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To achieve reactive voltage control and resolve the problem of photovoltaic in regional grids with high-proportion photovoltaic access, a multi-cycle reactive voltage rolling optimization control method supporting photovoltaic absorption was proposed, and a multi-cycle reactive voltage rolling optimization control framework was constructed based on the sensitivity-based mathematical model of allowed maximum photovoltaic capacity. First, a reactive power optimization model was built day ahead to minimize the actions of the discrete reactive regulating equipment and the resistance of photovoltaic absorption, and the action plan for discrete reactive power regulating equipment was thus determined. After that, with the determined day-ahead control plan for discrete reactive equipment as the constraint, and with the maximization of photovoltaic absorption and improvement of the dynamic reactive reserve margin of the system as the objectives within day, a reactive voltage rolling optimization control model was built for the optimal control plan for the discrete and continuous reactive equipment; the rolling optimization control model performed optimization once every five minutes, with two hours as a cycle. At last, with a regional grid system as a study case, a simulating calculation was carried out and the control effects after optimization by the proposed multi-cycle reactive voltage rolling optimization control method showed that the maximum voltage deviation of two key nodes had been dropped by 34.21% and 45.98%, respectively, the action times of capacitors and the regulation times of main transformers had been reduced by 61.29% and 64%, respectively, the maximum regulation capacity requirement of continuous reactive equipment in photovoltaic stations had been dropped by 62.17%, and the forecast photovoltaic output could be fully absorbed in this system. These findings verified the feasibility and effectiveness of the proposed method in improving voltage control and promoting maximum photovoltaic absorption of regional grid. The case study showed that the day-ahead optimization control method could alleviate the large fluctuations of photovoltaics by arranging a discrete reactive power equipment adjustment plan, and the within-day rolling optimization control could adjust the output of continuous reactive power equipment to alleviate short-term random fluctuations of photovoltaics after simulating calculation.