Optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system.

Hydrogen production using renewable energy is in line with China's the goal of carbon peak and carbon neutrality. The construction of off-grid hydrogen energy industrial park can effectively achieve local utilization of renewable energy and develop the green hydrogen industry. However, off-grid hydrogen energy industrial park has not the compensation and sustentation from large power grid, the stable operation and economic production of electrolyzer are affected by significant factors, such as power fluctuation and frequent start stop. Therefore, this paper proposed the optimization method for capacity configuration and power allocation of electrolyzer array in off-grid integrated energy system. Firstly, based on units of energy supply, energy conversion, and energy storage, a structural model of off-grid integrated energy system was established. Then, by analyzing the operational characteristics of single electrolyzer and electrolyzer array, flexible mode of multiple electrolyzers operating in combination was proposed. Furthermore, considering the hydrogen production cost, the mean of hydrogen production volatility and penalty cost, the capacity configuration and power allocation methods for electrolyzer array were proposed, and the optimization problem is solved with multi-objective particle swarm optimization algorithm. Finally, the hydrogen energy industrial park in Zhangye is taken as example to verify the effectiveness of above research content. Compared to a single type of alkaline electrolyzer, the mean of hydrogen production volatility of multiple electrolyzers operating in combination has decreased by 43.2 %, the hydrogen production quantity has increased by 9.74 %. Compared to a single type of proton exchange membrane electrolyzer, the hydrogen production cost has been reduced by 14.16 %. Compared with the balanced running mode, the flexible operation mode can improve the cost-effective and quantity of hydrogen production.

Distributionally robust optimization scheduling of port energy system considering hydrogen production and ammonia synthesis.

In order to effectively address the uncertainty risks of port energy system caused by intermittence and fluctuation of renewable energy, this paper proposes a scheduling method for port energy system based on distributionally robust optimization (DRO) considering ammonia synthesis after hydrogen production by water electrolysis (P2H2A), and uses real data from Tianjin Port for example analysis. The calculation results show that 1 h selected for the scheduling interval of P2H2A is reasonable, it can ensure that the ammonia synthesis reaction transitions smoothly to the new steady state, and the temperature and pressure of the ammonia converter meet safety constraints. The two-stage scheduling of port energy system based on DRO can be divided into pre-scheduling in the day-ahead stage and rescheduling in the intraday stage, which can improve the capacity of anti-risk for stochastic optimization and overcome the conservatism of robust optimization, and consider economy and robustness. Moreover, the rescheduling decision can be transformed to a prediction error function, the result of two-stage scheduling based on DRO is the pre-scheduling result, which is between the cost of stochastic optimization and robust optimization. As the Wasserstein distance-based sphere radius increases, the pre-scheduling cost of DRO gradually deviates from risk neutral stochastic optimization and leans towards risk averse robust optimization. When the Wasserstein distance-based sphere radius remains constant, the variance gradually decreases as the number of scenarios increases, which can promote the Wasserstein distance-based fuzzy set to converge to the true distribution. When the number of scenarios is greater than 15, the pre-scheduling cost will no longer fluctuate significantly, and the calculation time is in the range of 1200 s-6600 s. It can meet the demands of day-ahead scheduling calculation time. Therefore, the scheduling model has outstanding advantages in the computing time to improve the flexibility and economy of Tianjin Port's energy system scheduling, considering ammonia synthesis after hydrogen production using renewable energy.

Public health shocks, learning and diet improvement.

Many governments aim to mitigate health risks by attacking nutritional failures. In this article, we exploit a unique natural experiment, the COVID-19 pandemic as an exogenous public health shock, to estimate the learning effects of intensive health information campaigns on nutrient intake during the pandemic. Using data from nearly-one million food purchases in China, our empirical findings strongly support the learning effect in explaining improvements in nutrient intake in the post-COVID-19 period. We conclude that when public health shocks occur, policy makers can boost relevant learning mechanisms by promoting information and education to improve individuals' awareness of preventive health behaviors of a more permanent nature, which can lead to health improvements in a society.

Is no news bad news? The impact of disclosing COVID-19 tracing information on consumer dine out decisions.

Food markets around the world have been disrupted by the COVID-19 pandemic via consumer behavior upended by fear of infection. In this article, we examine the impact of disclosing COVID-19 contact tracing information on food markets, using the restaurant industry in China as a case study. By analyzing transaction data at 87 restaurants across 10 cities, we estimate difference-in-difference (DID) models to ascertain the impact of COVID-19 infections and contact information tracing on economic activity as measured by a daily number of transactions. Empirical results show that while the overall number of new COVID-19 infections at the national level caused a dramatic drop in numbers of transactions in all restaurants, restaurants in cities that disclosed contact tracing information of COVID-19 infections experienced a 23%-35% higher number of transactions than the ones in cities that did not disclose such information during the recovery period. Ultimately, we show that in the absence of a shelter-in-place mandate, disclosing contract tracing information to mitigate consumers' uncertainties about risks of being infected can contribute to a faster recovery of food markets, in addition to reducing COVID-19 infections.

The Effects of Anti-corruption Campaign on Research Grant Reimbursement: Regression Discontinuity Evidence from China.

Integrity and research ethics are cherished institutions in academic world. Although most societies have rules and codes that govern ethical conducts in research, few studies have provided quantitative evidence on the impacts of these regulations and codes on the behaviors of researchers. In the context of a nationwide anti-corruption campaign in China, this paper evaluates the changes of principal investigators' reimbursement behavior in a leading university when new reimbursement policies were introduced. Utilizing a novel grant dataset and a regression discontinuity design, we find that the new policies lowered PIs' monthly average amount of reimbursement from research grants by 35%, which can be interpreted as a reduction in grant misuse. Following speculations we argue that institutionalizing orchestrated efforts on grant management, payroll systems, and research integrity education is in the right direction toward building China into a true scientific power.