A Crowdfunding Model for Green Energy Investment
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Special Track on Computational Sustainability. Pages 2669-2675.
Abstract
This paper studies a new renewable energy investment model through crowdfunding, which is motivated by emerging community solar farms. In this paper we develop a sequential game theory model to capture the interactions among crowdfunders, the solar farm owner, and an electricity company who purchases renewable energy generated by the solar farm in a multi-period framework. By characterizing a unique subgame-perfect equilibrium, andcomparing it with a benchmark model without crowdfunding, we find that under crowdfunding although the farm owner reduces its investment level, the overall green energy investment level is increased due to the contribution of crowdfunders. We also find that crowdfunding can increase the penetration of green energy in consumption and thus reduce the energy procurement cost of the electricity company. Finally, the numerical results based on real data indicates crowdfunding is a simple but effective way to boost green generation.
@inproceedings{ijcai2015p378,
title = {A Crowdfunding Model for Green Energy Investment},
author = {Zheng, Ronghuo and Xu, Ying and Chakraborty, Nilanjan and Sycara, Katia P.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {2669--2675},
year = {2015},
month = {7},
note = {Special Track on Computational Sustainability},
url = {https://ijcai.org/proceedings/2015/378},
}
TY - CPAPER TI - A Crowdfunding Model for Green Energy Investment AU - Zheng, Ronghuo AU - Xu, Ying AU - Chakraborty, Nilanjan AU - Sycara, Katia P. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 2669 EP - 2675 UR - https://ijcai.org/proceedings/2015/378 ER -Copied
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