
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Control of greenhouse gas emissions by optimal DER technology investment and energy management in zero‐net‐energy buildings

doi: 10.1002/etep.418
Control of greenhouse gas emissions by optimal DER technology investment and energy management in zero‐net‐energy buildings
AbstractThe U.S. Department of Energy has launched the commercial building initiative (CBI) in pursuit of its research goal of achieving zero‐net‐energy commercial buildings (ZNEB), i.e., ones that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting‐edge, energy‐efficiency technologies and meet their remaining energy needs through on‐site renewable energy generation. This paper examines how such buildings may be implemented within the context of a cost‐ or CO2‐minimizing microgrid that is able to adopt and operate various technologies: photovoltaic (PV) modules and other on‐site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive/demand‐response technologies. A mixed‐integer linear program (MILP) that has a multi‐criteria objective function is used. The objective is minimization of a weighted average of the building's annual energy costs and CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand‐response measures may enable compliance with the ZNEB objective. Using a commercial test site in northern California with existing tariff rates and technology data, we find that a ZNEB requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy‐efficient combined heat and power (CHP) equipment, while occasional demand response saves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve a ZNEB. Additionally, the ZNEB approach does not necessary lead to zero‐carbon (ZC) buildings as is frequently argued. We also show a multi‐objective frontier for the CA example, which allows us to estimate the needed technologies and costs for achieving a ZC building or microgrid. Copyright © 2010 John Wiley & Sons, Ltd.
- University of North Texas United States
- University College London United Kingdom
- Lawrence Berkeley National Laboratory United States
- University of North Texas United States
- Lawrence Berkeley National Laboratory United States
Zero-Carbon, 20, Energy Efficiency, Storage, 03, Distributed Generation, 25, Energy Consumption, Heat Exchangers, 24, Absorption, Greenhouse Gases, Energy Balance, Electricity, 29, Capacity, Co2 Emissions, 14, Energy Accounting, 32, Minimization, Sales, Exports, Commercial Buildings, Energy Management, Tariffs Co2 Emissions, Zero-Net Energy Buildings, Compliance
Zero-Carbon, 20, Energy Efficiency, Storage, 03, Distributed Generation, 25, Energy Consumption, Heat Exchangers, 24, Absorption, Greenhouse Gases, Energy Balance, Electricity, 29, Capacity, Co2 Emissions, 14, Energy Accounting, 32, Minimization, Sales, Exports, Commercial Buildings, Energy Management, Tariffs Co2 Emissions, Zero-Net Energy Buildings, Compliance
2 Research products, page 1 of 1
- 2009IsAmongTopNSimilarDocuments
- 2010IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).60 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
