Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable e...Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.展开更多
With the widespread application of combined heat and power(CHP)units,the economic dispatch of integrated electric and district heating systems(IEHSs)has drawn increasing attention.Because the electric power system(EPS...With the widespread application of combined heat and power(CHP)units,the economic dispatch of integrated electric and district heating systems(IEHSs)has drawn increasing attention.Because the electric power system(EPS)and district heating system(DHS)are generally managed separately,the decentralized dispatch pattern is preferable for the IEHS dispatch problem.However,many common decentralized methods suffer from the drawbacks of slow and local convergence.Moreover,the uncertainties of renewable generation cannot be ignored in a decentralized pattern.Additionally,the most commonly used individual chance constraints in distributionally robust optimization cannot consider safety constraints simultaneously,so the safe operation of an IEHS cannot be guaranteed.Thus,distributionally robust joint chance constraints and robust constraints are jointly introduced into the IEHS dispatch problem in this paper to obtain a stronger safety guarantee,and a method combined with Bonferroni and conditional value at risk(CVaR)approximation is presented to transform the original model into a quadratic program.Additionally,a dynamic boundary response(DBR)-based distributed algorithm based on multiparametric programming is proposed for a fast solution.Case studies showcase the necessity of using mixed distributionally robust joint chance constraints and robust constraints,as well as the effectiveness of the DBR algorithm.展开更多
The reliable and coordinated operation of energy systems is becoming increasingly important as renewable energy penetration grows and electricity and gas infrastructures become more interconnected.This study ad-dresse...The reliable and coordinated operation of energy systems is becoming increasingly important as renewable energy penetration grows and electricity and gas infrastructures become more interconnected.This study ad-dresses the challenge of aligning multiple stakeholders’objectives in integrated electricity and gas distribution systems by proposing a sequential constrained optimization method.The method solves the multi-objective optimization problem by sequentially prioritizing each entity’s objective while incorporating others as adaptive-weighted sub-objectives and constraints.This process ensures that all entities participate in a fair and balanced decision-making procedure,ultimately converging to a consensus-based solution.The algorithm is validated using IEEE 33-bus and 118-bus test systems coupled with gas networks.Results show that the proposed method improves optimal resource allocation effectiveness by up to 3.66 compared to individual-objective or aggregated-objective benchmarks.Specifically,the method achieves performance improvements ranging from 0.02 pu to 1.7 pu across four distinct entities,highlighting its superiority in balancing conflicting operational goals.Moreover,the method demonstrates low computational delay and converges in fewer than 15 iterations for all tested cases.The algorithm adapts flexibly to different system configurations and maintains solution stability even under asymmetric stakeholder preferences.These findings indicate that the proposed sequential constrained optimization framework is a scalable and effective approach for equitable,multi-agent coordination in integrated multi-energy systems.展开更多
基金supported in part by the Science and Technology Development Fund,Macao SAR(File no.SKL-IOTSC(UM)-2021-2023,File no.0003/2020/AKP,and File no.0117/2022/A3)the Natural Science Foundation of Jiangsu Province,China(Operational reliability evaluation of multi-source and heterogeneous urban multi-energy systems,BK20220261).
文摘Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.
基金supported by National Natural Science Foundation of China(52377107,52007105)and the Taishan Scholars Program.
文摘With the widespread application of combined heat and power(CHP)units,the economic dispatch of integrated electric and district heating systems(IEHSs)has drawn increasing attention.Because the electric power system(EPS)and district heating system(DHS)are generally managed separately,the decentralized dispatch pattern is preferable for the IEHS dispatch problem.However,many common decentralized methods suffer from the drawbacks of slow and local convergence.Moreover,the uncertainties of renewable generation cannot be ignored in a decentralized pattern.Additionally,the most commonly used individual chance constraints in distributionally robust optimization cannot consider safety constraints simultaneously,so the safe operation of an IEHS cannot be guaranteed.Thus,distributionally robust joint chance constraints and robust constraints are jointly introduced into the IEHS dispatch problem in this paper to obtain a stronger safety guarantee,and a method combined with Bonferroni and conditional value at risk(CVaR)approximation is presented to transform the original model into a quadratic program.Additionally,a dynamic boundary response(DBR)-based distributed algorithm based on multiparametric programming is proposed for a fast solution.Case studies showcase the necessity of using mixed distributionally robust joint chance constraints and robust constraints,as well as the effectiveness of the DBR algorithm.
基金supported by the research fund of Hanyang University(HY-202400000003289)supported by the Korea Institute of Energy Technol-ogy Evaluation and Planning(KETEP)and the Ministry of Trade,In-dustry&Energy(MOTIE)of the Republic of Korea(No.RS-2025-02313547).
文摘The reliable and coordinated operation of energy systems is becoming increasingly important as renewable energy penetration grows and electricity and gas infrastructures become more interconnected.This study ad-dresses the challenge of aligning multiple stakeholders’objectives in integrated electricity and gas distribution systems by proposing a sequential constrained optimization method.The method solves the multi-objective optimization problem by sequentially prioritizing each entity’s objective while incorporating others as adaptive-weighted sub-objectives and constraints.This process ensures that all entities participate in a fair and balanced decision-making procedure,ultimately converging to a consensus-based solution.The algorithm is validated using IEEE 33-bus and 118-bus test systems coupled with gas networks.Results show that the proposed method improves optimal resource allocation effectiveness by up to 3.66 compared to individual-objective or aggregated-objective benchmarks.Specifically,the method achieves performance improvements ranging from 0.02 pu to 1.7 pu across four distinct entities,highlighting its superiority in balancing conflicting operational goals.Moreover,the method demonstrates low computational delay and converges in fewer than 15 iterations for all tested cases.The algorithm adapts flexibly to different system configurations and maintains solution stability even under asymmetric stakeholder preferences.These findings indicate that the proposed sequential constrained optimization framework is a scalable and effective approach for equitable,multi-agent coordination in integrated multi-energy systems.
