The integration of renewable energy sources, particularly photovoltaic (PV) stations, is on the rise as countries worldwide strive for a greener, low-carbon future. This shift, though promising, brings challenges to power grid stability, most critically concerning frequency regulation. A recent study presents innovative methodologies to evaluate the active frequency support capability (AFSC) of PV stations, which are increasingly called upon to reinforce frequency stability as traditional power generation units are phased out.
According to the National Energy Administration, by the end of 2023, China's total installed capacity for wind and solar power generation surpassed one billion kilowatts, accounting for 36% of the nation’s power generation capacity. Despite this progress, reliance on PV energy reduces the rotational inertia available to the grid, which can lead to significant issues when frequency drops. High-profile blackouts, including the infamous 2016 South Australia blackout, bring to light the urgent need for effective frequency regulation strategies.
The authors of the article contend, “The proposed indicator system and evaluation method can reflect the AFSC of PV stations effectively.” Their research culminates in the establishment of a comprehensive evaluation indicator system and bi-level evaluation method, which combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), along with the Antagonistic Interpretive Structural Modeling (AISM) strategy. This integrated model is aimed at mitigating subjective biases and enhancing the reliability of evaluations.
The most pressing challenge addressed by the research is the necessity for PV stations to assist the grid during frequency deviation events. The study outlines three primary dimensions for evaluating AFSC: frequency stability, power support, and power regulation. The authors note, “The bi-level evaluation method has advantages in terms of computation speed and performance,” indicating its applicability for real-time grid management.
The methodology was put to the test using the IEEE 39-bus test system, where case studies demonstrated the method's effectiveness under various scenarios by simulating disturbances and the subsequent frequency response from PV stations. Results showcased the significant impacts of factors like active power ramp rate and average active power variation on frequency stability, underscoring the necessity of optimizing these parameters for enhanced grid performance.
One of the chief innovations resulting from this research is the development of software based on the evaluation system which has already been implemented on site to monitor the active frequency support capabilities of PV stations. This software not only evaluates AFSC but also incorporates features for maintaining active voltage stability and providing alerts to operators during operational anomalies.
Moving forward, the authors see great potential for this methodology to guide the advancement of power generation strategies as global energy demands increase. They conclude with aspirations for developing differentiated evaluation methods based on regional characteristics for enhanced implementation of frequency support capabilities, clearly marking the path for future innovation and collaboration.