Research on Establishment of Vehicle Energy Distribution Model and Energy Consumption Optimization Based on Electric Hybrid System

In order to improve the adaptability and accuracy of the system average efficiency model in energy consumption analysis of working conditions, this paper presents a vehicle energy distribution model based on the layout and powertrain operation features of the electric hybrid system, and presents a vehicle energy consumption optimization method for control strategy and hardware quality optimization based on the guidance of the energy distribution model.

Electric Power-grid Friendly Characteristic Data Center Energy Consumption Optimization Method

With the acceleration of the digitization process, the load of the data center on the power grid continues to increase. During the operation of the data center, the load demand on the power grid is relatively large, and the load demand on the power grid fluctuates greatly. In the Power industry, the average PUE(power usage effectiveness) of data center is above 2, which is extremely unfriendly to the power grid. This paper proposes and summarizes the optimization parameters at various levels, the energy efficiency of software and hardware, and provides a method for optimization through global variables for high-efficiency and energyconsuming data centers, which can minimize cooling energy consumption and IT energy consumption. To build a electric power grid-friendly characteristic data center with high efficiency and low energy consumption.

Research on Multi-Agent Systems in a Smart Small Grid for Resource Apportionment and Planning

With the advancement in the technology, deployment of sensors in the industrial or public building is increasing rapidly. The basic aim is to obtain the data from the environment and decision making to the energy saving. The activities caused by the human results the undergoing negative change in the environment. There are many techniques available for decision making and consider the environmental factors solely which cause the energy consumption. However, user’s preferences are not adapted by the systems, but at energy consumption optimization, these systems are very successful. The end-users use the system which considers the factors and their wellbeing are get affected. The distributed generation is incorporated by the Smart Small Grid (SSG), communication network and the sensors for the more reliable, flexible and efficient grid. The energy saving system is presented in this paper which also adapts to the inhabitants preferences apart from environmental conditions consideration. The architecture of Multi-Agent System (MAS) and the agents are utilized for negotiation process performance between the users comfort preferences and optimization degree that according to these preferences, achievement of system is done. The energy consumption of 40% is obtained and in the inhabitants' behavior pattern, the algorithm was specialized. The 16.89% of reduction is obtained by the existing system and it was focused to obtain the agreement between the system and users for user preference satisfaction and the energy optimization is also performed at the same time.

Comment on Hamayun et al. Evaluation of Two-Column Air Separation Processes Based on Exergy Analysis. Energies 2020, 13, 6361

Oxygen production from air belongs to energy-intense processes and, as a result, possibilities for its decrease are a frequent topic of optimization studies, often performed with simulation software such as Aspen Plus or Aspen HYSYS. To obtain veritable results and sound solutions, a suitable calculation method hand in hand with justified assumptions and simplifications should form the base of any such studies. Thus, an analysis of the study by Hamayun et al., Energies 2020, 13, 6361, has been performed, and several weak spots of the study, including oversimplified assumptions, improper selection of a thermodynamic package for simulation and omission of certain technological aspects relevant for energy consumption optimization studies, were identified. For each of the weak spots, a recommendation based on good praxis and relevant scientific literature is provided, and general recommendations are formulated with the hope that this comment will aid all researchers utilizing Aspen Plus and Aspen HYSYS software in their work.