Joint Optimization of Channel Allocation,Link Assignment and Power Control for Device-to-Device Communication Underlaying Cellular Network

Device-to-Device(D2D) communication has been proposed to facilitate cellular network with system capacity(SC) and quality of service(QoS).We consider the design of link assignment(LA),channel allocation(CA)and power control(PC) in D2D-aided content delivery scenario for both user fairness(UF)and system throughput(ST) under QoS requirement.Due to the complexity of the problem,we decompose it into two components:CA is formulated from graph perspective to mitigate severe co-channel interference,which turns out to be the Max K-cut problem;LA and PC are jointly optimized to utilize the gain achieved from CA for supreme performance,and specifically,genetic algorithm(GA) is adopted to optimize LA,but when deriving the fitness of each chromosome,PC optimization will be involved.Thanks to numerical results,we elucidate the efficacy of our scheme.

Ensemble Wind Power Prediction Interval with Optimal Reserve Requirement

Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Thus,a prediction model that performs well in one case might underperform in another.To address this shortcoming,this paper proposes an ensemble WPPI framework that integrates multiple WPPI models with distinct characteristics to improve robustness.Another important and often overlooked factor is the role of probabilistic wind power prediction(WPP)in quantifying wind power uncertainty,which should be handled by operating reserve.Operating reserve in WPPI frameworks enhances the efficacy of WPP.In this regard,the proposed framework employs a novel bi-layer optimization approach that takes both WPPI quality and reserve requirements into account.Comprehensive analysis with different real-world datasets and various benchmark models validates the quality of the obtained WPPIs while resulting in more optimal reserve requirements.

Time constant optimization of solar irradiance absolute radiometer

We experimentally evaluate and optimize the time constant of solar irradiance absolute radiometer(SIAR). The systemic error introduced by variable time constant is studied by a finite element method. The results shown that, with a classic time constant of 30 s for SIAR, the systemic errors are 0.06% in the midday and 0.275% in the morning and afternoon. The uncertainty level which can be considered negligible for SIAR is also investigated, and it is suggested that the uncertainty level has to be less than 0.02%. Then, combining the requirement of international comparison with these two conclusions, we conclude that the suitable time constant for SIAR is 20 s.