An Improved Differential Evolution Whale Algorithm for Economic Load Distribution

An improved optimization algorithm combining the differential evolution algorithm and the whale algorithm is proposed for the problem of not being able to get rid of the local optimum in the economic load distribution algorithm. The algorithm adopts a nonlinear convergence strategy, a crossover strategy of differential evolution and the introduction of an elimination mechanism, which balances the global search and local exploitation ability of the algorithm and improves the accuracy of the solved optimal solution. The 13-unit and 40-unit systems are selected for economic load distribution calculation, and the experimental results show that the proposed improved algorithm is superior in distributing the economic load of the power system and can effectively reduce the economic cost.

Environment, Health and Economic Growth： Study on Optimal Energy Tax Revenue Distribution

Under the dual pressures of economic growth and environmental protection,how to curb pollution and raise public welfare without harming the economy or with minimal economic output losses has become a major question facing China in its efforts to transform growth pattern and accomplish economic transition. On the basis of an overlapping generation(OLG) model, this paper introduces the health effects of environmental pollution to systematically discuss the optimal distribution ratio of energy tax revenues in subsidizing household income and emission abatement under given tax rates to reduce the risks of "environment-health-poverty" trap. Our research shows that an optimal distribution ratio for maximizing per capita output or an optimal distribution ratio for maximizing public welfare exists. Based on China's actual parameters, however, this study has found that China's energy tax revenue distribution policy hardly meets the two optimal targets at the same time. Specific distribution ratio is subject to government decision-making preference, and needs to be adjusted according to actual differences.

The challenges that head nurses confront on financial management today:A qualitative study

Aim: To explore challenges that Chinese head nurses confront on financial management from the perspective of different levels of nursing and non-nursing managers and to provide contemporary nurse managers with suitable supports.Methods: Eighteen nursing leaders in different levels were divided into two groups: Junior Leadership Group (head nurses) and Senior Leadership Group (nurse coordinator, nurse executive, and vice-president of the hospital). All the subjects were invited to participate in a semi-structured interview. The interviews were audio-taped and transcribed, and data were analyzed using a comparative content approach. Results: The four following challenges that head nurses confront on financial management practice were identified from the research findings: 1) lack of intrinsic motivation;2) insufficient training and edu-cation on financial management and nursing economics;3) desires for cross-uniting communication and cooperation;4) insufficient reference managerial tool. Conclusions: The confusion confronted by head nurses in Changsha include three aspects: managerial roles, managerial training, and managerial tools. Cooperative management model, evidence-based management training, and data-driven tools will contribute to improving the financial management capacity of nurse managers.

Recent progress on the study of distributed economic dispatch in smart grid:an overview

Designing an efficient distributed economic dispatch(DED)strategy for the smart grid(SG)in the presence of multiple generators plays a paramount role in obtaining various benefits of a new generation power syst em,such as easy implementation,low maintenance cos t,high energy efficiency,and strong robus tn ess agains t uncertainties.It has drawn a lot of interest from a wide variety of scientific disciplines,including power engineering,control theory,and applied mathematics.We present a state-of-the-art review of some theoretical advances toward DED in the SG,with a focus on the literature published since 2015.We systematically review the recent results on this topic and subsequently categorize them into distributed discrete-and continuous-time economic dispatches of the SG in the presence of multiple generators.After reviewing the literature,we briefly present some future research directions in DED for the SG,including the distributed security economic dispatch of the SG,distributed fast economic dispatch in the SG with practical constraints,efficient initialization-free DED in the SG,DED in the SG in the presence of smart energy storage batteries and flexible loads,and DED in the SG with artificial intelligence technologies.

Fully Distributed Economic Dispatch for Cyber-physical Power System with Time Delays and Channel Noises

Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation cost.In fact,the power grid is becoming a cyber-physical power system(CPPS).Therefore,the quality of communication is a key point.In this paper,considering two important factors,i.e.,time delays and channel noises,a fully distributed consensus based algorithm is proposed for solving EDP.The critical maximum allowable upper bounds of heterogeneous communication delays and self-delays are obtained.It should be pointed out that the proposed algorithm can be robust against the time-varying delays and channel noises considering generator constraints.In addition,even with time-varying delays and channel noises,the power balance of supply and demand is not broken during the optimization.Several simulation studies are presented to validate the correctness and superiority of the developed results.