Optimal Charging Control of Energy Storage and Electric Vehicle of an Individual in the Internet of Energy With Energy Trading

Chun-Cheng Lin, Der Jiunn Deng*, Chih Chi Kuo, Yu Lin Liang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Developing green energy to be applied in green cities has received much attention. The Internet of energy (IoE) effectively improves networking of distributed green energies through extending smart grids with bidirectional transmission of energy and distributed renewable energy facilities. Previous works on the IoE focused on decisions of IoE operators or optimization of the whole system. However, few considered optimal decisions of a single end user in the IoE. Therefore, this work creates a mixed-integer linear programming (MILP) model for a single end user that considers green energy generation, an energy storage, an electric vehicle, and an IoE-based energy trading platform to reduce energy waste. This model considers a complete system of charging control of multiple facilities of a single end user in the IoE, and allows the end user to purchase energy and sell green energy through the IoE, in which the energy prices of the electrical grid and the IoE platform are set by the power company and the energy market, respectively. Because MILP is NP complete and the proposed model involves a large number of variables and constraints, this paper further proposes a genetic algorithm for this problem, in which a repairing scheme is proposed to handle solution infeasibility of all constraints. By simulation, the proposed algorithm is verified to effectively reduce energy waste.

Original languageEnglish
Pages (from-to)2570-2578
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number6
DOIs
StatePublished - 1 Jun 2018

Keywords

  • Battery energy storage system (BESS)
  • electric vehicle (EV)
  • energy trading
  • Internet of energy (IoE)
  • real-time price (RTP)

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