Integrated optimization improves power quality and reduces costs in renewable energy parks, suggesting efficiency enhancements.
With the increasing share of renewable energy, green power parks face challenges such as high electricity purchasing costs and fluctuations in power quality. To address these issues, this paper proposes an integrated optimization method based on power quality responsibility modeling and a differentiated reward–penalty pricing mechanism (DRPPM). First, an integrated operation model of “source–grid–load–storage” is established. Within the pressure–state–response (PSR) framework, power quality deviations are quantified and mapped into economic costs. Then, a differentiated reward–penalty pricing mechanism is designed to dynamically adjust power quality deviations through a continuous function, guiding users toward adaptive energy consumption behavior. Finally, a green power park in Gansu Province dominated by wind and photovoltaic generation is used as a case study with four typical simulation scenarios. The results show that the proposed mechanism reduces the park’s electricity purchasing cost and increases the green power consumption ratio by up to 74.9%. Meanwhile, it effectively improves power quality indicators such as frequency, voltage, and harmonics. The study verifies the comprehensive advantages of the proposed framework in terms of economy, energy efficiency, and stability, providing a reference for low-carbon and efficient operation of high-energy-consumption green power parks.
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Yang et al. (2025) studied this question.
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