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Net-Zero energy buildings are currently being built, and they no longer consist of small demonstration projects but rather large commercial and institutional buildings. However, achieving a “net-zero energy building” concept for existing buildings has its challenges in an urban environment where private and/or public space around the building considered is limited, in addition to the inherent energy challenges associated with urban multi-story buildings. While the most achievable task would be energy efficiency improvements in the operation of the building electrical and mechanical systems, examples of integration of renewable heat and electrical power systems on college and corporate campuses are abundant. The integration of renewable energy systems on urban campuses presents significant logistical challenges. For instance, the available roof area may not be enough to produce a substantial amount of photovoltaic power for the buildings under consideration. In this investigation, two students enrolled in an independent study Mechanical Engineering course at the Milwaukee School of Engineering (MSOE) developed a web-based a Distributed Energy Resources and Systems (DERS) decision guidance modeling tool that can be used by facilities directors on college or corporate campuses. Their work was augmented by an undergraduate engineering student who was employed as a research assistant during the following summer. The tool allows the following user-defined input, priorities, and constraints to generate a recommended suite of distributed energy resources that best meet the requirements of the user: • electrical and thermal load distribution on campus • geographical location • user objectives (moving toward a net-zero energy campus, a net zero carbon campus, or minimization of energy costs) • capital resources available The model uses ambient weather data, system performance parameters, and capital costs of distributed energy resources to make recommendations on the distributed energy system configuration. The tool enables the user to identify and analyze practical technologies that can be adopted for an existing campus in moving toward a net-zero energy goal. For calculations of solar photovoltaic (solar PV) system output, the solar irradiance and ambient temperature are used in conjunction with an estimated cell temperature correction along with rule-of-thumb derating factors (e.g. electrical losses, dirt losses, etc.). Solar thermal system output is estimated using the f-chart analysis approach which utilizes local solar irradiance data, ambient temperature, thermal load of the building, and typical performance parameters of flat plate solar thermal collectors. Combined Heat and Power (CHP) system output is estimated using design guidelines provided by the US Department of Energy’s Midwest Combined Heat and Power Applications Center. The decision tool outputs the following parameters: • Annual thermal energy output • Annual electrical energy output • Number of solar PV panels • Number of solar thermal panels • Size of the CHP system • Internal rate of return on the total initial capital investment Currently, the tool uses an iterative method in MATLAB to optimize the configuration of distributed energy systems as measured by the internal rate of return (IRR) realized from the initial capital investment. Future work will focus on expanding the capabilities of the tool so the user can identify the optimum configuration as measured by the amount of off-site energy purchased (thus moving toward net-zero energy), and/or by the amount of carbon emissions generated (moving toward net-zero carbon). Introduction This paper details the work started by two students enrolled in an 10-week independent study course in the Mechanical Engineering Department at MSOE. Their work was followed by contributions from an undergraduate research assistant who was employed over the summer. The objective of this project was to develop a distributed energy resources decision guidance tool that would be capable of making recommendations based on energy load distribution, renewable energy resource availability, user priorities, and capital constraints. The tool was to take into account solar PV, solar thermal, and combined heat and power (CHP) systems. The tool was designed to calculate the optimal size of each system for a given budget and campus location, and minimize the payback time on the investment. The tool was created using HTML, CSS, and JavaScript/jQuery web languages and runs within all major web browsers. This tool was developed within a local directory and can only be used if the root folder of the project is provided to the user. However, provided that the files can be hosted on a server, the tool can be easily configured to be viewed online. Weather data was queried from the National Renewable Energy Laboratory (NREL) using a public API [1]. The following sections go into detail on what equations were used to generate fiscal models for each source of energy. Web-based Decision Tool NREL API The weather data required for the calculations within Eco-Locate were obtained using a public API [1] made available by NREL. In order to access the weather data a personalized API [1] key is required by NREL. This key is obtained by registering the campus and project to the laboratory. This is done so NREL can properly track what party is accessing their data and block users whom they believe may be using their data improperly. The following table is a summary of the data that was queried and stored from the NREL database. Table 1: Overview of NREL Output Variables Variable Name Description solrad_monthly An array of 12 data values describing the average daily solar irradiance for one month. Units of kWh/m/day. solrad_annual A single decimal value that represents the average daily solar radiance for a year. Units of kWh/m/day. tamb An array of 12 data values of the average ambient temperature of a month. Units °C. All insolation data is obtained with an assumed tilt angle of 20°. This is the default value NREL uses when no tilt angle is inputted by the user. For the purpose of this tool it is necessary to find the solar irradiance over a year. This is done using the following equation. EYear,Sun = solrad_annual ∙ 365 days

Development of a Web-based Decision Tool for Selection of Distributed Energy Resources and Systems (DERS) for Moving College and Corporate Campuses Toward Net-Zero Energy