Hydrogen fuel cell, having features of high efficiency and zero carbon emission, has shown great application potential in integrated energy systems. To this end, a novel optimal scheduling strategy of electric-heat-ga...
Hydrogen fuel cell, having features of high efficiency and zero carbon emission, has shown great application potential in integrated energy systems. To this end, a novel optimal scheduling strategy of electric-heat-gas (EHG) integrated energy system considering the heat and power coupling characters of hydrogen fuel cell is proposed in this paper. However, the intricate thermoelectric coupling characteristics of fuel cells need to be investigated to develop the refined scheduling modes. Based on the constructed mechanism model of hydrogen fuel cell, the thermoelectric coupling characteristics of hydrogen fuel cell cogeneration is analyzed among the feasible region, and further linearized as a series of constraints in the scheduling model. Considering the carbon trading cost, energy purchase cost and wind curtailment cost, the scheduling model of the EHG integrated energy system is developed. The results show that consideration of nonlinear thermoelectric coupling characteristics has improved the scheduling accuracy, which is more desirable in real projects. Using the established scheduling strategy, the available renewable resources can be fully absorbed. The carbon emissions and the total cost are significantly reduced, by 25.8% and 16%, respectively. Studies also indicate that the proposed optimal scheduling significantly enhances the operational flexibility and economic effect of the system.
In this paper, we present an approach, inspired by human behavior, in predicting the state of a high speed object based on the state of another object that causes such a high speed, e.g. predicting the state of a high...
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In this paper a novel approach based on multi-robot cooperation is introduced for inspection and repair of dome structures. In this application, three robots which can be extended to more, connect to each other by thr...
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Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming ...
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Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.
We apply recent results on robust global asymptotic stabilization of the attitude of a single rigid body to the problem of synchronizing the attitude of a network of rigid bodies using graph-local information. The pro...
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The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections ...
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The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Then its connections to various topics and research areas are briefly discussed, including order determination, pattern recognition, data mining, machine learning, statistical regression and manifold embedding. Finally, some results of variable selection in system identification in the recent literature are presented.
In this paper we propose a centralized algorithm for stable operation of a multi-robot dome inspection, repair, and maintenance based on potential field method. The multi-robot system consists of two robots, a leader ...
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This paper presents a registration framework for curve skeleton of 3D models. The algorithm matches two skeletons and deforms a source skeleton to the other target skeleton, so that each node aligns with its closest p...
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The paper elaborates the design of an optimal feedback control system for a washing machine. It is sought to save on the water and energy consumption and the associated wear and tear and detergent consumption through ...
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This paper introduces a post-iteration averaging algorithm to achieve asymptotic optimality in convergence rates of stochastic approximation algorithms for consensus control with structural constraints. The algorithm ...
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This paper introduces a post-iteration averaging algorithm to achieve asymptotic optimality in convergence rates of stochastic approximation algorithms for consensus control with structural constraints. The algorithm involves two stages. The first stage is a coarse approximation obtained using a sequence of large stepsizes. Then, the second stage provides a refinement by averaging the iterates from the first stage. We show that the new algorithm is asymptotically efficient and gives the optimal convergence rates in the sense of the best scaling factor and 'smallest' possible asymptotic variance.
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