Optimal Operation Strategy of Electricity-Hydrogen Regional Energy System under Carbon-Electricity Market Trading

Given the“double carbon”objective and the drive toward low-carbon power,investigating the integration and interaction within the carbon-electricity market can enhance renewable energy utilization and facilitate energy conservation and emission reduction endeavors.However,further research is necessary to explore operational optimization methods for establishing a regional energy system using Power-to-Hydrogen(P2H)technology,focusing on participating in combined carbon-electricity market transactions.This study introduces an innovative Electro-Hydrogen Regional Energy System(EHRES)in this context.This system integrates renewable energy sources,a P2H system,cogeneration units,and energy storage devices.The core purpose of this integration is to optimize renewable energy utilization and minimize carbon emissions.This study aims to formulate an optimal operational strategy for EHRES,enabling its dynamic engagement in carbon-electricity market transactions.The initial phase entails establishing the technological framework of the electricity-hydrogen coupling system integrated with P2H.Subsequently,an analysis is conducted to examine the operational mode of EHRES as it participates in carbon-electricity market transactions.Additionally,the system scheduling model includes a stepped carbon trading price mechanism,considering the combined heat and power generation characteristics of the Hydrogen Fuel Cell(HFC).This facilitates the establishment of an optimal operational model for EHRES,aiming to minimize the overall operating cost.The simulation example illustrates that the coordinated operation of EHRES in carbon-electricity market transactions holds the potential to improve renewable energy utilization and reduce the overall system cost.This result carries significant implications for attaining advantages in both low-carbon and economic aspects.

A Storage and Transmission Joint Planning Method for Centralized Wind Power Transmission

Centralized delivery has become the main operation mode under the scaled development of wind power.Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base.The configuration of transmission capacity,which has the features of low utilization and poor economy,is hardly matching correctly due to the volatility and low energy density of wind.The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity,but facing the issue of energy storage cost recovery.Therefore,it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission.This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage,reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission.Then,analyze the multi-functional cost-sharing mode of energy storage,improve the efficiency of energy storage cost recovery.Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage,and realizes the transmission capacity optimization coordination and optimization with energy storage.The proposed method is verified by a wind base located in Northeast China.

Internet-of-things enabled supply chain planning and coordination with big data services:Certain theoretic implications

Recent advances in information technology have led to profound changes in global manufacturing.This study focuses on the theoretical and practical challenges and oppor-tunities arising from the Internet of Things(IoT)as it enables new ways of supply-chain operations partially based on big-data analytics and changes in the nature of industries.We intend to reveal the acting principle of the IoT and its implications for big-data ana-lytics on the supply chain operational performance,particularly with regard to dynamics of operational coordination and optimization for supply chains by leveraging big data ob-tained from smart connected products(SCPs),and the governance mechanism of big-data sharing.Building on literature closely related to our focal topic,we analyze and deduce the substantial influence of disruptive technologies and emerging business models including the IoT,big data analytics and SCPs on many aspects of supply chains,such as consumers value judgment,products development,resources allocation,operations optimization,revenue management and network governance.Furthermore,we propose several research directions and corresponding research schemes in the new situations.This study aims to promote future researches in the field of big data-driven supply chain management with the IoT,help firms improve data-driven operational decisions,and provide government a reference to advance and regulate the development of the IoT and big data industry.