Optimal Planning and Operation of Smart Grids with Electric Vehicle Interconnection

Publication Type

Journal Article

Date Published

06/2012

Authors

DOI

Abstract

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 mixed integer 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.

Journal

Journal of Energy Engineering, Special Issue: Challenges and opportunities in the 21st century energy infrastructure

Volume

138

Year of Publication

2012

Issue

2

ISSN

ISSN (print): 0733-9402, ISSN (online): 1943-7897

Organization

Research Areas

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