The safety and economy of ship navigation will be impacted by the randomness of meteorology and the timeliness of the forecasting system, thus it is essential to take this into account when optimizing ship speed. A mathematical model of a hybrid diesel-electric ship is first established. Using the k-means clustering method, typical scenarios of prediction mistakes are produced while taking into account the uncertainty of wind speed and wave height predictions in meteorological data. Based on this, a stochastic optimization-based energy management and speed optimization model for hybrid ships is established and solved by an improved particle swarm algorithm. The simulation results confirm the superiority of the suggested model in lowering the ship's fuel consumption and enhancing safety and stability.
KEYWORDS: Blockchain, Photovoltaics, Systems modeling, Data privacy, Telecommunications, Polonium, Power consumption, Data modeling, Computing systems, Stochastic processes
Virtual Power Plant (VPP), as a technology for the aggregated management of distributed resources, has received extensive research and application. Concurrently, as the process of power market reform advances, the collaborative operation of multiple VPPs has become a crucial research focus. Against this backdrop, this paper proposes a decentralized collaborative governance model for multiple virtual power plants based on the blockchain Delegated Proof of Stake (DPoS) consensus mechanism. Considering the dual characteristics of source and load in VPPs, a singular VPP scheduling model is introduced. The paper outlines the process of the blockchain DPoS consensus mechanism and introduces a decentralized iterative pricing mechanism for multiple virtual power plant systems. This mechanism, combined with the DPoS consensus mechanism, utilizes witness nodes as multi-centralized entities to safeguard against malicious attacks and single-point failures. Finally, case studies validate the effectiveness and rationality of the proposed model.
KEYWORDS: Risk assessment, Renewable energy, Photovoltaics, Wind energy, Wind speed, Power grids, Solar energy, Monte Carlo methods, Telecommunications, Probability theory
In order to reflect the impact of source-load uncertainty on the overall operation risk of the power system in the future time interval, this paper establishes a multi-dimensional risk assessment system for renewable energy distribution networks based on value-at-risk. Firstly, the output probability model and load probability model of wind power photovoltaic are established, and then the sampling combination and power flow calculation are carried out based on the Monte Carlo method, and the corresponding node voltage and branch power flow results are obtained. Calculate the two risk indicators of branch power limit and node voltage limit at each prediction time of the distribution network, and use them as the first dimension risk assessment index; secondly, based on the value-at-risk theory to quantitatively evaluate the system risk, calculate the second dimension risk assessment Index; Finally, calculate the third dimension risk assessment index, calculate the comprehensive risk index through the entropy weight method, and comprehensively and reasonably analyze the operation risk of the distribution network under the access of different amounts of renewable energy. Finally, the rationality of the proposed model and method is verified by IEEE33 example system.
Facing the environmental problems caused by high carbon emissions, multi-energy coupling technology cooperates with carbon trading mechanism to achieve low-carbon operation of virtual power plant(VPP). This article firstly analyses the allocation method of carbon emission quota and the ladder-type carbon trading mechanism. Secondly, in order to realize low-carbon economic dispatch and multi-energy demand response (DR) of VPP, a VPP operation optimization model is established based on multi-energy coupling. Finally, a case is studied to verify the economic and environmental benefits of this model. The results show that ladder-type carbon trading mechanism can reduce the carbon emissions of the system.
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