Multi energy integrated service stations have strong comprehensive energy and coupling properties, covering functional units such as substation, multi type energy conversion station, data center, distributed power generation, charging and replacement power station, wireless base station and so on. However, with the continuous improvement of the physical complexity of power grid information, there are still great theoretical and practical difficulties on how to build the operation optimization architecture of energy integrated service station and realize the organic integration of energy flow, data flow and business flow. The typical model forms of various equilibrium equality constraints and inequality constraints between stations and stations are established, and the multi-objective operation optimization model is established and solved. The results show that it improves the level of multi energy conversion, multi energy complementarity, comprehensive energy utilization efficiency, realizes the purpose of collaborative control optimization of multiple energy integrated service stations, and effectively promotes the maximum local consumption of renewable energy.
This paper introduces access control which traditionally researched in the field of information security into the area of collaborative system. We build an application-oriented access control mechanism and use it to analyze the fundamentality of access control to cooperation in a web-based knowledge-sharing system. The mechanism is simple but clear and verified by projects. We also hope readers can take advantage of the design of our access control mechanism and knowledge-sharing system which is common part of collaboration suites. Finally we find access control does contribute and help members to cooperate better in the system.
In response to the current issues of high energy consumption, environmental pollution, and safety hazards associated with the vinyl chloride distillation process, this study has developed a sustainable, economically energy-efficient, and safe multi-objective optimization method for the vinyl chloride distillation process. Based on the actual operation of the vinyl chloride distillation process in enterprises, this research employs the Non-dominated Sorting Genetic Algorithm III (NSGA-III) to optimize key parameters of the distillation operation, aiming to achieve multiple objectives such as improving product quality, reducing energy consumption, decreasing CO2 emissions, and enhancing process safety. The safety performance of the optimized scheme was comprehensively evaluated through simulation with Aspen Plus V14 software, combined with Hazard and Operability (HAZOP) qualitative risk analysis and quantitative risk analysis based on Aspen Plus. Through comparative analysis with the original design scheme, the following conclusions were drawn: all optimization plans (A, B, C, D) are superior to the original design to varying degrees. Further research revealed that as the number of iterations of the genetic algorithm increases, the optimization plans have significantly improved in terms of multi-objective performance, highlighting the importance of adequate iteration in the process of finding the optimal solution. The outcomes of this study not only provide an effective strategy for the optimization of the vinyl chloride distillation process but also offer a theoretical basis and practical guidance for the green development and safe production in the chemical industry.
Role based access control (RBAC) has received much attention for more than a decade as one of the most attractive solutions for access control in Web-based information systems. However, its associated characteristics are often not suitable for a varying organization requiring a flexible structure. In order to address this limitation, it may essentially be required to assess more flexibility to access control mechanisms. To this end, we propose a new extended access control mechanisms incorporating three authentication dimensions based on user, department, and role. We then demonstrate that the proposed mechanisms can improve utilization of a Web-based knowledge-sharing system.
At present, the full utilization of decentralized resources at the bottom user-side in the power system has become one of the important means of energy transformation and utilization and promoting the sustainable development of economy and society. However, the user-side resources have the characteristics of large quantity, different types, serious parameter differentiation, operation laws and regulation characteristics. After large-scale access, there are problems of effective perception and accurate aggregation in participating in power grid regulation. The existing direct acquisition and direct control model based on single equipment is difficult to adapt to the multi-form load aggregation under the demand of multiple power grid regulation. The quantitative evaluation method of user-side resource aggregation adaptability for different power grid regulation requirements constructs the evaluation systems of 5 primary indicators, 11 secondary indicators and 34 tertiary indicators respectively, which is conducive to guiding the resource aggregation under the requirements of power grid regulation for different granularity resource aggregation, response time and duration, It realizes the adaptive quantitative evaluation of indicators under different regulation needs, and fully excavates the regulation potential of user-side adjustable resources, which has a certain engineering application prospect.
Equipment maintenance is one of the essential tasks for manufacturing industries. There have been a number of information systems developed to cope with equipment malfunctions. Most fault diagnosis systems are applications of expert systems which have two drawbacks with regard to knowledge acquisition. One is the lack of knowledge continuity; the other is the limited source of knowledge being incapable of combining knowledge of entire workforce. In this study, we propose an equipment maintenance decision support system architecture with a flexible knowledge maintenance methodology. A case implementation to a sewage management company with multiple distributed plants is introduced to show that the proposed approach helps more efficient utilization of experience-based knowledge in maintaining equipments.
State estimation (SE) is regarded as an essential tool for achieving the secure and efficient operation of distribution networks, and extensive research on SE has been conducted over the past three decades. Nonetheless, the high penetration of distribution generations (DGs) is accompanied by uncertainties and dynamics, and the extensive application of intelligent electronic devices (IEDs) is associated with data processing issues, all of which raise new challenges, and these issues must be taken care of for further development of SE in smart distribution networks. This paper attempts to present a comprehensive literature review of numerous works that address various issues in SE, examining key technical research issues and future perspectives. Hopefully, it will be able to meet the needs for the development of smart distribution networks.
Business process management (BPM) as a research discipline has been around for quite a while. Extensive research effort has been devoted to advancing BPM methodologies, techniques, and tools. Despite its continuous development over the years, little attention has been given to understanding the evolutionary process of BPM research. In this paper, we attempt to analyze and rationalize the development of BPM research through a longitudinal literature analysis. We collect and review BPM articles from leading information systems (IS) journals. Each article is categorized based on its demographic background, year of publication, research method, and research area. We adopt a meta-analysis approach in analyzing the data produced from a categorization process. Our analysis provides an overview of BPM research from multiple perspectives. It also summarizes the publication behavior in the field. We hope our work will help BPM researchers identify research areas that are important yet under-researched. It may also be useful in guiding the future direction of BPM research.
Under the background of "Carbon Peak, Carbon Neutralization" national strategic carbon reduction goal, establishing an appropriate carbon trading mechanism is an effective way to achieve carbon reduction . This paper establishes an optimal model of economic and environmental dispatching for a virtual power plant (VPP) which contains energy storage, gas turbine, wind power and photovoltaic generation when it participates in carbon trading. Firstly, the carbon trading mechanism is introduced, and the scenario generation method considering the uncertainty of wind power based on Gaussian kernel function theory is formed to get the classical scene curve of wind power. Then, a mixed integer quadratic programming model for coordinated dispatch of distributed power and energy storage in VPP under carbon trading environment is established with the objective of minimizing the total cost of VPP. Finally, the example validation shows that the model reduces the total cost and total carbon emissions of the system, greatly improves the consumption of clean energy, and makes the scheduling of virtual power plants take into account both economic and environmental benefits.
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