and Reliability on Microgrid Viability: A Study of Commercial Buildings in California and New York States Michael Stadler, Chris Marnay, Afzal Siddiqui, Judy Lai, Brian Coffey, and Hirohisa Aki Environmental Energy Technologies Division Revised March 2009 http://eetd.lbl.gov/EA/EMP/emp-pubs.html The work described in this paper was funded by the Office of Electricity Delivery and Energy Reliability, Renewable and Distributed Systems Integration Program in the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231.

Optimal Planning and Operation of Smart Grids with Electric Vehicle Interconnection

Connection of electric storage technologies to smartgrids will have substantial implications for building energy systems. Local storage will enable demand response. When connected to buildings, mobile storage devices such as electric vehicles (EVs) are in competition with conventional stationary sources at the building. EVs can change the financial as well as environmental attractiveness of on-site generation (e.g. PV or fuel cells). In order to examine the impact of EVs on building energy costs and CO2 emissions, a distributed-energy-resources adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs or CO2 emissions and solved for 2020 technology assumptions. The mixedinteger linear program is applied to a set of 139 different commercial buildings in California and example results as well as the aggregated economic and environmental benefits are reported. Special constraints for the available PV, solar thermal, and EV parking lots at the commercial buildings are considered. The research shows that EV batteries can be used to reduce utility-related energy costs at the smart grid or commercial building due to arbitrage of energy between buildings with different tariffs. However, putting more emphasis on CO2 emissions makes stationary storage more attractive and stationary storage capacities increase while the attractiveness of EVs decreases. The limited availability of EVs at the commercial building decreases the attractiveness of EVs and if PV is chosen by the optimization, then it is mostly used to charge the stationary storage at the commercial building and not the EVs connected to the building.

A method for simulating the performance of photosensor-based lighting controls

Abstract The unreliability of photosensor-based lighting controls continues to be a significant market barrier that prevents widespread acceptance of daylight dimming controls in commercial buildings. Energy savings from the use of daylighting in commercial buildings is best realized through the installation of reliable photoelectric lighting controls that dim electric lights when sufficient daylight is available to provide adequate background and/or task illumination. In prior work, the authors discussed the limitations of current simulation approaches and presented a robust method to simulate the performance of photosensor-based controls using an enhanced version of the radiance lighting simulation package. The method is based on the concept of multiplying two fisheye images: one generated from the angular sensitivity of the photosensor and the other from a 180 or 360° fisheye image of the space as “seen” by the photosensor. This paper includes a description of the method, its validation and possible applications for designing, placing, calibrating and commissioning photosensor-based lighting controls.

Applications of Optimal Building Energy System Selection and Operation

Berkeley Lab has been developing the Distributed Energy Resources Customer Adoption Model for several years. Given load curves for energy services requirements in a building microgrid (µ·grid), fuel costs and other economic inputs, and a menu of available technologies, the model finds the optimum equipment fleet and operating schedule. This capability is being applied using a Software as a Service (SaaS) model. The evolution of this approach is demonstrated by description of four past and present projects: (1) a public access web site focused on solar photovoltaic generation and battery viability for large non-residential customers; (2) a building CO2 emissions reduction operations problem for a university dining hall with potential investments considered; (3) a battery and rolling operating schedule problem for a large county jail; and (4) the direct control of the solar-assisted heating ventilation and air conditioning system of a university building by providing optimised daily schedules that are automatically implemented in the building’s energy management and control system. Together these examples show that optimisation of building μ·grid design and operation can be effectively achieved using SaaS.

Web-based economic and environmental optimization of microgrids

Even as distributed generation and distributed energy resources (DER) become a more appealing option to meeting building electricity, heat, and cooling demands, the process of selecting the appropriate equipment mix remains as a complex and time-consuming obstacle. This is the motivation behind Lawrence Berkeley National Laboratorys (LBNL) development of WebOpt, a flexible web-based software as service (SaaS) approach for optimizing the selection and operation of DER equipment, and running the Distributed Energy Resources Customer Adoption Model (DER-CAM), the optimization platform that supports it. DER-CAM solves energy systems for microgrids [1], [2] (e.g. combined heat and power (CHP) or electric storage) holistically, taking into account service levels for multiple building end-uses, including heating, cooling and electricity. Given an individual microgrids hourly energy requirements, available technologies and the economic environment as defined by tariff structure, DER-CAM finds the economically or environmentally optimal combination of equipment to install and an optimal schedule to operate it [3], [4].

A green prison: The Santa Rita Jail campus microgrid

A large microgrid project is nearing completion at Alameda Countys twenty-two-year-old 45 ha 4,000-inmate Santa Rita Jail, about 70 km east of San Francisco. Often described as a green prison, it has a considerable installed base of distributed energy resources (DER) including an eight-year old 1.2 MW PV array, a five-year old 1 MW fuel cell with heat recovery, and considerable efficiency investments. Fig. 1 is an aerial depiction of the Jail with the PV rooftop modules clearly visible.

Encouraging Combined Heat and Power in California Buildings

Encouraging Combined Heat and Power in California Buildings Michael Stadler, Markus Groissbock, Goncalo Cardoso, Andreas Muller, Judy Lai Lawrence Berkeley National Laboratory February 2013

Wireless electricity metering of miscellaneous and electronic devices in buildings

Miscellaneous and electronic loads (MELs) consume about 30% of the electricity used in U.S. commercial buildings, but our understanding of their energy use lags the traditional end-uses. A key component of reducing energy use is understanding how devices are used, but few studies have collected field data on the long-term energy used by a large sample of devices due to the difficulty and expense of collecting device-level energy data. This paper describes a wireless MELs metering system and an office building case study where these meters were deployed. Hundreds of miscellaneous and electronic devices where metered for several months. This paper includes key findings on the meters, network and MELs energy use.

Evaluation of miscellaneous and electronic device energy use in hospitals

Miscellaneous and electronic loads (MELs) consume about one-thirdof the primary energy used in US buildings, and their energy use is increasing faster than other end-uses. In healthcare facilities, 30percent of the annual electricity was used by MELs in 2008. This paper presents methods and challenges for estimating medical MELs energy consumption along with estimates of energy use in a hospital by combining device-level metered data with inventories and usage information. An important finding is that common, small devices consume large amounts of energy in aggregate and should not be ignored when trying to address hospital energy use.

Healthcare Energy Efficiency Research and Development

Hospitals are known to be among the most energy intensive commercial buildings in California. Estimates of energy end-uses (e.g. for heating, cooling, lighting, etc.) in hospitals are uncertain for lack of information about hospital-specific mechanical system operations and process loads. Lawrence Berkeley National Laboratory developed and demonstrated a benchmarking system designed specifically for hospitals. Version 1.0 featured metrics to assess energy performance for the broad variety of ventilation and thermal systems that are present in California hospitals. It required moderate to extensive sub-metering or supplemental monitoring. In this new project, we developed a companion handbook with detailed equations that can be used to convert data from energy and other sensors that may be added to or already part of hospital heating, ventilation and cooling systems into metrics described in the benchmarking document. This report additionally includes a case study and guidance on including metering into designs for new hospitals, renovations and retrofits. Despite widespread concern that this end-use is large and growing, there is limited reliable information about energy use by distributed medical equipment and other miscellaneous electrical loads in hospitals. This report proposes a framework for quantifying aggregate energy use of medical equipment and miscellaneous loads. Novel approaches are suggested and tried in an attempt to obtain data to support this framework.