• Media type: E-Article
  • Title: Electricity supply chain management considering environmental evaluation : a multi-period optimization stochastic programming model
  • Contributor: Sun, Jing [Author]; Ozawa, Masahiro [Author]; Zhang, Weichen [Author]; Takahashi, Kosuke [Author]
  • Published: 2022
  • Published in: Cleaner and responsible consumption ; 7(2022) vom: Dez., Artikel-ID 100086, Seite 1-11
  • Language: English
  • DOI: 10.1016/j.clrc.2022.100086
  • Identifier:
  • Keywords: Renewable energy ; Green energy coefficient (GEC) ; Electricity supply chain ; Aufsatz in Zeitschrift
  • Origination:
  • Footnote:
  • Description: This paper aims to derive optimal combination of electric powers for electric power market network considering environmental evaluation. Currently, attention is being paid to increasing the ratio of renewable energy generation in the electric power market which called Green Energy Coefficient (GEC). Many studies have analyzed different purposes for power market, such as configuration problem of electric power price, customer's electric power purchase distribution problem, power consumption problem, the development problem of the power generating system and so on. In this research, we propose the optimization stochastic programming models for electricity supply chain under renewable integration. We explicitly consider intermittency of renewable energy by developing a scenario decision tree, and further formulate and solve a multistage stochastic supply balance model to meet the aggregate demand in each period. The case study application is used to illustrate the model and how it supports the electricity supply chain management strategy.
  • Access State: Open Access
  • Rights information: Attribution - Non Commercial - No Derivs (CC BY-NC-ND)