Increasing self-consumption of photovoltaic electricity by storing energy in electric vehicle using smart grid technology in the residential sector, 
a model for simulating different smart grid programs

Publication date

2014

Authors

van der Kam, M. J.ISNI 0000000506288583
van Sark, W. G.J.H.M.ORCID 0000-0002-4738-1088ISNI 0000000397039608

Editors

Helfert, M.
Krempels, K.H.
Donnellan, B.

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

No license information available

Abstract

In this paper a model has been developed which intends to simulate the increase of self-consumption of photovoltaic (PV)-power by storing energy in electric vehicle (EV) using smart grid technology in the residential sector. Three different possible smart grid control algorithms for a micro-grid consisting of solar panels, a household and an EV are presented that manage the (dis-)charging profile of an EV, either in real-time or using linear optimization using predictions for PV-power and electricity demand. The different control algorithms are simulated for a year using data for PV-power and electricity demand from the Netherlands and one specific EV. Preliminary results of the model are presented, showing that all control algorithms could significantly increase self-consumption and reduce peaks in electricity demand from the main grid. Although the difference in performance of the control algorithms for self-consumption is marginal, we find that linear optimization works better than the real-time algorithms for peak reduction.

Keywords

valorisation, Electric vehicle, Energy storage, Photovoltaic electricity, Self-consumption, Smart grid, SDG 7 - Affordable and Clean Energy

Citation

van der Kam, M & van Sark, W G J H M 2014, Increasing self-consumption of photovoltaic electricity by storing energy in electric vehicle using smart grid technology in the residential sector, 
a model for simulating different smart grid programs. in M Helfert, K H Krempels & B Donnellan (eds), Proceedings 3rd International Conference on Smart Grids and Green IT Systems : SMARTGREENS 2014. SciTePress, pp. 14-20. https://doi.org/10.5220/0004763000140020