Demand response minimizing the impact on the consumers' utility considering forecast error on renewable energy resource

Yuya Taniguchi, Ryo Kutsuzawa, Akira Yamashita, Jun Matsumoto, Naoaki Yamanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In the smart grid, which is a new generation grid integrated with bidirectional communication and advanced information technology, it is supposed that the number of energy suppliers will increase because many renewable resources will be connected to the grid. The increase in the number of suppliers that use renewable energy resources introduces new challenges in scheduling and dispatching controllable resources to control the load of the power grid in the system. By using the pricing method that maximizes social welfare, consumers/suppliers can determine the optimal power consumption/generation that maximizes own welfare. However, when a forecast error of renewable energy output occurs, the gap between the total power consumption and generation causes unless consumers decrease power consumption from the optimal consumption. Decreasing consumers' power consumption might lower their utility. In this paper, we define impact on consumers' utility and propose two demand response methods which aim to minimize the impact. The first method, called One-Time Demand Response, minimizes the impact on consumers' utility of a certain time slot by using a Lagrange multiplier. In the second method, called Foresight Demand Response, all consumers can forecast the electricity market price of the next time slot by using linear regression, and consumers do not reduce power consumption when the incentive of a certain time slot is cheaper than the forecast electricity market price of the next time slot. From the performance evaluation, we confirm the impact on consumers' utility in One-Time Demand Response and Foresight Demand Response. We also confirm that both two proposals can increase consumers' welfare compared to not carrying out demand response.

Original languageEnglish
Title of host publicationLANMAN 2017 - 23rd IEEE International Symposium on Local and Metropolitan Area Networks
PublisherIEEE Computer Society
Volume2017-June
ISBN (Electronic)9781538607282
DOIs
Publication statusPublished - 2017 Jul 7
Event23rd IEEE International Symposium on Local and Metropolitan Area Networks, LANMAN 2017 - Osaka, Japan
Duration: 2017 Jun 122017 Jun 14

Other

Other23rd IEEE International Symposium on Local and Metropolitan Area Networks, LANMAN 2017
CountryJapan
CityOsaka
Period17/6/1217/6/14

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering
  • Communication

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    Taniguchi, Y., Kutsuzawa, R., Yamashita, A., Matsumoto, J., & Yamanaka, N. (2017). Demand response minimizing the impact on the consumers' utility considering forecast error on renewable energy resource. In LANMAN 2017 - 23rd IEEE International Symposium on Local and Metropolitan Area Networks (Vol. 2017-June). [7972173] IEEE Computer Society. https://doi.org/10.1109/LANMAN.2017.7972173