Economic optimization of operations for hybrid energy systems under variable markets

Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper proposes a methodology for operations optimization to maximize their economic value based on predicted renewable generation and market information. A multi-environment computational platform for performing such operations optimization is also developed. To compensate for prediction error, a control strategy is accordingly designed to operate a standby energy storage element (ESE) to avoid energy imbalance within HES. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value. Simulation results of two specific HES configurations illustrate the proposed methodology and computational capability. Economic advantages of such operations optimizer and associated flexible operations are demonstrated by comparing the economic performance of flexible operations with that of constant operations. Sensitivity analysis with respect to market variability and prediction error are also performed.