This study aims to explore the relationship between the doses of inactivated COVID-19 vaccines received and SARS-CoV-2 Omicron infection in the real-world setting, so as to preliminarily evaluate the protective effect induced by COVID-19 vaccination. We conducted a test-negative case-control study and recruited the test-positive cases and test-negative controls in the outbreak caused by Omicron BA.2 in April 2022 in Guangzhou, China. All the participants were 3 years and older. The vaccination status between the case group and the control group was compared in the vaccinated and all participants, respectively, to estimate the immune protection of inactivated COVID-19 vaccines. After adjusting for sex and age, compared with a mere single dose, full vaccination of inactivated COVID-19 vaccines (OR = 0.191, 95% CI: 0.050 to 0.727) and booster vaccination (OR = 0.091, 95% CI: 0.011 to 0.727) had a more superior protective effect. Compared with one dose, the second dose was more effective in males (OR = 0.090), as well as two doses (OR = 0.089) and three doses (OR = 0.090) among individuals aged 18–59. Whereas, when compared with the unvaccinated, one dose (OR = 7.715, 95% CI: 1.904 to 31.254) and three doses (OR = 2.055, 95% CI: 1.162 to 3.635) could contribute to the increased risk of Omicron infection after adjusting for sex and age. Meanwhile, by contrast with unvaccinated individuals, the result of increased risk was also manifested in the first dose in males (OR = 12.400) and one dose (OR = 21.500), two doses (OR = 1.890), and a booster dose (OR = 1.945) in people aged 18–59. In conclusion, the protective effect of full and booster vaccination with inactivated COVID-19 vaccines exceeded the incomplete vaccination, of which three doses were more effective. Nevertheless, vaccination may increase the risk of Omicron infection compared with unvaccinated people. This may result from the transmission traits of BA.2, the particularity and stronger protection awareness of the unvaccinated population, as well as the ADE effect induced by the decrease of antibody titers after a long time of vaccination. It is crucial to explore this issue in depth for the formulation of future COVID-19 vaccination strategies.
High penetration variable renewable energy introduces flexibility issues to the power system. For countries with coal as their main energy source, retrofitting existing thermal power units is one of the most realistic and feasible measures to improve power system flexibility. Multiple retrofit options will almost certainly be available for each individual power plant—all with distinct investment costs and performance implications. Therefore, this paper develops a multi-technical flexibility retrofit planning model to inform investment decisions of thermal power units in the short term. The model is formulated as a mix linear programming, with the goal of minimizing the systems overall investment and operational costs. In particular, a linear formulation is proposed to solve the coupling problem of retrofitting and operating, and take account of the changes in various units’ operational parameters after retrofit. The correctness and effectiveness of the proposed models are verified by a case study through a modified IEEE-30 bus system. The results demonstrate that it is necessary to consider the complementariness of multiple technologies between units. Besides, the proposed model could minimize the overall system investment and operational costs, and provide advice to planners and power generation companies.
Due to the randomness, volatility and intermittent nature of wind power, power systems with significant wind penetration face serious “curtailment” problems. The flexibility of a power system is an important factor that affects the large-scale consumption of wind power. Based on this fact, this paper takes into account the economics and flexibility of the system, and proposes an optimal scheduling method that takes the flexibility of each thermal power unit into account. Firstly, a comprehensive evaluation index system of thermal power unit flexibility is designed by an analytic hierarchy process and entropy method. The system covers the technical indexes and economic characteristics of thermal power units and is able to quantitatively evaluate the different types of thermal power units in the system. Secondly, a multi-objective optimization scheduling model involving the overall flexibility of the unit and the total power generation cost is established. Finally, the correctness and effectiveness of the proposed indicators and models are verified by a case study.
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