Optimizing cleaner productions of sustainable energies: A co-design framework for complementary operations of offshore wind and pumped hydro-storages

Abstract

There has been a constant evolution in developing clean energy technologies to reduce environmental concerns. In this context, wind energy technology is an ingenious option to make the energy sector more sustainable. However, the growing penetration of wind energy pose challenges to the power system reliability. An integrated system including offshore wind farms (OWFs) and pumped hydroelectric storages (PHSs) emerges as a promising solution to this issue. However, the current wind farm layout optimization (WFLO) always neglect the optimal designs of the PHSs, and also is not based on the optimal OWF controls. Therefore, this paper develops a co-design optimization framework to jointly optimize the wind farm layout and the PHSs’ configurations. The operation principle of the integrated system is first described and two optimization objectives are proposed. An evolutionary trained adaptive neuro-fuzzy inference system (ANFIS) is constructed to forecast OWF power output. The co-design optimization is then formulated as a constrained multi-objective optimization problem and evolutionary algorithms are adopted to find the optimal solutions. Two design cases considering the optimal/non-optimal OWF controls are proposed for the validations. The test results indicate that the trained ANFIS can efficiently identify the characteristics of OWF power generations. In the co-design optimization, the averaged power mismatch is lower than 5 MW, and there are several points that have zero power mismatch. The maximum OWF powers are around 30 MW in the optimal OWF control case, but are lower than 25 MW without using the optimal control. There also exist obvious differences between the optimal PHS parameters in the two cases due to the optimal OWF control.