Manufacturing plants are increasingly complex and integrated, requiring control systems able to identify the interactions between the various operating units. Production planning and control design of a process are to...Manufacturing plants are increasingly complex and integrated, requiring control systems able to identify the interactions between the various operating units. Production planning and control design of a process are tools that, if combined, bring many economic benefits to the processes since they aim to identify and maintain optimal decision operations to a system. This work uses such integration between production planning and plantwide control to propose a control system for the Williams-Otto plant from the definition of the operating optimal point for coordinated decentralized optimization, in which the original optimization problem decomposition into smaller coordinated problems ensure that the found local optimum also meets the requirements of the global system. The results for decentralized optimization are satisfactory and very similar to the global optimum problem and to the control system response proposed based on the optimal obtained. It is effective taking smooth actions, working with （economic） optimal set points （economically） of operation. The unification of production planning techniques and plantwide control techniques is an effective tool for the control system design for entire plants.展开更多
Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],th...Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.展开更多
Current urban transport and energy systems are gradually being integrated and developed towards a state of multi-area interconnection.This paper proposes a decentralized optimization approach of multi-area power-trans...Current urban transport and energy systems are gradually being integrated and developed towards a state of multi-area interconnection.This paper proposes a decentralized optimization approach of multi-area power-transport coupled systems(PTCSs)based on this change.To begin with,models concerning optimal power flow and mixed equilibrium flow are defined to describe flow patterns,respectively.Considering the traffic assignment model is non-linear and challenging to solve,this paper converts it into an equivalent variational inequality(Ⅵ).With this foundation,a decentralized optimization model is proposed,and decoupling strategies are investigated.To solve the problem effectively,an improved algorithm applicable to the decentralized optimization of PTCSs,supported by the Ⅳ tool,is proposed.In addition,a rigorous convergence analysis of the proposed algorithm was conducted.Simulations indicate the proposed algorithm solves the problem with good results and can guarantee convergence within a reasonable time frame.展开更多
We study decentralized smooth optimization problems over compact submanifolds.Recasting it as a composite optimization problem,we propose a decentralized Douglas-Rachford splitting algorithm(DDRS).When the proximal op...We study decentralized smooth optimization problems over compact submanifolds.Recasting it as a composite optimization problem,we propose a decentralized Douglas-Rachford splitting algorithm(DDRS).When the proximal operator of the local loss func-tion does not have a closed-form solution,an inexact version of DDRS(iDDRS),is also presented.Both algorithms rely on careful integration of the nonconvex Douglas-Rachford splitting algorithm with gradient tracking and manifold optimization.We show that our DDRS and iDDRS achieve the convergence rate of O(1/k).The main challenge in the proof is how to handle the nonconvexity of the manifold constraint.To address this issue,we utilize the concept of proximal smoothness for compact submanifolds.This ensures that the projection onto the submanifold exhibits convexity-like properties,which allows us to control the consensus error across agents.Numerical experiments on the principal component analysis are conducted to demonstrate the effectiveness of our decentralized DRS compared with the state-of-the-art ones.展开更多
In response to the critical need to balance fiscal expenditure governance with sustainable development,this study identifies the optimal level of fiscal expenditure decentralization that enhances sustainable outcomes....In response to the critical need to balance fiscal expenditure governance with sustainable development,this study identifies the optimal level of fiscal expenditure decentralization that enhances sustainable outcomes.The study aims to determine the optimal expenditure decentralization that maximizes sustainable development outcomes across these dimensions.Theoretically,we analyze the impact mechanism of expenditure decentralization on sustainable development and hypothesize that there is an inverted U-shaped relationship between them,along with the possibility of finding an optimal level of expenditure decentralization.We test this hypothesis by measuring sustainable development in the context of a panel data set for 52 countries covering the period 1991–2016 using the National Sustainable Development Index(NSDI).We find strong support for the inverted U-shaped relationship between expenditure decentralization and sustainable development in both the short and long run.Sustainable development is the coordination of economic,social,and environmental development to balance intergenerational welfare and maximize the total welfare of all generations.Excessive and insufficient expenditure decentralization can potentially negatively affect the efficiency of public goods provision and residents’utility,thereby adversely impacting total welfare and sustainable development.The results are robust to alternative specifications and to IV estimation to correct for potential endogeneity.The expenditure decentralization level most conducive to sustainable development lies between 30.9%and 34.5%.The optimal decentralization range was determined using the Lind–Mehlum method,supporting the main findings of this study.This research thus contributes to the literature by quantifying the complex relationship between fiscal decentralization policies and sustainable development,providing a clear,actionable pathway for policymakers seeking sustainable outcomes.展开更多
In this note, we extend the algorithms Extra [13] and subgradient-push [I0] to a new algorithm ExtraPush for consensus optimization with convex differentiable objective functions over a directed network. When the stat...In this note, we extend the algorithms Extra [13] and subgradient-push [I0] to a new algorithm ExtraPush for consensus optimization with convex differentiable objective functions over a directed network. When the stationary distribution of the network can be computed in advance, we propose a simplified algorithm called Normalized ExtraPush. Just like Extra, both ExtraPush and Normalized ExtraPush can iterate with a fixed step size. But unlike Extra, they can take a column-stochastic mixing matrix, which is not necessarily doubly stochastic. Therefore, they remove the undirected-network restriction of Extra. Subgradient-push, while also works for directed networks, is slower on the same type of problem because it must use a sequence of diminishing step sizes. We present preliminary analysis for ExtraPush under a bounded sequence assumption. For Normalized ExtraPush, we show that it naturally produces a bounded, linearly convergent sequence provided that the objective function is strongly convex. In our numerical experiments, ExtraPush and Normalized ExtraPush performed similarly well. They are significantly faster than subgradient-push, even when we hand-optimize the step sizes for the latter.展开更多
Cooperation in energy systems is no longer limited to the distribution of electricity,and more attention is paid to the trading of green certificates(GCs).This paper proposed a cooperative method for photovoltaic(PV)a...Cooperation in energy systems is no longer limited to the distribution of electricity,and more attention is paid to the trading of green certificates(GCs).This paper proposed a cooperative method for photovoltaic(PV)and electric-to-hydrogen(EH)trading,including GC trading under risk management.First,a novel PV and EH model is established and the cooperation mechanism is analyzed.Meanwhile,PV and EH models were risk-controlled using the conditional value at risk to reduce the impact of the uncertainty of PV electricity and EH loads.Then,the PV-EH cooperative model was established based on cooperative game theory;this was then divided into two subproblems of“cooperative benefit maximization”and“transaction payment negotiation,”and the above two subproblems were solved distributively by alternating direction multiplier method(ADMM).Only energy transactions and price negotiations were conducted between the PV and EH,which can protect the privacy and confidentiality of each entity.Finally,the effectiveness of the cooperation model was verified using a practical engineering case.The simulation results show that the cooperation of the PV-EH can significantly improve the operational efficiency of each entity and the overall efficiency of the cooperation and realize the efficient redistribution of electricity and GC.展开更多
The increasing focus on carbon neutrality has led to heightened interest in multiple microgrids(MGs)due to their potential to significantly reduce emissions by the integrated electricity-heat-carbon sharing among them...The increasing focus on carbon neutrality has led to heightened interest in multiple microgrids(MGs)due to their potential to significantly reduce emissions by the integrated electricity-heat-carbon sharing among them.In this paper,a decentralized peer-to-peer(P2P)framework for integrated electricityheat-carbon sharing is proposed to optimize the trading process of multi-energy and carbon among multiple MGs.The proposed framework considers certified emission reductions(CERs)of photovoltaic(PV)systems in each MG,and carbon allocation and trading among multiple MGs.The P2P trading behaviors among multiple MGs are modelled as a non-cooperative game.A decentralized optimization method is then developed using a price-based incentive scheme to solve the non-cooperative game and optimize the transactions of the electricityheat-carbon jointly.The optimization problem is solved using sub-gradient in a decentralized manner.And the Nash equilibrium of the non-cooperative game is proven to exist uniquely,ensuring the convergence of the model.Furthermore,the proposed decentralized optimization method safeguards the private information of the MGs.Numerical results show that the total operational cost of the MGs and the carbon emissions can be reduced significantly.展开更多
In order to obtain an accurate state estimation of the operation in the combined heat and power system,it is necessary to carry out state estimation.Due to the limited information sharing among various energy systems,...In order to obtain an accurate state estimation of the operation in the combined heat and power system,it is necessary to carry out state estimation.Due to the limited information sharing among various energy systems,it is practical to perform state estimation in a decentralized manner.However,the possible communication packet loss is seldomly considered among various energy systems.This paper bridges this gap by proposing a relaxed alternating direction method of multiplier algorithm.It can also improve the computation efficiency compared with the conventional alternating direction of the multiplier algorithm.Case studies of two test systems are carried out to show the validity and superiority of the proposed algorithm.展开更多
In this paper,we focus on the decentralized online learning problem where online data streams are separately collected and collaboratively processed by a network of decentralized agents.Comparing to centralized batch ...In this paper,we focus on the decentralized online learning problem where online data streams are separately collected and collaboratively processed by a network of decentralized agents.Comparing to centralized batch learning,such a framework is faithful to the decentralized and online natures of the data streams.We propose an online decentralized alternating direction method of multipliers that efficiently solves the online learning problem over a decentralized network.We prove its O(√T)regret bound when the instantaneous local cost functions are convex,and its O(log T)regret bound when the instantaneous local cost functions are strongly convex,where T is the number of iterations.Both regret bounds are in the same orders as those of centralized online learning.Numerical experiments on decentralized online least squares and classification problems demonstrate effectiveness of the proposed algorithm.展开更多
This paper proposes a fast and decentralized solution methodology for the robust operation of multi-area integrated electricity-gas systems(M-IEGSs).A deterministic reformulation is obtained for the two-stage robust m...This paper proposes a fast and decentralized solution methodology for the robust operation of multi-area integrated electricity-gas systems(M-IEGSs).A deterministic reformulation is obtained for the two-stage robust model by applying the linear decision rule based electrical reserve utilization scheme as well as regulating the distributed gas storages.Two linear approximations are developed for the nonconvex Weymouth equation in the gas network to determine the gas flow directions.The penalty convex-concave procedure(P-CCP)is then adopted to refine a feasible local optimum for the nonconvex model with an acceleration strategy.The decentralized decision-making is enabled by the alternating direction multipliers method(ADMM).The convergence as well as computation performance of the overall solution procedure can be guaranteed as only convex optimizations are solved.Simulation results validate the effectiveness of the proposed methods as well as the benefits of the proposed convex programing based solution procedure.展开更多
Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different...Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.展开更多
文摘Manufacturing plants are increasingly complex and integrated, requiring control systems able to identify the interactions between the various operating units. Production planning and control design of a process are tools that, if combined, bring many economic benefits to the processes since they aim to identify and maintain optimal decision operations to a system. This work uses such integration between production planning and plantwide control to propose a control system for the Williams-Otto plant from the definition of the operating optimal point for coordinated decentralized optimization, in which the original optimization problem decomposition into smaller coordinated problems ensure that the found local optimum also meets the requirements of the global system. The results for decentralized optimization are satisfactory and very similar to the global optimum problem and to the control system response proposed based on the optimal obtained. It is effective taking smooth actions, working with （economic） optimal set points （economically） of operation. The unification of production planning techniques and plantwide control techniques is an effective tool for the control system design for entire plants.
基金supported by the National Key Research and Development Program of China(2022YFA1004701)the National Natural Science Foundation of China(72271187,62373283)Shanghai Municipal Science and Technology Major(2021SHZDZX0100).
文摘Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.
基金supported by National Natural Science Foundation of China under grant 52307087.
文摘Current urban transport and energy systems are gradually being integrated and developed towards a state of multi-area interconnection.This paper proposes a decentralized optimization approach of multi-area power-transport coupled systems(PTCSs)based on this change.To begin with,models concerning optimal power flow and mixed equilibrium flow are defined to describe flow patterns,respectively.Considering the traffic assignment model is non-linear and challenging to solve,this paper converts it into an equivalent variational inequality(Ⅵ).With this foundation,a decentralized optimization model is proposed,and decoupling strategies are investigated.To solve the problem effectively,an improved algorithm applicable to the decentralized optimization of PTCSs,supported by the Ⅳ tool,is proposed.In addition,a rigorous convergence analysis of the proposed algorithm was conducted.Simulations indicate the proposed algorithm solves the problem with good results and can guarantee convergence within a reasonable time frame.
文摘We study decentralized smooth optimization problems over compact submanifolds.Recasting it as a composite optimization problem,we propose a decentralized Douglas-Rachford splitting algorithm(DDRS).When the proximal operator of the local loss func-tion does not have a closed-form solution,an inexact version of DDRS(iDDRS),is also presented.Both algorithms rely on careful integration of the nonconvex Douglas-Rachford splitting algorithm with gradient tracking and manifold optimization.We show that our DDRS and iDDRS achieve the convergence rate of O(1/k).The main challenge in the proof is how to handle the nonconvexity of the manifold constraint.To address this issue,we utilize the concept of proximal smoothness for compact submanifolds.This ensures that the projection onto the submanifold exhibits convexity-like properties,which allows us to control the consensus error across agents.Numerical experiments on the principal component analysis are conducted to demonstrate the effectiveness of our decentralized DRS compared with the state-of-the-art ones.
基金supported by Zhejiang Province Philosophy and Social Science Planning Fund(24NDQN090YB)Hangzhou City Philosophy and Social Science Planning Fund(Z23JC041)the Major program project of the National Social Science Fund of China(No:19ZDA055).
文摘In response to the critical need to balance fiscal expenditure governance with sustainable development,this study identifies the optimal level of fiscal expenditure decentralization that enhances sustainable outcomes.The study aims to determine the optimal expenditure decentralization that maximizes sustainable development outcomes across these dimensions.Theoretically,we analyze the impact mechanism of expenditure decentralization on sustainable development and hypothesize that there is an inverted U-shaped relationship between them,along with the possibility of finding an optimal level of expenditure decentralization.We test this hypothesis by measuring sustainable development in the context of a panel data set for 52 countries covering the period 1991–2016 using the National Sustainable Development Index(NSDI).We find strong support for the inverted U-shaped relationship between expenditure decentralization and sustainable development in both the short and long run.Sustainable development is the coordination of economic,social,and environmental development to balance intergenerational welfare and maximize the total welfare of all generations.Excessive and insufficient expenditure decentralization can potentially negatively affect the efficiency of public goods provision and residents’utility,thereby adversely impacting total welfare and sustainable development.The results are robust to alternative specifications and to IV estimation to correct for potential endogeneity.The expenditure decentralization level most conducive to sustainable development lies between 30.9%and 34.5%.The optimal decentralization range was determined using the Lind–Mehlum method,supporting the main findings of this study.This research thus contributes to the literature by quantifying the complex relationship between fiscal decentralization policies and sustainable development,providing a clear,actionable pathway for policymakers seeking sustainable outcomes.
文摘In this note, we extend the algorithms Extra [13] and subgradient-push [I0] to a new algorithm ExtraPush for consensus optimization with convex differentiable objective functions over a directed network. When the stationary distribution of the network can be computed in advance, we propose a simplified algorithm called Normalized ExtraPush. Just like Extra, both ExtraPush and Normalized ExtraPush can iterate with a fixed step size. But unlike Extra, they can take a column-stochastic mixing matrix, which is not necessarily doubly stochastic. Therefore, they remove the undirected-network restriction of Extra. Subgradient-push, while also works for directed networks, is slower on the same type of problem because it must use a sequence of diminishing step sizes. We present preliminary analysis for ExtraPush under a bounded sequence assumption. For Normalized ExtraPush, we show that it naturally produces a bounded, linearly convergent sequence provided that the objective function is strongly convex. In our numerical experiments, ExtraPush and Normalized ExtraPush performed similarly well. They are significantly faster than subgradient-push, even when we hand-optimize the step sizes for the latter.
基金supported in part by the National Natural Science Foundation of China(No.5197707).
文摘Cooperation in energy systems is no longer limited to the distribution of electricity,and more attention is paid to the trading of green certificates(GCs).This paper proposed a cooperative method for photovoltaic(PV)and electric-to-hydrogen(EH)trading,including GC trading under risk management.First,a novel PV and EH model is established and the cooperation mechanism is analyzed.Meanwhile,PV and EH models were risk-controlled using the conditional value at risk to reduce the impact of the uncertainty of PV electricity and EH loads.Then,the PV-EH cooperative model was established based on cooperative game theory;this was then divided into two subproblems of“cooperative benefit maximization”and“transaction payment negotiation,”and the above two subproblems were solved distributively by alternating direction multiplier method(ADMM).Only energy transactions and price negotiations were conducted between the PV and EH,which can protect the privacy and confidentiality of each entity.Finally,the effectiveness of the cooperation model was verified using a practical engineering case.The simulation results show that the cooperation of the PV-EH can significantly improve the operational efficiency of each entity and the overall efficiency of the cooperation and realize the efficient redistribution of electricity and GC.
基金supported in part by the National Key R&D Program of China(No.2023YFB2407300)the National Natural Science Foundation of China(No.U23B6006)。
文摘The increasing focus on carbon neutrality has led to heightened interest in multiple microgrids(MGs)due to their potential to significantly reduce emissions by the integrated electricity-heat-carbon sharing among them.In this paper,a decentralized peer-to-peer(P2P)framework for integrated electricityheat-carbon sharing is proposed to optimize the trading process of multi-energy and carbon among multiple MGs.The proposed framework considers certified emission reductions(CERs)of photovoltaic(PV)systems in each MG,and carbon allocation and trading among multiple MGs.The P2P trading behaviors among multiple MGs are modelled as a non-cooperative game.A decentralized optimization method is then developed using a price-based incentive scheme to solve the non-cooperative game and optimize the transactions of the electricityheat-carbon jointly.The optimization problem is solved using sub-gradient in a decentralized manner.And the Nash equilibrium of the non-cooperative game is proven to exist uniquely,ensuring the convergence of the model.Furthermore,the proposed decentralized optimization method safeguards the private information of the MGs.Numerical results show that the total operational cost of the MGs and the carbon emissions can be reduced significantly.
基金supported in part by the Key-Area Research and Development Program of Guangdong Province(No.2020B010166004)Guangdong Basic and Applied Basic Research Foundation(No.2019A1515011408)+2 种基金the Science and Technology Program of Guangzhou(No.201904010215)the Talent Recruitment Project of Guangdong(No.2017GC010467)the Fundamental Research Funds for the Central Universities
文摘In order to obtain an accurate state estimation of the operation in the combined heat and power system,it is necessary to carry out state estimation.Due to the limited information sharing among various energy systems,it is practical to perform state estimation in a decentralized manner.However,the possible communication packet loss is seldomly considered among various energy systems.This paper bridges this gap by proposing a relaxed alternating direction method of multiplier algorithm.It can also improve the computation efficiency compared with the conventional alternating direction of the multiplier algorithm.Case studies of two test systems are carried out to show the validity and superiority of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(No.61573331).
文摘In this paper,we focus on the decentralized online learning problem where online data streams are separately collected and collaboratively processed by a network of decentralized agents.Comparing to centralized batch learning,such a framework is faithful to the decentralized and online natures of the data streams.We propose an online decentralized alternating direction method of multipliers that efficiently solves the online learning problem over a decentralized network.We prove its O(√T)regret bound when the instantaneous local cost functions are convex,and its O(log T)regret bound when the instantaneous local cost functions are strongly convex,where T is the number of iterations.Both regret bounds are in the same orders as those of centralized online learning.Numerical experiments on decentralized online least squares and classification problems demonstrate effectiveness of the proposed algorithm.
基金supported by Science and Technology Project of State Grid Corporation of China(No.SGJX0000KXJS1900321)。
文摘This paper proposes a fast and decentralized solution methodology for the robust operation of multi-area integrated electricity-gas systems(M-IEGSs).A deterministic reformulation is obtained for the two-stage robust model by applying the linear decision rule based electrical reserve utilization scheme as well as regulating the distributed gas storages.Two linear approximations are developed for the nonconvex Weymouth equation in the gas network to determine the gas flow directions.The penalty convex-concave procedure(P-CCP)is then adopted to refine a feasible local optimum for the nonconvex model with an acceleration strategy.The decentralized decision-making is enabled by the alternating direction multipliers method(ADMM).The convergence as well as computation performance of the overall solution procedure can be guaranteed as only convex optimizations are solved.Simulation results validate the effectiveness of the proposed methods as well as the benefits of the proposed convex programing based solution procedure.
基金supported by the Key-Area Research and Development Program of Guangdong Province under Grant 2020B010166004the National Natural Science Foundation of China under Grant 52177086+2 种基金the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515011408the Science and Technology Program of Guangzhou under Grant 201904010215the Talent Recruitment Project of Guangdong under Grant 2017GC010467.
文摘Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.
