Risk-averse stochastic scheduling of hydrogen-based flexible loads under 100% renewable energy scenario

Mengxiao Chen, Xiaoyu Cao, Zitong Zhang, Lun Yang, Donglai Ma and Miaomiao Li

Applied Energy, 2024, vol. 370, issue C, No S0306261924009528

Abstract: The development of 100% renewable energy (RE) systems provides a viable solution for achieving the global target of carbon neutrality. To support the reliable and economical operation of RE-based local energy networks, this paper presents a joint scheduling model for grid-scale RE generation and hydrogen-based flexible loads. The direct load control (DLC) through hydrogen-electrical microgrids is analytically modeled for leveraging the intrinsic flexibility of demand-side multi-energy synergy. To handle the uncertainty and volatility of RE generation, a risk-averse stochastic programming method with the receding-horizon mechanism is developed. Also, the power balancing cost in scheduling objectives is represented as a conditional value-at-risk (CVaR) measure to control the risks of fully RE supply. Case studies on an exemplary RE system confirm the effectiveness and economic benefits of the proposed method. The hydrogen-enabled DLC can largely mitigate the supply–demand mismatches, which shows a great potential to facilitate 100% RE scenarios.

Keywords: Renewable energy system; Flexible loads; Hydrogen-electrical microgrid; Stochastic receding-horizon scheduling; Conditional Value-at-Risk (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123569

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