Xiang Huo, Boming Liu, Jin Dong, Jianming Lian, Mingxi Liu
Reinforcement learning (RL)-based methods have achieved significant success in managing grid-interactive efficient buildings (GEBs). However, RL does not carry intrinsic guarantees of constraint satisfaction, which may lead to severe safety consequences. Besides, in GEB control applications, most existing safe RL approaches rely only on the regularisation parameters in neural networks or penalty of rewards, which often encounter challenges with parameter tuning and lead to catastrophic constraint violations. To provide enforced safety guarantees in controlling GEBs, this paper designs a physics-inspired safe RL method whose decision-making is enhanced through safe interaction with the environment. Different energy resources in GEBs are optimally managed to minimize energy costs and maximize customer comfort. The proposed approach can achieve strict constraint guarantees based on prior knowledge of a set of developed hard steady-state rules. Simulations on the optimal management of GEBs, including heating, ventilation, and air conditioning (HVAC), solar photovoltaics, and energy storage systems, demonstrate the effectiveness of the proposed approach.
{"title":"Optimal Management of Grid-Interactive Efficient Buildings via Safe Reinforcement Learning","authors":"Xiang Huo, Boming Liu, Jin Dong, Jianming Lian, Mingxi Liu","doi":"arxiv-2409.08132","DOIUrl":"https://doi.org/arxiv-2409.08132","url":null,"abstract":"Reinforcement learning (RL)-based methods have achieved significant success\u0000in managing grid-interactive efficient buildings (GEBs). However, RL does not\u0000carry intrinsic guarantees of constraint satisfaction, which may lead to severe\u0000safety consequences. Besides, in GEB control applications, most existing safe\u0000RL approaches rely only on the regularisation parameters in neural networks or\u0000penalty of rewards, which often encounter challenges with parameter tuning and\u0000lead to catastrophic constraint violations. To provide enforced safety\u0000guarantees in controlling GEBs, this paper designs a physics-inspired safe RL\u0000method whose decision-making is enhanced through safe interaction with the\u0000environment. Different energy resources in GEBs are optimally managed to\u0000minimize energy costs and maximize customer comfort. The proposed approach can\u0000achieve strict constraint guarantees based on prior knowledge of a set of\u0000developed hard steady-state rules. Simulations on the optimal management of\u0000GEBs, including heating, ventilation, and air conditioning (HVAC), solar\u0000photovoltaics, and energy storage systems, demonstrate the effectiveness of the\u0000proposed approach.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Communication topology is a crucial part of a distributed control implementation for cyber-physical systems, yet is typically treated as a constraint within control design problems rather than a design variable. We propose a data-driven method for designing an optimal topology for the purpose of distributed control when a system model is unavailable or unaffordable, via a mixed-integer second-order conic program. The approach demonstrates improved control performance over random topologies in simulations and efficiently drops links which have a small effect on predictor accuracy, which we show correlates well with closed-loop control cost.
{"title":"Value of Communication: Data-Driven Topology Optimization for Distributed Linear Cyber-Physical Systems","authors":"Michael Nestor, Fei Teng","doi":"arxiv-2409.08116","DOIUrl":"https://doi.org/arxiv-2409.08116","url":null,"abstract":"Communication topology is a crucial part of a distributed control\u0000implementation for cyber-physical systems, yet is typically treated as a\u0000constraint within control design problems rather than a design variable. We\u0000propose a data-driven method for designing an optimal topology for the purpose\u0000of distributed control when a system model is unavailable or unaffordable, via\u0000a mixed-integer second-order conic program. The approach demonstrates improved\u0000control performance over random topologies in simulations and efficiently drops\u0000links which have a small effect on predictor accuracy, which we show correlates\u0000well with closed-loop control cost.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a novel approach to distributed pose estimation in the multi-agent system based on an invariant Kalman filter with covariance intersection. Our method models uncertainties using Lie algebra and applies object-level observations within Lie groups, which have practical application value. We integrate covariance intersection to handle estimates that are correlated and use the invariant Kalman filter for merging independent data sources. This strategy allows us to effectively tackle the complex correlations of cooperative localization among agents, ensuring our estimates are neither too conservative nor overly confident. Additionally, we examine the consistency and stability of our algorithm, providing evidence of its reliability and effectiveness in managing multi-agent systems.
{"title":"Covariance Intersection-based Invariant Kalman Filtering(DInCIKF) for Distributed Pose Estimation","authors":"Haoying Li, Xinghan Li, Shuaiting Huang, Chao yang, Junfeng Wu","doi":"arxiv-2409.07933","DOIUrl":"https://doi.org/arxiv-2409.07933","url":null,"abstract":"This paper presents a novel approach to distributed pose estimation in the\u0000multi-agent system based on an invariant Kalman filter with covariance\u0000intersection. Our method models uncertainties using Lie algebra and applies\u0000object-level observations within Lie groups, which have practical application\u0000value. We integrate covariance intersection to handle estimates that are\u0000correlated and use the invariant Kalman filter for merging independent data\u0000sources. This strategy allows us to effectively tackle the complex correlations\u0000of cooperative localization among agents, ensuring our estimates are neither\u0000too conservative nor overly confident. Additionally, we examine the consistency\u0000and stability of our algorithm, providing evidence of its reliability and\u0000effectiveness in managing multi-agent systems.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the expansion of the power grid and the increase of the proportion of new energy sources, the uncertainty and random factors of the power grid increase, endangering the safe operation of the system. It is particularly important to find out the critical links of vulnerability in the power grid to ensure the reliability of the power grid operation. Aiming at the problem that the identification speed of the traditional critical link of vulnerability identification methods is slow and difficult to meet the actual operation requirements of the power grid, the improved graph attention network (IGAT) based identification method of the critical link is proposed. First, the evaluation index set is established by combining the complex network theory and the actual operation data of power grid. Secondly, IGAT is used to dig out the mapping relationship between various indicators and critical links of vulnerability during the operation of the power grid, establish the identification model of critical links of vulnerability, and optimize the original graph attention network considering the training accuracy and efficiency. Thirdly, the original data set is obtained through simulation, and the identification model is trained, verified and tested. Finally, the model is applied to the improved IEEE 30-node system and the actual power grid, and the results show that the proposed method is feasible, and the accuracy and speed are better than that of traditional methods. It has certain engineering utilization value.
{"title":"Critical link identification of power system vulnerability based on modified graph attention network","authors":"Changgang Wang, Xianwei Wang, Yu Cao, Yang Li, Qi Lv, Yaoxin Zhang","doi":"arxiv-2409.07785","DOIUrl":"https://doi.org/arxiv-2409.07785","url":null,"abstract":"With the expansion of the power grid and the increase of the proportion of\u0000new energy sources, the uncertainty and random factors of the power grid\u0000increase, endangering the safe operation of the system. It is particularly\u0000important to find out the critical links of vulnerability in the power grid to\u0000ensure the reliability of the power grid operation. Aiming at the problem that\u0000the identification speed of the traditional critical link of vulnerability\u0000identification methods is slow and difficult to meet the actual operation\u0000requirements of the power grid, the improved graph attention network (IGAT)\u0000based identification method of the critical link is proposed. First, the\u0000evaluation index set is established by combining the complex network theory and\u0000the actual operation data of power grid. Secondly, IGAT is used to dig out the\u0000mapping relationship between various indicators and critical links of\u0000vulnerability during the operation of the power grid, establish the\u0000identification model of critical links of vulnerability, and optimize the\u0000original graph attention network considering the training accuracy and\u0000efficiency. Thirdly, the original data set is obtained through simulation, and\u0000the identification model is trained, verified and tested. Finally, the model is\u0000applied to the improved IEEE 30-node system and the actual power grid, and the\u0000results show that the proposed method is feasible, and the accuracy and speed\u0000are better than that of traditional methods. It has certain engineering\u0000utilization value.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David E. J. van Wijk, Samuel Coogan, Tamas G. Molnar, Manoranjan Majji, Kerianne L. Hobbs
Obtaining a controlled invariant set is crucial for safety-critical control with control barrier functions (CBFs) but is non-trivial for complex nonlinear systems and constraints. Backup control barrier functions allow such sets to be constructed online in a computationally tractable manner by examining the evolution (or flow) of the system under a known backup control law. However, for systems with unmodeled disturbances, this flow cannot be directly computed, making the current methods inadequate for assuring safety in these scenarios. To address this gap, we leverage bounds on the nominal and disturbed flow to compute a forward invariant set online by ensuring safety of an expanding norm ball tube centered around the nominal system evolution. We prove that this set results in robust control constraints which guarantee safety of the disturbed system via our Disturbance-Robust Backup Control Barrier Function (DR-BCBF) solution. Additionally, the efficacy of the proposed framework is demonstrated in simulation, applied to a double integrator problem and a rigid body spacecraft rotation problem with rate constraints.
{"title":"Disturbance-Robust Backup Control Barrier Functions: Safety Under Uncertain Dynamics","authors":"David E. J. van Wijk, Samuel Coogan, Tamas G. Molnar, Manoranjan Majji, Kerianne L. Hobbs","doi":"arxiv-2409.07700","DOIUrl":"https://doi.org/arxiv-2409.07700","url":null,"abstract":"Obtaining a controlled invariant set is crucial for safety-critical control\u0000with control barrier functions (CBFs) but is non-trivial for complex nonlinear\u0000systems and constraints. Backup control barrier functions allow such sets to be\u0000constructed online in a computationally tractable manner by examining the\u0000evolution (or flow) of the system under a known backup control law. However,\u0000for systems with unmodeled disturbances, this flow cannot be directly computed,\u0000making the current methods inadequate for assuring safety in these scenarios.\u0000To address this gap, we leverage bounds on the nominal and disturbed flow to\u0000compute a forward invariant set online by ensuring safety of an expanding norm\u0000ball tube centered around the nominal system evolution. We prove that this set\u0000results in robust control constraints which guarantee safety of the disturbed\u0000system via our Disturbance-Robust Backup Control Barrier Function (DR-BCBF)\u0000solution. Additionally, the efficacy of the proposed framework is demonstrated\u0000in simulation, applied to a double integrator problem and a rigid body\u0000spacecraft rotation problem with rate constraints.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"75 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tianyu Dai, Khaled Aljanaideh, Rong Chen, Rajiv Singh, Alec Stothert, Lennart Ljung
MATLAB(R) releases over the last 3 years have witnessed a continuing growth in the dynamic modeling capabilities offered by the System Identification Toolbox(TM). The emphasis has been on integrating deep learning architectures and training techniques that facilitate the use of deep neural networks as building blocks of nonlinear models. The toolbox offers neural state-space models which can be extended with auto-encoding features that are particularly suited for reduced-order modeling of large systems. The toolbox contains several other enhancements that deepen its integration with the state-of-art machine learning techniques, leverage auto-differentiation features for state estimation, and enable a direct use of raw numeric matrices and timetables for training models.
{"title":"Deep Learning of Dynamic Systems using System Identification Toolbox(TM)","authors":"Tianyu Dai, Khaled Aljanaideh, Rong Chen, Rajiv Singh, Alec Stothert, Lennart Ljung","doi":"arxiv-2409.07642","DOIUrl":"https://doi.org/arxiv-2409.07642","url":null,"abstract":"MATLAB(R) releases over the last 3 years have witnessed a continuing growth\u0000in the dynamic modeling capabilities offered by the System Identification\u0000Toolbox(TM). The emphasis has been on integrating deep learning architectures\u0000and training techniques that facilitate the use of deep neural networks as\u0000building blocks of nonlinear models. The toolbox offers neural state-space\u0000models which can be extended with auto-encoding features that are particularly\u0000suited for reduced-order modeling of large systems. The toolbox contains\u0000several other enhancements that deepen its integration with the state-of-art\u0000machine learning techniques, leverage auto-differentiation features for state\u0000estimation, and enable a direct use of raw numeric matrices and timetables for\u0000training models.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an improved height profile model for drop-on-demand 3D printing with UV curable ink. It is extended from a previously validated model and computes height profile indirectly from volume and area propagation to ensure volume conservation. To accommodate 2D patterns using multiple passes, volume change and area change within region of interest are modeled as a piecewise function of height difference before drop deposition. Model coefficients are experimentally obtained and validated with bootstrapping of experimental samples. Six different drop patterns are experimentally validated. The RMS height profile errors for 2D patterns from the proposed model are consistently smaller than existing models from literature and are on the same level as 1D patterns reported in our previous publication.
{"title":"An Improved Height Difference Based Model of Height Profile for Drop-on-Demand 3D Printing With UV Curable Ink","authors":"Yumeng Wu, George Chiu","doi":"arxiv-2409.07021","DOIUrl":"https://doi.org/arxiv-2409.07021","url":null,"abstract":"This paper proposes an improved height profile model for drop-on-demand 3D\u0000printing with UV curable ink. It is extended from a previously validated model\u0000and computes height profile indirectly from volume and area propagation to\u0000ensure volume conservation. To accommodate 2D patterns using multiple passes,\u0000volume change and area change within region of interest are modeled as a\u0000piecewise function of height difference before drop deposition. Model\u0000coefficients are experimentally obtained and validated with bootstrapping of\u0000experimental samples. Six different drop patterns are experimentally validated.\u0000The RMS height profile errors for 2D patterns from the proposed model are\u0000consistently smaller than existing models from literature and are on the same\u0000level as 1D patterns reported in our previous publication.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses a distributed controller design problem for discrete-time systems using linear matrix inequalities (LMIs). Sparsity constraints on control gains of distributed controllers result in conservatism via the convexification of the existing methods such as the extended LMI method. In order to mitigate the conservatism, we introduce a novel LMI formulation for this problem, utilizing the clique-wise decomposition method from our previous work on continuous-time systems. By reformulating the sparsity constraint on the gain matrix within cliques, this method achieves a broader solution set. Also, the analytical superiority of our method is confirmed through numerical examples.
{"title":"Distributed Controller Design for Discrete-Time Systems Via the Integration of Extended LMI and Clique-Wise Decomposition","authors":"Sotaro Fushimi, Yuto Watanabe, Kazunori Sakurama","doi":"arxiv-2409.07666","DOIUrl":"https://doi.org/arxiv-2409.07666","url":null,"abstract":"This study addresses a distributed controller design problem for\u0000discrete-time systems using linear matrix inequalities (LMIs). Sparsity\u0000constraints on control gains of distributed controllers result in conservatism\u0000via the convexification of the existing methods such as the extended LMI\u0000method. In order to mitigate the conservatism, we introduce a novel LMI\u0000formulation for this problem, utilizing the clique-wise decomposition method\u0000from our previous work on continuous-time systems. By reformulating the\u0000sparsity constraint on the gain matrix within cliques, this method achieves a\u0000broader solution set. Also, the analytical superiority of our method is\u0000confirmed through numerical examples.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erik Bauer, Marc Blöchlinger, Pascal Strauch, Arman Raayatsanati, Curdin Cavelti, Robert K. Katzschmann
Aerial manipulation combines the versatility and speed of flying platforms with the functional capabilities of mobile manipulation, which presents significant challenges due to the need for precise localization and control. Traditionally, researchers have relied on offboard perception systems, which are limited to expensive and impractical specially equipped indoor environments. In this work, we introduce a novel platform for autonomous aerial manipulation that exclusively utilizes onboard perception systems. Our platform can perform aerial manipulation in various indoor and outdoor environments without depending on external perception systems. Our experimental results demonstrate the platform's ability to autonomously grasp various objects in diverse settings. This advancement significantly improves the scalability and practicality of aerial manipulation applications by eliminating the need for costly tracking solutions. To accelerate future research, we open source our ROS 2 software stack and custom hardware design, making our contributions accessible to the broader research community.
{"title":"An Open-Source Soft Robotic Platform for Autonomous Aerial Manipulation in the Wild","authors":"Erik Bauer, Marc Blöchlinger, Pascal Strauch, Arman Raayatsanati, Curdin Cavelti, Robert K. Katzschmann","doi":"arxiv-2409.07662","DOIUrl":"https://doi.org/arxiv-2409.07662","url":null,"abstract":"Aerial manipulation combines the versatility and speed of flying platforms\u0000with the functional capabilities of mobile manipulation, which presents\u0000significant challenges due to the need for precise localization and control.\u0000Traditionally, researchers have relied on offboard perception systems, which\u0000are limited to expensive and impractical specially equipped indoor\u0000environments. In this work, we introduce a novel platform for autonomous aerial\u0000manipulation that exclusively utilizes onboard perception systems. Our platform\u0000can perform aerial manipulation in various indoor and outdoor environments\u0000without depending on external perception systems. Our experimental results\u0000demonstrate the platform's ability to autonomously grasp various objects in\u0000diverse settings. This advancement significantly improves the scalability and\u0000practicality of aerial manipulation applications by eliminating the need for\u0000costly tracking solutions. To accelerate future research, we open source our\u0000ROS 2 software stack and custom hardware design, making our contributions\u0000accessible to the broader research community.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"298 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to improve energy utilization and reduce carbon emissions, this paper presents a comprehensive energy system economic operation strategy of Incineration power plant Power-to-gas (P2G) with waste heat recovery. First, consider the coordinated operation of Incineration power plant - P2G, introduce the refined Power-to-gas two-stage operation process, add Hydrogen fuel cells on the basis of traditional Power-to-gas to reduce the energy ladder loss, and recycle the Methanation reaction heat; Secondly, in order to improve the energy utilization efficiency of Incineration, it is considered to install a waste heat recovery device containing a water source heat pump to recover the waste heat of flue gas and consume some electric energy, sourced from wind power, and add a CO2 separation device to combine the recovered CO2 with P2G to synthesize CH4 to achieve carbon recycling. Finally, within the framework of a tiered carbon trading mechanism an IES optimization model for electricity-heat with the goal of minimizing the system operating cost is constructed, and the GUROBI modeling optimization engine is used to solve this model. The results verify the effectiveness of the model.
{"title":"Low carbon optimal scheduling of integrated energy system considering waste heat utilization under the coordinated operation of incineration power plant and P2G","authors":"Limeng Wang, Shuo Wang, Na Wang, Yuze Ma, Yang Li","doi":"arxiv-2409.07254","DOIUrl":"https://doi.org/arxiv-2409.07254","url":null,"abstract":"In order to improve energy utilization and reduce carbon emissions, this\u0000paper presents a comprehensive energy system economic operation strategy of\u0000Incineration power plant Power-to-gas (P2G) with waste heat recovery. First,\u0000consider the coordinated operation of Incineration power plant - P2G, introduce\u0000the refined Power-to-gas two-stage operation process, add Hydrogen fuel cells\u0000on the basis of traditional Power-to-gas to reduce the energy ladder loss, and\u0000recycle the Methanation reaction heat; Secondly, in order to improve the energy\u0000utilization efficiency of Incineration, it is considered to install a waste\u0000heat recovery device containing a water source heat pump to recover the waste\u0000heat of flue gas and consume some electric energy, sourced from wind power, and\u0000add a CO2 separation device to combine the recovered CO2 with P2G to synthesize\u0000CH4 to achieve carbon recycling. Finally, within the framework of a tiered\u0000carbon trading mechanism an IES optimization model for electricity-heat with\u0000the goal of minimizing the system operating cost is constructed, and the GUROBI\u0000modeling optimization engine is used to solve this model. The results verify\u0000the effectiveness of the model.","PeriodicalId":501175,"journal":{"name":"arXiv - EE - Systems and Control","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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