As the power system transitions to a new green and low-carbon paradigm,the penetration of renewable energy in China’s power system is gradually increasing.However,the variability and uncertainty of renewable energy o...As the power system transitions to a new green and low-carbon paradigm,the penetration of renewable energy in China’s power system is gradually increasing.However,the variability and uncertainty of renewable energy output limit its profitability in the electricity market and hinder its market-based integration.This paper first constructs a wind-solar-thermalmulti-energy complementary system,analyzes its external game relationships,and develops a bi-level market optimization model.Then,it considers the contribution levels of internal participants to establish a comprehensive internal distribution evaluation index system.Finally,simulation studies using the IEEE 30-bus system demonstrate that the multi-energy complementary system stabilizes nodal outputs,enhances the profitability of market participants,and promotes the market-based integration of renewable energy.展开更多
Multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable development.This study investigates an effective energy management strategy(EMS)for MEMG.First,an energy man...Multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable development.This study investigates an effective energy management strategy(EMS)for MEMG.First,an energy management system model that allows for intra-microgrid energy conversion is developed,and the corresponding Markov decision process(MDP)problem is formulated.Subsequently,an improved double deep Q network(iDDQN)algorithm is proposed to enhance the exploration ability by modifying the calculation of the Q value,and a prioritized experience replay(PER)is introduced into the iDDQN to improve the training speed and effectiveness.Finally,taking advantage of the federated learning(FL)and iDDQN algorithms,a federated iDDQN is proposed to design an MEMG energy management strategy to enable each microgrid to share its experiences in the form of local neural network(NN)parameters with the federation layer,thus ensuring the privacy and security of data.The simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO_2 emissions and protecting data privacy.展开更多
The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the co...The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the complementary and efficient use of different types of energy, which is the basic component of the physical layer of the Energy Internet. In this paper, aiming at the demand of the energy application for towns, a distributed energy system based on multi-energy complementary is constructed. Firstly, the supply condition of the distributed energy for the demonstration project is analyzed, and the architecture of the multi-energy complementary distributed energy system is established. Then the regulation strategy of the multi-energy complementary distributed energy system is proposed. Finally, an overall system scheme for the multi-energy complementary distributed energy system suitable for towns is developed, which provides a solid foundation for the development and promotion of the multi-energy complementary distributed energy system.展开更多
Under the current long-term electricity market mechanism,new energy and thermal power face issues such as deviation assessment and compression of generation space.The profitability of market players is limited.Simulta...Under the current long-term electricity market mechanism,new energy and thermal power face issues such as deviation assessment and compression of generation space.The profitability of market players is limited.Simultaneously,the cooperation model among various energy sources will have a direct impact on the alliance’s revenue and the equity of income distribution within the alliance.Therefore,integrating new energy with thermal power units into an integrated multi-energy complementary system to participate in the long-term electricity market holds significant potential.To simulate and evaluate the benefits and internal distribution methods of a multi-energy complementary system participating in long-term market transactions,this paper first constructs a multi-energy complementary system integrated with new energy and thermal power generation units at the same connection point,and participates in the annual bilateral game as a unified market entity to obtain the revenue value under the annual bilateral market.Secondly,based on the entropy weight method,improvements are made to the traditional Shapley value distribution model,and an internal distribution model for multi-energy complementary systems with multiple participants is constructed.Finally,a Markov Decision Process(MDP)evaluation system is constructed for practical case verification.The research results show that the improved Shapley value distribution model achieves higher satisfaction,providing a reasonable allocation scheme for multi-energy complementary cooperation models.展开更多
Liquefied natural gas (LNG),recognized as the primary form for natural gas transportation,can release substantial cold energy during gasification.To make efficient use of this cold energy,this paper proposes a data-dr...Liquefied natural gas (LNG),recognized as the primary form for natural gas transportation,can release substantial cold energy during gasification.To make efficient use of this cold energy,this paper proposes a data-driven stochastic robust (DDSR) energy management method for the multi-stage cascade utilization of LNG cold energy in a multi-energy microgrid (MEMG) of an LNG receiving terminal.Firstly,a general scheduling model considering the flexible coupling between adjacent stages,energy losses,and electric power consumption for the cascade utilization of LNG cold energy is introduced.This model is applied to carbon capture,cryogenic power generation,and direct cooling,which are sequentially associated with the deep,medium,and shallow cooling zones of LNG cold energy,respectively.Moreover,a two-stage energy management framework is proposed to coordinate the cascade utilization of LNG cold energy with other energy resources in the MEMG.To tackle the uncertainties of renewable energy generation and various loads,a DDSR-based solution method is developed,aiming to achieve both economic benefits and solution robustness by identifying the worst-case scenarios and the corresponding worst-case probability.Accordingly,a Benders decomposition-based solution algorithm is proposed to divide the original problem into a master problem and a slave problem,which are solved iteratively.The simulation results verify the effectiveness and high efficiency of the proposed DDSR energy management method for multi-stage cascade utilization of LNG cold energy.展开更多
Multi-energy microgrid(MEMG)offers an effective approach to deal with energy demand diversification and new energy consumption on the consumer side.In MEMG,it is critical to deploy an energy management system(EMS)to e...Multi-energy microgrid(MEMG)offers an effective approach to deal with energy demand diversification and new energy consumption on the consumer side.In MEMG,it is critical to deploy an energy management system(EMS)to efficiently utilize energy and ensure reliable system operation.To help EMS formulate optimal dispatching schemes,a deep reinforcement learning(DRL)-based MEMG energy management scheme with renewable energy source(RES)uncertainty is proposed in this paper.To accurately describe the operating state of the MEMG,the off-design performance model of energy conversion devices is considered in scheduling.The nonlinear optimal dispatching model is expressed as a Markov decision process(MDP)and is then addressed by the twin delayed deep deterministic policy gradient(TD3)algorithm.In addition,to accurately describe the uncertainty of RES,the conditional-least squares generative adversarial networks(C-LSGANs)method based on RES forecast power is proposed to construct the scenario set of RES power generation.The generated data of RES is used to schedule the acquisition of caps and floors for the purchase of electricity and natural gas.Based on this,the superior energy supply sector can formulate solutions in advance to tackle the uncertainty of RES.Finally,the simulation analysis demonstrates the validity and superiority of the method.展开更多
The isolated hybrid AC/DC multi-energy microgrid(IH-MEMG)offers an effective solution for meeting the electrical,heating,and cooling energy demands of remote and off-grid areas.For an IH-MEMG,system transient dynamics...The isolated hybrid AC/DC multi-energy microgrid(IH-MEMG)offers an effective solution for meeting the electrical,heating,and cooling energy demands of remote and off-grid areas.For an IH-MEMG,system transient dynamics(i.e.,frequency or voltage of the electricity network)and economics are critical aspects that pose the greatest concern to operators.However,these aspects are generally investigated separately owing to their different time scales.To integrate these aspects from the scope of real-time control,this study proposes a bi-layer coordinated power regulation strategy considering system dynamics and economics for the IH-MEMG.First,coupling relationships among multiple sub-networks are analyzed,and a frequency-voltage coupling model between the AC and DC sides is established.Then,a bi-layer coordinated power regulation strategy is developed for the IH-MEMG with output characteristics of different components involved:the primary layer includes a multi-entity power support mechanism used to improve the dynamics of the electricity network,wherein a cooperation principle of the combined cooling,heating,and power(CCHP)unit and energy storage unit(ESU)is designed in detailed;meanwhile,the secondary layer includes a real-time economics-oriented optimization framework used to adjust the power references of multiple units generated from the primary layer for cost efficiency improvement(notably,the primary layer can work independently).Finally,the effectiveness of the proposed strategy is verified through comprehensive simulations under varying operation scenarios.展开更多
基金funded by the National Key R&D Program of China,grant number 2019YFB1505400.
文摘As the power system transitions to a new green and low-carbon paradigm,the penetration of renewable energy in China’s power system is gradually increasing.However,the variability and uncertainty of renewable energy output limit its profitability in the electricity market and hinder its market-based integration.This paper first constructs a wind-solar-thermalmulti-energy complementary system,analyzes its external game relationships,and develops a bi-level market optimization model.Then,it considers the contribution levels of internal participants to establish a comprehensive internal distribution evaluation index system.Finally,simulation studies using the IEEE 30-bus system demonstrate that the multi-energy complementary system stabilizes nodal outputs,enhances the profitability of market participants,and promotes the market-based integration of renewable energy.
基金supported by the Research and Development of Key Technologies of the Regional Energy Internet based on Multi-Energy Complementary and Collaborative Optimization(BE2020081)。
文摘Multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable development.This study investigates an effective energy management strategy(EMS)for MEMG.First,an energy management system model that allows for intra-microgrid energy conversion is developed,and the corresponding Markov decision process(MDP)problem is formulated.Subsequently,an improved double deep Q network(iDDQN)algorithm is proposed to enhance the exploration ability by modifying the calculation of the Q value,and a prioritized experience replay(PER)is introduced into the iDDQN to improve the training speed and effectiveness.Finally,taking advantage of the federated learning(FL)and iDDQN algorithms,a federated iDDQN is proposed to design an MEMG energy management strategy to enable each microgrid to share its experiences in the form of local neural network(NN)parameters with the federation layer,thus ensuring the privacy and security of data.The simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO_2 emissions and protecting data privacy.
文摘The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the complementary and efficient use of different types of energy, which is the basic component of the physical layer of the Energy Internet. In this paper, aiming at the demand of the energy application for towns, a distributed energy system based on multi-energy complementary is constructed. Firstly, the supply condition of the distributed energy for the demonstration project is analyzed, and the architecture of the multi-energy complementary distributed energy system is established. Then the regulation strategy of the multi-energy complementary distributed energy system is proposed. Finally, an overall system scheme for the multi-energy complementary distributed energy system suitable for towns is developed, which provides a solid foundation for the development and promotion of the multi-energy complementary distributed energy system.
文摘Under the current long-term electricity market mechanism,new energy and thermal power face issues such as deviation assessment and compression of generation space.The profitability of market players is limited.Simultaneously,the cooperation model among various energy sources will have a direct impact on the alliance’s revenue and the equity of income distribution within the alliance.Therefore,integrating new energy with thermal power units into an integrated multi-energy complementary system to participate in the long-term electricity market holds significant potential.To simulate and evaluate the benefits and internal distribution methods of a multi-energy complementary system participating in long-term market transactions,this paper first constructs a multi-energy complementary system integrated with new energy and thermal power generation units at the same connection point,and participates in the annual bilateral game as a unified market entity to obtain the revenue value under the annual bilateral market.Secondly,based on the entropy weight method,improvements are made to the traditional Shapley value distribution model,and an internal distribution model for multi-energy complementary systems with multiple participants is constructed.Finally,a Markov Decision Process(MDP)evaluation system is constructed for practical case verification.The research results show that the improved Shapley value distribution model achieves higher satisfaction,providing a reasonable allocation scheme for multi-energy complementary cooperation models.
基金supported in part by the National Natural Science Foundation of China(No.52307091)in part by the Natural Science Foundation of Jiangsu Province(No.BK20230952)in part by the China Postdoctoral Science Foundation(No.2023M740976).
文摘Liquefied natural gas (LNG),recognized as the primary form for natural gas transportation,can release substantial cold energy during gasification.To make efficient use of this cold energy,this paper proposes a data-driven stochastic robust (DDSR) energy management method for the multi-stage cascade utilization of LNG cold energy in a multi-energy microgrid (MEMG) of an LNG receiving terminal.Firstly,a general scheduling model considering the flexible coupling between adjacent stages,energy losses,and electric power consumption for the cascade utilization of LNG cold energy is introduced.This model is applied to carbon capture,cryogenic power generation,and direct cooling,which are sequentially associated with the deep,medium,and shallow cooling zones of LNG cold energy,respectively.Moreover,a two-stage energy management framework is proposed to coordinate the cascade utilization of LNG cold energy with other energy resources in the MEMG.To tackle the uncertainties of renewable energy generation and various loads,a DDSR-based solution method is developed,aiming to achieve both economic benefits and solution robustness by identifying the worst-case scenarios and the corresponding worst-case probability.Accordingly,a Benders decomposition-based solution algorithm is proposed to divide the original problem into a master problem and a slave problem,which are solved iteratively.The simulation results verify the effectiveness and high efficiency of the proposed DDSR energy management method for multi-stage cascade utilization of LNG cold energy.
基金supported by National Natural Science Foundation of China(51777027)。
文摘Multi-energy microgrid(MEMG)offers an effective approach to deal with energy demand diversification and new energy consumption on the consumer side.In MEMG,it is critical to deploy an energy management system(EMS)to efficiently utilize energy and ensure reliable system operation.To help EMS formulate optimal dispatching schemes,a deep reinforcement learning(DRL)-based MEMG energy management scheme with renewable energy source(RES)uncertainty is proposed in this paper.To accurately describe the operating state of the MEMG,the off-design performance model of energy conversion devices is considered in scheduling.The nonlinear optimal dispatching model is expressed as a Markov decision process(MDP)and is then addressed by the twin delayed deep deterministic policy gradient(TD3)algorithm.In addition,to accurately describe the uncertainty of RES,the conditional-least squares generative adversarial networks(C-LSGANs)method based on RES forecast power is proposed to construct the scenario set of RES power generation.The generated data of RES is used to schedule the acquisition of caps and floors for the purchase of electricity and natural gas.Based on this,the superior energy supply sector can formulate solutions in advance to tackle the uncertainty of RES.Finally,the simulation analysis demonstrates the validity and superiority of the method.
基金supported by the International Science and Technology Cooperation Program of China(Grant No.2022YFE0129300)the National Natural Science Foundation of China(Grant Nos.U22B20104,52277090,52207097)+2 种基金the Science and Technology Innovation Program of Hunan Province(Grant No.2023RC3102)the Excellent Innovation Youth Program of Changsha of China(Grant No.kq2209010)the Key Research and Development Program of Hunan Province(Grant No.2023GK2007)。
文摘The isolated hybrid AC/DC multi-energy microgrid(IH-MEMG)offers an effective solution for meeting the electrical,heating,and cooling energy demands of remote and off-grid areas.For an IH-MEMG,system transient dynamics(i.e.,frequency or voltage of the electricity network)and economics are critical aspects that pose the greatest concern to operators.However,these aspects are generally investigated separately owing to their different time scales.To integrate these aspects from the scope of real-time control,this study proposes a bi-layer coordinated power regulation strategy considering system dynamics and economics for the IH-MEMG.First,coupling relationships among multiple sub-networks are analyzed,and a frequency-voltage coupling model between the AC and DC sides is established.Then,a bi-layer coordinated power regulation strategy is developed for the IH-MEMG with output characteristics of different components involved:the primary layer includes a multi-entity power support mechanism used to improve the dynamics of the electricity network,wherein a cooperation principle of the combined cooling,heating,and power(CCHP)unit and energy storage unit(ESU)is designed in detailed;meanwhile,the secondary layer includes a real-time economics-oriented optimization framework used to adjust the power references of multiple units generated from the primary layer for cost efficiency improvement(notably,the primary layer can work independently).Finally,the effectiveness of the proposed strategy is verified through comprehensive simulations under varying operation scenarios.
