Portfolio planning of renewable energy with energy storage technologies for different applications from electricity grid

Portfolio planning of renewable energy industry with energy storage technologies is the key to meeting the different and increasing application demands from electricity grid. However, it is a difficult and fuzzy problem because of the complex interaction between renewable energy and energy storage technologies, various applications from electricity grid, and uncertain decision environment, which has not been solved simultaneously so far. Therefore, this paper proposes a two-stage planning framework based on fuzzy multi-criteria-decision making techniques to select the most promising renewable energy with energy storage portfolio from the aspects of energy generation, transmission and terminal application. Firstly, three types and thirteen special energy storage technology application scenarios are distinguished, and the superiorities of the typical energy storage technologies are evaluated from the generation, transmission and terminal applications via interval fuzzy number based PROMETHEE-II. On this basis, an eight-step fuzzy multi-criteria decision-making framework is adopted to study the portfolio models with six promising renewable energy and the selected energy storage technology combinations. The result shows that photovoltaic still dominate in the application of renewable energy. Photovoltaic & CAES in generation, Hydropower & CAES in generation, Wind & CAES in generation, Photovoltaic & CAES, HFC in generation, Photovoltaic & Ni-Cd battery in transmission, Photovoltaic & CAES and Ni-Cd battery in terminal application are better solutions for government or decision makers to further comprehensively plan the large-scale application of clean energy in the grid. Besides, portfolios with complementary effects are identified and analyzed separately. This research contributes to the literature.

Automated summary

This study proposed a two-stage planning framework based on fuzzy multi-criteria-decision making techniques to select the most promising renewable energy with energy storage portfolio. The research found that photovoltaic still dominates in the application of renewable energy, and suggested better solutions for renewable energy and energy storage technology combinations.