Maximum Group Perceived Utility Consensus Models Considering Regret Aversion

In the consensus-reaching process(CRP),the actual utility of decision-makers(DMs)is often influenced by the psychological behavior of regret aversion.However,the influence of regret aversion on DMs’utilities is rarely taken into account in the existing consensus models.The consensus-reaching problem of DMs with regret aversion is explored to maximize their perceived utilities under a limited budget.Firstly,three basic types of perceived utility functions are constructed based on the regret theory to describe the perceived utility of DMs with various preferences.Then,considering the limited budget and individual regret aversion,the maximum perceived utility consensus models based on types of left-skewed,right-skewed,middle-skewed,and heterogeneous utility preferences are proposed to achieve the consensus that maximizes the group perceived utility.After that,an example of land-transfer price negotiation in China is given to illustrate the validity of the proposed models.Finally,the model comparison and the sensitivity analysis are presented to reveal the influence of DMs’regret aversion on the CRP.The results suggest that the DMs’regret aversion will not affect left-skewed and right-skewed groups,but will affect the consensus results of middle-skewed and heterogeneous groups.

Flexible path planning-based reconfiguration strategy for maximum capacity utilization of battery pack

Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.

Single-atom Pd catalysts as oxidase mimics with maximum atom utilization for colorimetric analysis

Pd-based nanomaterials have shown great promise as potential mimic enzymes,but conventional catalysts use only a small fraction of the Pd content that located on the catalyst's surface.Herein,we demonstrated that maximum atom utilization could be achieved by using single-atom Pd catalysts as oxidase mimic.The single-atom Pd nanozymes exhibit significantly enhanced catalytic efficiency,with a catalytic rate constant(Kcat)and the catalytic efficiency(Kcat/Km)values more than 625 and 4,837 times higher than those of horseradish peroxidase,respectively.A combined experimental and theoretical calculation reveals reactive oxygen species involved catalytic mechanism which endows single-atom Pd catalysts with excellent colorimetric analysis performance.Benefiting from the maximum atom utilization efficiency and well-defined structural features,the single-atom Pd nanozymes could be successfully applied for the total antioxidant capacity of fruit,determining the serum acid phosphatase activity as well as constructing NAND logic gate.This finding not only provides an effective strategy to maximize the noble-metal atom utilization efficiency as enzyme mimics,but also provides a new idea for extending their possible applications.

Markov approximation for multilayered selection in satellite network

A satellite network system comprises three layers of satellites:LEO(Low Earth Orbit),MEO(Middle Earth Orbit)and GEO(Geostationary Orbit).In the system,users can choose a layer according to their demands,including QoS(Quality of Service),congestion,energy cost,etc.The utility that users gain will change when they access satellites in different layers.The mobility of satellites in the LEO and MEO leads to frequent handover among satellites in the same layer.These characteristics of multi-layered satellite networks make it possible for us to exploit the optimal distribution of users,which will maximize the utility of the entire satellite network.While the proposed problem is an NP-hard problem,we analyze the system based on the Markov chain and use the Markov approximation to approach the maximum utility.In addition,we use the count down and select algorithm to implement the process of Markov chain.The simulation results validate the convergence of the Markov approximation.In addition,the gap between the approximate value and optimal values decreases with an increase inβ,which is a positive constant in Markov formulation,according to the simulation results.

Hierarchical and distributed demand response control strategy for thermostatically controlled appliances in smart grid

Thermostatically controlled appliances(TCAs)have great thermal storage capability and are therefore excellent demand response(DR) resources to solve the problem of power fluctuation caused by renewable energy.Traditional centralized management is affected by communication quality severely and thus usually has poor realtime control performance. To tackle this problem, a hierarchical and distributed control strategy for TCAs is established. In the proposed control strategy, target assignment has the feature of self-regulating, owing to the designed target assignment and compensating algorithm which can utilize DR resources maximally in the controlled regions and get better control effects. Besides, the model prediction strategy and customers’ responsive behavior model are integrated into the original optimal temperature regulation(OTR-O), and OTR-O will be evolved into improved optimal temperature regulation. A series of case studies have been given to demonstrate the control effectiveness of the proposed control strategy.