LBNL Report Number
Lawrence Berkeley National Laboratory (LBL) is working with the California Energy Commission (CEC) to determine the role of distributed generation (DG) in greenhouse gas reductions. The impact of DG on large industrial sites is well known, and mostly, the potentials are already harvested. In contrast, little is known about the impact of DG on commercial buildings with peak electric loads ranging from 100 kW to 5 MW. We examine how DG with combined heat and power (CHP) may be implemented within the context of a cost minimizing microgrid that is able to adopt and operate various smart energy technologies, such as thermal and photovoltaic (PV) on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and storage systems. We use a mixed-integer linear program (MILP) that has the minimization of a site's annual energy costs as objective. Using 138 representative commercial sites in California (CA) with existing tariff rates and technology data, we find the greenhouse gas reduction potential for California's commercial sector. This paper shows results from the ongoing research project and finished work from a two year U.S. Department of Energy research project. To show the impact of the different technologies on CO2 emissions, several sensitivity runs for different climate zones within CA with different technology performance expectations for 2020 were performed. The considered sites can contribute between 1 Mt/a and 1.8 Mt/a to the California Air Resources Board (CARB) goal of 6.7Mt/a CO2 abatement potential in 2020. Also, with lower PV and storage costs as well as consideration of a CO2 pricing scheme, our results indicate that PV and electric storage adoption can compete rather than supplement each other when the tariff structure and costs of electricity supply have been taken into consideration. To satisfy the site's objective of minimizing energy costs, the batteries will be charged also by CHP systems during off-peak and mid-peak hours and not only by PV during sunny on-peak hours.