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A Multi-Individual distributed Modeling and Optimization method for Integrated Energy Systems With Complex Composition

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IEEE ACCESS 2020年 8卷 136198-136205页

作者： Lei, Yunkai Tang, Quan Li, Ting Wang, Yunling Xu, Weiting Zheng, Jiehui Wang, L. X. State Grid Sichuan Econ Res Inst Chengdu 610000 Peoples R China South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China

This paper proposes a multi-individual distributed (MID) method for operation optimization of heterogeneous integrated energy systems. The proposed method decouples high-dimensional centralized problem of complex systems into distributed subproblems corresponding with independent small individuals. Each subproblem can be solved by appropriate algorithm according to its physical properties. In the MID method, the individuals carry out their own optimal operation strategies to maximize self-interests while information privacy and independent operation of system participants are protected. Furthermore, optimal energy market clearing prices, which guarantee the maximization of social welfare, are obtained in this method. When market transaction prices deviate from the optimal prices, there will be a marked decline in the benefit of the whole system.

关键词： Cooling Thermal energy Couplings Optimization methods Power systems Natural gas Multi-individual distributed method modeling and optimization integrated energy systems

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distributed Stochastic MPC Traffic Signal Control for Urban Networks

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第8期24卷 8079-8096页

作者： Pham, Viet Hoang Ahn, Hyo-Sung Gwangju Inst Sci & Technol Sch Mech Engn Gwangju 61005 South Korea

In this paper, we design a stochastic model predictive control (MPC)-based traffic signal control method for urban networks when the uncertainties of the traffic model parameters (including the exogenous traffic flows and the turning ratios of downstream traffic flows) are taken into account. Considering that the traffic model parameters are random variables with known expectations and variances, the traffic signal control and coordination problem is formulated as a quadratic program with linear and second-order cone constraints. In order to reduce computational complexity, we suggest a way to decompose the optimization problem corresponding to the whole network into multiple subproblems. By applying an Alternating Direction method of Multipliers (ADMM) scheme, the optimal stochastic traffic signal splits are found in a distributed manner. The effectiveness of the designed control method is validated via some simulations using VISSIM and MATLAB.

关键词： Roads Stochastic processes Junctions Mathematical models Optimization Turning Uncertainty Traffic signal split optimization stochastic model predictive control distributed method

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distributed Control for an Urban Traffic Network

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第12期23卷 22937-22953页

作者： Viet Hoang Pham Sakurama, Kazunori Mou, Shaoshuai Ahn, Hyo-Sung Gwangju Inst Sci & Technol GIST Sch Mech Engn Gwangju 61005 South Korea Kyoto Univ Grad Sch Informat Sakyo Ku Kyoto 6068501 Japan Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA

In this paper, we develop a distributed control method for an urban traffic network in order to improve traffic conditions and guarantee a smooth operation for all roads and intersections. An optimal coordination among traffic flows is determined by a model predictive control idea. The control objective is formulated as a constrained optimization problem in which the cost function to be minimized is a combination of some traffic network-related performance indexes and the constraints are derived from capacities of roads and intersections. The green time assigned to each road link is computed from its optimal downstream traffic flow. In the proposed algorithms, every road link uses only its local information to determine its control decision which corresponds to a global optimal solution. The algorithms are developed by using a gradient projection-based method and properties of the minimal polynomial of a matrix pair. The effectiveness of the proposed algorithms is validated via numerical simulations with MATLAB and VISSIM.

关键词： Roads Mathematical models Sensors Predictive control Decentralized control Vehicle dynamics Urban areas Urban traffic control model predictive control distributed method

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A comparative study of the time of concentration methods for designing urban drainage infrastructure

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AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY 2022年第10期71卷 1197-1218页

作者： Mehta, Osheen Kansal, Mitthan Lal Bisht, Deepak Singh Indian Inst Technol Water Resources Dev & Management Roorkee Uttarakhand India Western Himalayan Reg Ctr Natl Inst Hydrol Jammu India

The time of concentration (ToC) is an important parameter in rainfall-runoff simulation for designing and evaluating an urban drainage system (UDS). There are several lumped and distributed methods available in the literature for estimating the ToC. However, these methods lead to significantly varied values. Therefore, it is imperative to choose an appropriate and best-suited method for estimating the ToC. This study analyses eight lumped approach-based and two distributed approach-based methods for estimating the ToC in an urban area of Gurugram, a satellite city in the National Capital Region (NCR) of Delhi in India. Considering the ToC obtained by the Natural Resource Conservation Service (NRCS) method as the 'true' value, the Carter method among lumped methods and the SWDM method between the distributed methods results in ToC values in agreement with the NRCS method. Furthermore, to study the impact of the underestimation or overestimation of ToC on drainage, the system is evaluated in terms of variation in flood volume, duration, peak discharge, and the time to peak for different ToC values. The simulations were carried out by setting the model in SWMM, and it was found that flood volume increases by 4.25 times and the duration increases by 7.25 times if the ToC is increased from 0.1 to 6.14 h. The results infer that ToC estimation methods significantly impact the design and performance of an urban drainage infrastructure.

关键词： distributed method lumped method SWMM time of concentration urban catchment

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DRL-Based Improved UAV Swarm Control for Simultaneous Coverage and Tracking with Prior Experience Utilization

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DRONES 2024年第12期8卷 784-784页

作者： Chen, Yiting Chen, Runfeng Huang, Yuchong Xiong, Zehao Li, Jie Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China

Area coverage and target tracking are important applications of UAV swarms. However, attempting to perform both tasks simultaneously can be a challenge, particularly under resource constraints. In such scenarios, UAV swarms must collaborate to cover extensive areas while simultaneously tracking multiple targets. This paper proposes a deep reinforcement learning (DRL)-based, scalable UAV swarm control method for a simultaneous coverage and tracking (SCT) task, called the SCT-DRL algorithm. SCT-DRL simplifies the interaction between UAV swarms into a series of pairwise interactions and aggregates the information of perceived targets in advance, based on which forms the control framework with a variable number of neighboring UAVs and targets. Another highlight of SCT-DRL is using the trajectories of the traditional one-step optimization method to initialize the value network, which encourages the UAVs to select the actions leading to the state with less rest time to task completion to avoid extensive random exploration at the beginning of training. SCT-DRL can be seen as a special improvement of the traditional one-step optimization method, shaped by the samples derived from the latter, and gradually overcomes the inherent myopic issue with the far-sighted value estimation through RL training. Finally, the effectiveness of the proposed method is demonstrated through numerical experiments.

关键词： deep reinforcement learning simultaneous coverage and tracking multi-UAV control distributed method

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distributed multi-UAV cooperation for path planning by an NTVPSO-ADE algorithm 41

Distributed multi-UAV cooperation for path planning by an NT...

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第41届中国控制会议

作者： Liangliang Lu Jiyang Dai Jin Ying Nanchang Hangkong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Multi-UAV cooperative trajectory planning faces issues such as model establishment difficulty and a considerable amount of *** work proposes a distributed hybrid particle swarm optimization(PSO) and differential evolution(DE) technique.A nonlinear time-varying PSO(NTVPSO) is developed to update the velocity and position of the PSO,aiming at the difficult balance of exploration and exploitation search for *** adaptive DE(ADE) is proposed in order to improve the information sharing between particles and the algorithm's convergence *** order to realize the collaborative planning of multiple UAVs,a distributed method is used to solve the single UAV trajectory planning task by using *** trace is fed back to the PSO velocity update formula to guide the direction of particle *** simulation results show that the algorithm is highly competitive in terms of path optimality and can be used as a viable alternative to solve multi-UAV cooperative trajectory planning problems.

关键词： Multu-UAV Particle Swarm Optimization Differential Evolution distributed method

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A distributed Regularized Jacobi-Type ADMM-method for Generalized Nash Equilibrium Problems in Hilbert Spaces

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NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION 2018年第12期39卷 1316-1349页

作者： Boergens, Eike Kanzow, Christian Univ Wurzburg Inst Math Campus Hubland Nord Wurzburg Germany

We consider the generalized Nash equilibrium problem in a Hilbert space setting. The joint constraints are eliminated by an augmented Lagrangian-type approach, and we present a fully distributed version by using ideas from alternating direction methods of multipliers (ADMM methods). Convergence follows, under a cocoercivity condition, from the fact that this method can be interpreted as a suitable splitting approach in our Hilbert space endowed with a modified scalar product. This observation also leads to a second algorithmic approach, which yields convergence under a Lipschitz assumption and monotonicity. Numerical results are presented for some examples arising in both finite- and infinite-dimensional Hilbert spaces.

关键词： ADMM method convergence distributed method generalized Nash equilibrium problem Hilbert space

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Decentralized UAV Swarm Scheduling with Constrained Task Exploration Balance

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DRONES 2023年第4期7卷 267-267页

作者： Chen, Runfeng Li, Jie Peng, Ting Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China

Scheduling is one of the key technologies used in unmanned aerial vehicle (UAV) swarms. Scheduling determines whether a task can be completed and when the task is complete. The distributed method is a fast way to realize swarm scheduling. It has no central node and UAVs can freely join or leave it, thus making it more robust and flexible. However, the two most representative methods, the Consensus-Based Bundle Algorithm (CBBA) and the Performance Impact (PI) algorithm, pursue the minimum cost impact of tasks, which have optimization limitations and are easily cause task conflicts. In this paper, a new concept called "task consideration" is proposed to quantify the impact of tasks on scheduling and the regression of the task itself, balancing the exploration of the UAV for the minimum-impact task and the regression of neighboring tasks to improve the optimization and convergence of scheduling. In addition, the conflict resolution rules are modified to fit the proposed method, and the exploration of tasks is increased by a new removal method to further improve the optimization. Finally, through extensive Monte Carlo experiments, compared with CBBA and PI, the proposed method is shown to perform better in terms of task allocation and total travel time, and with the increase in the number of average UAV tasks, the number of iterations is less and the convergence is faster.

关键词： UAV planning swarm scheduling distributed method market-based algorithm task consideration

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Penalty methods for distributed Optimization with Inequality and Equality Constraints 40

Penalty Methods for Distributed Optimization with Inequality...

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40th Chinese Control Conference (CCC)

作者： Xia, Zicong Liu, Yang Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Zhejiang Peoples R China

ISBN: (纸本)9789881563804

This paper focuses on the penalty method, which has the potential to turn constrained problems into unconstrained ones, for distributed optimization with inequality and equality constraints. A selection principle to choose penalty gains is proposed based on value-distance ratio. Furthermore, a distributed method is developed to solve the obtained problems while its convergence is rigorously proved. Finally, an example in a numerical way demonstrates the validity of this paper.

关键词： distributed optimization Penalty methods distributed method Non-smooth analysis

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Power Restoration method of Distribution Network with ESS and DG

Power Restoration Method of Distribution Network with ESS an...

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IEEE IAS Conference on Industrial and Commercial Power System Asia (IEEE I and CPS Asia)

作者： Sun, Shoujing Cong, Wei Qiu, Jifu Chen, Ming Wei, Zhen Zhang, Zijin Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China Shandong Elect Power Co State Grid Qingdao Power Supply Co Qingdao Peoples R China

ISBN: (纸本)9781665434980

A restoration method of distributed power supply in power grid with energy storage system is proposed. First, it introduces the principle of distributed access and operation constraints of ESS and DG in the distribution network. Utilizing the parallel coordination and information interaction between independent and peer intelligent terminals in the distribution network, the power restoration method is adopted, which mainly includes two parts: distributed network topology search and expression and calculation of constraints on power restoration. It not only exerts the advantages of ESS in power restoration, but also avoids the problems of large amount of information collection and large amount of calculation in the centralized power restoration method in the distribution network. At the same time, consider the ESS power control adjustment strategy to achieve reasonable power support for the distribution network to expand the scope of power restoration in the power outage area. The simulation results of the IEEE33-bus system example verify the flexibility and effectiveness of the proposed method.

关键词： distribution network power restoration energy storage system (ESS) distributed generator (DG) distributed method

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