An incorporation and application of a two-dimensional, unstructured grid hydrodynamic model with a suspended sediment transport module is presented in the study. The model has a satisfactory verification with availabl...
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An incorporation and application of a two-dimensional, unstructured grid hydrodynamic model with a suspended sediment transport module is presented in the study. The model has a satisfactory verification with available measured data. After the verification, the variation of tidal current field and the seabed evolution are simulated. Based on the simulation results, the paper compares and analyzes the effects of different axis layouts of detached breakwater on flow field and seabed evolution. The results show that after the construction of the breakwater, the flow velocity of the both sides of the breakwater decreases, the flow velocity of the east entrance increases, and the erosion and siltation of sediment are consistent with the change of the flow field. In addition, the smaller the angle between the breakwater axis and the depth contour is, the smaller the impact on the change of the tidal current field and sediment erosion and siltation is.
The purpose of the study is to optimize power price in smart homes that connect to share energy. A Demand Side Management (DSM) system is used to coordinate P2P energy trading between smart homes using the improved ea...
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ISBN:
(数字)9798350309638
ISBN:
(纸本)9798350309645
The purpose of the study is to optimize power price in smart homes that connect to share energy. A Demand Side Management (DSM) system is used to coordinate P2P energy trading between smart homes using the improved eagle perching optimizer (IEPO). The IEPO algorithm produces optimum solutions for 99% of actual datasets, according to the outcomes. It is possible that consumer price distribution in the microgrid (MG) could be unequal as a result of P2P energy trading. The Pareto optimality principle addresses the issue of unequal price distribution, preventing households from being harmed by improving the costs of others. A final evaluation is performed on the effect of renewable energy and the penetration of storage within the MG. As the renewable energy and the penetration of storage increases, savings cannot necessarily be linear. As the saturation point approaches, they slowly begin to decline.
Decentralized peer-to-peer Local Energy Markets (LEMs) are gaining popularity as local power production from Renewable Energy Sources (RESs) increases. The study investigates a blockchain-driven LEM in which prosumers...
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ISBN:
(数字)9798350309638
ISBN:
(纸本)9798350309645
Decentralized peer-to-peer Local Energy Markets (LEMs) are gaining popularity as local power production from Renewable Energy Sources (RESs) increases. The study investigates a blockchain-driven LEM in which prosumers and consumers buy and sell energy independently of the involvement of a third party. The suggested scheme involves Home Energy Management (HEM) and demurrage mechanisms that enable both consumers and prosumers to reduce their power prices and improve their power usage. The end-user can likewise move the load to off-peak periods and benefit from lower energy costs from the LEM through the approach. In this solution, HEM and demurrage mechanisms are used to optimize power usage as well as energy costs. As well as providing adequate power for the LEM, it is economically beneficial for end users and the community. The proposed system in the study utilizes the Deep Deterministic Policy Gradient (DDPG) algorithm and demurrage mechanisms to optimize electricity usage and energy costs. Meanwhile, smart contract on the Ethereum blockchain regulate and safeguard the electricity trading process.
The governance of service ecosystem needs to balance efficiency and fairness to promote the sustainable development of the system, making it an important topic. However, service entities in the service ecosystem have ...
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ISBN:
(数字)9798350368550
ISBN:
(纸本)9798350368567
The governance of service ecosystem needs to balance efficiency and fairness to promote the sustainable development of the system, making it an important topic. However, service entities in the service ecosystem have autonomy and engage in dynamic game with governance strategies, leading to governance challenges. To address this issue, we model the governance process as a repeated sequential game between the governance algorithm and service entities, and propose a novel two-level learning algorithm. This algorithm considers the learning evolution of service entities and the co-evolutionary of the governance algorithm, using reinforcement learning to learn effective governance strategies while also considering the response function of service entities to balance efficiency and fairness. Combining the ideas of bilevel optimization and online learning, this algorithm effectively balances exploration (understanding the service entities’ responses function) and exploitation (choosing efficient actions). We apply the algorithm to a classic service ecosystem, the ride-hailing service system, and empirically demonstrate its effectiveness in the governance task of order dispatching.
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