The advent of distributed energy resources encourages the direct energy transaction among grid subscribers, who may play interchangeable roles as energy producers and consumers (prosumers). Since microgrids integrated...
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The advent of distributed energy resources encourages the direct energy transaction among grid subscribers, who may play interchangeable roles as energy producers and consumers (prosumers). Since microgrids integrated with distributed energy resources (DERs) can offer diverse options, it is desirable to design a proper energy transaction protocol to minimize the cost of prosumers. This paper proposes a discrete biased min-consensus algorithm to discover the best supply candidate with minimum power loss. The proposed discrete approach is implemented based on the multi-energy-router system (MERS) by performing three types of consensus-based algorithms in a distributed manner. Major procedures include demand request broadcasting, transmission power loss calculation, and the optimalrouting discovery. The convergence of the proposed discrete approach is proved by rigorous mathematical analysis. Simulations demonstrate the effectiveness of the proposed discrete approach for both small- and large-scale systems.
The purpose of this paper is to relax traffic congestion caused by the decrease in vehicle speed in case of a driver searching for a parking lot in traffic network, by using Smart Parking System. Smart Parking System ...
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ISBN:
(纸本)9788993215182
The purpose of this paper is to relax traffic congestion caused by the decrease in vehicle speed in case of a driver searching for a parking lot in traffic network, by using Smart Parking System. Smart Parking System is a system that allocates parking lot considering both the driver's preference and the parking lot manager's preference in advance. At that time, driver should know the optimal route and its time from currrent location to each parking lot. In this paper, Smart Parking System consider the road condition in traffic network and present the driver time by the optimal route from the driver's current location to each parking lot. Then, the parking lot allocation is determined by using matching theory considering both the driver's preference including information of optimal route and its time and the parking lot manager's preference. Finally, the effectiveness is confirmed by numerical simulations and results of parking lot allocation using optimal vehicle routing.
Due to the private ownerships of various resource and equipment in a microgrid, it is essential to design a proper power trading strategy for a mutually satisfying partnership among suppliers and users. This paper pro...
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Due to the private ownerships of various resource and equipment in a microgrid, it is essential to design a proper power trading strategy for a mutually satisfying partnership among suppliers and users. This paper proposes a novel discounted min-consensus algorithm to discover the optimal electrical power trading route with minimal power loss in dc microgrids. The proposed distributed algorithm only requires information exchange among neighbors based on a peer-to-peer communication protocol, which is robust to topology changes and enables parallel data processing to achieve fast decision-making. The convergence and optimality of the proposed discounted min-consensus algorithm are guaranteed by rigorous analysis. Simulation results of the 10-bus, 68-bus, and 1062-bus power systems demonstrate the effectiveness of the proposed distributed optimalrouting strategy for electrical power trading. Moreover, the proposed novel distributed algorithm sheds light on applying distributed control and optimization approaches to solve problems arising in artificial intelligence.
We study the question of routing for minimum average drop rate over unreliable servers that are susceptible to random buffer failures, which arises in unreliable data or manufacturing networks. Interestingly, we first...
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We study the question of routing for minimum average drop rate over unreliable servers that are susceptible to random buffer failures, which arises in unreliable data or manufacturing networks. Interestingly, we first reveal that the traditional Join-the-Shortest-Queue (JSQ) or optimal Randomized Splitting (RS) strategies are consistently outperformed by the Constant Splitting Rule (CSR) where the incoming traffic is split with a constant fraction towards the available servers. This finding motivates us to obtain the optimal splitting fraction under CSR. However, the objective function to be minimized depends on the mean queue length of the servers, whose closed-form expression is not available and often intractable for general arrival and service processes. Thus, we use non-derivative methods to solve this optimization problem by approximately evaluating the objective value at each iteration. To that end, we explicitly characterize the approximation error by utilizing the regenerating nature of unreliable buffers. By adaptively controlling the precision of this approximation, we show that our proposed algorithm converges to an optimal splitting decision in the almost sure sense. Yet, previous works on non-derivative methods assume continuous differentiability of the objective function, which is not the case in our setup. We relax this strong assumption to the case when the objective function is locally Lipschitz continuous, which is another contribution of this paper. (C) 2013 Elsevier B.V. All rights reserved.
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