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Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision‐making. The decision‐maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject. [ABSTRACT FROM AUTHOR]

This paper employs the threshold cointegration methodology to assess the long- and short-run dynamics of asymmetric adjustment between economic policy uncertainty (EPU) of China-India, China-Japan, China-Korea, India-Japan, India-Korea, and Japan-Korea pairs using monthly EPU data ranging from January 1997 to April 2020. The relationship between the EPU pairs is examined in terms of Engle-Granger and threshold cointegrations. The findings provide evidence of long-run threshold cointegration and that the adjustments towards the long-run equilibrium position are asymmetric in the short run for the China-India and India-Japan EPU pairs in M-TAR specification with nonzero threshold values. Also, the results suggest a unidirectional causal relationship between China-India, China-Japan, and India-Korea EPU pairs in the long and short run using the spectral frequency domain causality approach. However, a bidirectional causal relationship between China-Korea, India-Japan, and Japan-Korea pairs exists in the long and short run. Therefore, the findings provide some clues to economic policymakers within the Asian subregion for possible policy uncertainty synergies and spillovers among the Asian countries. [ABSTRACT FROM AUTHOR]

Summary: As the uncertainty of renewable energy output brings more and more risks to the day‐ahead dispatch of the power grid, an optimization scheduling strategy of a smart energy system based on improved master‐slave game model is proposed. Risk factors related to the uncertainties of renewable energy are introduced into the master‐slave game model. Taking the smart energy system as the leader and the end users as the follower, an optimized operation model of the smart energy system based on the improved master‐slave game model is established, which is transformed into a single‐layer linear programming model according to the Karush‐Kuhn‐Tucher conditions and the duality theorem. The benefits of the system and electric vehicle users in four application scenarios are obtained by the YALMIP algorithm and the sensitivity affecting the economics of the smart energy system is analyzed. The validity of the model is verified by a simulation analysis of actual operation data from the smart energy system in China. The simulation results show that the method proposed in this paper can increase the revenue of the smart energy system by 7%, reduce the risk cost and charging cost of electric vehicle users by 63.92% and 48.34%. [ABSTRACT FROM AUTHOR]

Summary: This paper considers the co‐optimization operation problem of the multiple micro energy grids (MEGs), and proposes a novel concept of the flexible boundary. Then, a three‐level co‐optimization model of reconfiguration, dispatching, and reserve is designed considering different time scales. Furthermore, an improved ant colony algorithm based on the information entropy and the chaotic search is proposed. The Shenzhen international low‐carbon park in China is selected as an example. The results show that: (a) The capacity configuration scheme considering the flexible boundary conditions could decrease the reserve capacity of power, heating, and cooling from the upper energy grid, namely, 75%, 50%, and 75%, and delay 537 × 104¥ the investment cost of the new capacity by utilizing the complementary characteristics between different MEGs. (b) The proposed three‐level co‐optimization model could establish the multi‐level optimal cooperative operation schemes of multi‐MEGs and decrease the reserve power from the upper energy grid and incentive‐based demand response. Among them, UPG provides MEG 1, MEG 2, and MEG 3 with cooling load reserve capacity reduction of 53.95, 85.44, and 38.3 kw h. The positive reserve provided by IBDR for MEG 1, MEG 2, and MEG 3 decreased by 30.53, 20.21, and 52 kW h. (c) The proposed improved ant colony algorithm can consider the operational characteristics of each energy entity in different stages of multi‐MEGs and obtain the global optimal operation scheme. Compared the traditional ant colony algorithm, the average convergence times decrease by 18% and the optimization degree of the objective value increase by 12.38%. (d) The sensitivity analysis shows the conditional value at risk method can formulate the optimal dispatching schemes of multi‐MEGs according to the risk attitudes of decision makers. When confidence degree is between 0.3 and 0.8, the decision‐makers have a high‐risk sensitivity and are more willing to avoid uncertain risks of wind power plant and photovoltaic power. Overall, the proposed model and solution algorithm could achieve the optimal operation strategy of the micro energy grids. [ABSTRACT FROM AUTHOR]

Summary: Precast buildings have been becoming popular in China in these 5 years since they have many merits such as effectiveness, safety, high quality, and environmental friendliness. In some cities of China, it is required to make the proportion of precast buildings account for 30% in newly built construction areas. Following the rapid development, their vibration behaviors are attracting more attention since it may be quite different from the cast‐in‐situ building. To investigate the difference, this paper studies the modal properties of two kinds of buildings, i.e., new‐type precast building and cast‐in‐situ building. They were built in the same area, while the structural forms are also similar. The main difference is the construction manner. Ambient vibration tests of these two structures were conducted respectively. Since the number of sensors is limited, the locations of interest were measured by a multiple‐setup technique. The difficulty encountered during the field test was discussed. A frequency domain Bayesian approach was used to conduct operational modal analysis. Both the most probable value and posterior uncertainties of modal parameters were studied, including translational, torsional, and wrapping modes. The difference of the modal parameters of the two kinds of buildings are compared and discussed. Finite element models were also built to perform a comparison. It is seen that although the structural forms and appearances of the two buildings are similar, some obvious differences were observed regarding the dynamic characteristics, which provide valuable information for popularizing and future assessment of the new‐type precast structure. [ABSTRACT FROM AUTHOR]

Summary: Power‐to‐gas storage (P2GS) provides a new approach for clean energy accommodation, which could be used to support the development of the microenergy grid (MEG). This paper designs a novel structure of MEG including power sources, heating sources, and P2GS. The risk condition values (CVaR) is applied to analyze the uncertainties from wind power plant, photovoltaic power generation, and solar collectors, and a multiobjective optimal model is proposed for balancing the operation economic benefit and the risk level. Then different membership functions are selected for converting the multiobjective model into a mixed integer programming model. Finally, an industrial park in northern China was selected to verify the proposed model. The results show that (a) complementary effect exists in different clean energy sources and P2GS can convert excess energy into CH4 for power generation, which are better for achieving the power‐to‐gas‐to‐power cycle optimization effect. (b) The proposed optimal model could balance revenue and risk, rationally control its operation risk while pursuing the maximum operation benefits, which is better to achieve MEG's optimal equilibrium operation. (c) Maximum emission trade allowance could enhance MEG's enthusiasm for clean energy accommodation, and P2GS could be a feasible way for near‐zero carbon emissions. Therefore, the proposed risk aversion optimal model could increase the economic benefits and control the risks and provide decision support for decision makers. [ABSTRACT FROM AUTHOR]

Manufacturing is one of the drivers of China's growth, realizing structural upgrading is vital to achieve high-quality economic development during periods of economic policy uncertainty. Based on firm-level and province-level panel data from 1997 to 2018, this paper used a fixed effect panel data model and panel quantile regression model to investigate the effect of economic policy uncertainty on structural upgrading in manufacturing. The findings indicate that the effect of economic policy uncertainty on structural upgrading in manufacturing is significantly positive and great in regions at advanced stages of manufacturing structure. The discussion about the results suggests that the mechanism of economic policy uncertainty affecting structural upgrading in manufacturing operates through pushing the manufacturing industry to implement service transformation strategies along with vertical integration. [ABSTRACT FROM AUTHOR]

As China enters a new era, the role of consumption as a driving force for the economy has become increasingly prominent. The consumption of rural residents is not only a matter of high-quality economic development but also an important part of realizing people's aspirations for a better life. This study contributes to the literature by establishing an econometric model based on the construction of a theoretical model for optimizing the utility of household consumption, using panel data from China's 31 provinces, eliminating endogenesis by using instrumental variables, taking  2SLS and dynamic  GMM. The results show that the relationship between income uncertainty and rural residents' consumption varies in the same direction, stimulating consumption when real income exceeds psychological income and reducing consumption when real income does not reach psychological income. The quantile model shows that income uncertainty has a greater impact on the middle-high-consumption groups and a smaller impact on the lower-income groups. [ABSTRACT FROM AUTHOR]

Summary: This research is motivated by the practice of a well‐known basin—the Yalong River Basin located in the eastern part of the Qinghai‐Tibet Plateau in China, which requires a more reasonable day‐ahead scheduling and operation of a wind‐pumped‐hydro system. Optimal electricity flow remains a widely‐cultivated topic within power system research community since its inception about half‐a‐century ago. In contrast to previous studies, this article proposes a multiobjective multistage nonlinear model to not only for the technical pump‐operating constraints of the coordinated system, but also for lessening the variations on the active power output coming from the intermittence variability of the wind energy resource. Specifically, minimizing the fluctuations of the power output and minimizing the "abandoned rate" of the wind and hydro power are considered two objectives. A state transition equation to compute the energy balance in the reservoir is introduced in the constraint for scheduling the pump‐hydro system. Moreover, the expected operator and chance constraint are used to deal with the stochastic wind energy output. Finally, the scheduling of a wind‐pumped‐hydro system of the Yalong River Basin is proposed as a practical example to illustrate the effectiveness, feasibility, and validity of the proposed model. [ABSTRACT FROM AUTHOR]

In the location-related planning of a hydropower system, the consideration of future operations under uncertainties can make the decisions sustainable and robust. Then, it is of great importance to develop an effective approach that deals with the long-term stochasticity due to the long-lasting effects of the location selections. Thus, we propose a multistage stochastic programming model to optimize the planning decisions of cascade hydropower stations and the long-term stochastic operations in an integrated way. The first stage (i.e., the planning stage) in the model deals with the location and capacity decisions of the hydropower stations, while the subsequent stages implement the scheduling decisions under each stagewise stochastic scenario. To address the curse of dimensionality caused by the long-term stochastic operations, we further propose a novel dimensionality reduction approach based on dual equilibrium to transform the multistage model into a tractable two-stage stochastic program. The applicability of our approach is validated by a case study based on a basin of Yangtze River, China, and corresponding sensitivity analysis. [ABSTRACT FROM AUTHOR]