Open AccessFour‐level robust model for a virtual power plant in energy and reserve markets
Author(s) -
Zhou Yizhou,
Wei Zhig,
Sun Guoqiang,
Cheung Kwok W.,
Zang Haixiang,
Chen Sheng
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5197
Subject(s) - virtual power plant , mathematical optimization , hedge , computer science , strong duality , realisation , integer programming , linear programming , robust optimization , energy market , stochastic programming , renewable energy , distributed generation , optimization problem , engineering , mathematics , electrical engineering , ecology , physics , quantum mechanics , biology
The integration of distributed energy resources into a virtual power plant (VPP) can realise the scale merit. This study presents a novel approach for determining the optimal offering strategy of a VPP participating in the day‐ahead (DA), the spinning reserve (SR), and the real‐time (RT) markets. To hedge against multi‐stage uncertainties, the authors propose a robust mixed integer linear programming optimisation model that comprises four levels: (i) the optimal DA energy and reserve dispatch; (ii) the worst‐case realisation of uncertainties involved in DA market energy prices, SR market capacity prices, stochastic power production, and called balancing power; (iii) the optimal RT energy re‐dispatch; and (iv) the worst‐case realisation of uncertain RT market energy prices. Moreover, a tractable solution method based on strong duality theory and the column‐and‐constraint generation algorithm to solve the proposed four‐level formulation was developed. Finally, numerical results for a realistic case study demonstrate the efficiency and applicability of the proposed approach. The commercial benefits of this strategy are also evaluated.