Pattern Classification and PSO Optimal Weights Based Sky Images Cloud Motion Speed Calculation Method for Solar PV Power Forecasting

Zhen, Zhao; Pang, Shuaijie; Wang, Fei; Li, Kangping; Li, Zhigang; Ren, Hui; Shafie‐khah, Miadreza; Catalào, João P. S.

doi:10.1109/tia.2019.2904927

Cited by 123 publications

(27 citation statements)

References 46 publications

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“…Because of its fast speed, no need to manually set the threshold, etc. ; it has been widely used in the field of image processing [31][32][33] and has achieved excellent results. us, PSO is adopted here to remove the background noises.…”

Section: Difference-particle Swarm Optimization (D-pso)mentioning

confidence: 99%

Real-Time Height Measurement for Moving Pedestrians

et al. 2020

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Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

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Section: Difference-particle Swarm Optimization (D-pso)mentioning

confidence: 99%

Real-Time Height Measurement for Moving Pedestrians

et al. 2020

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“…DR is, indeed, considered as a promising means to facilitate the accommodation of renewable energy in addition to some other technologies such as wind and solar power forecasting with different time scales (e.g. ultra-short term [3], [4], short term [5], [6]). End-use customers participate in DR programs by changing their electricity consumption patterns in response to dynamic time varying electricity price or incentive signals [7].…”

Section: S Imentioning

confidence: 99%

Day-Ahead Optimal Joint Scheduling Model of Electric and Natural Gas Appliances for Home Integrated Energy Management

Zhang

et al. 2019

IEEE Access

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Home energy management systems (HEMSs) enable residential customers to efficiently participate in demand response programs in order to obtain optimal benefits. Traditional HEMSs only manage household electric appliances to reduce the electricity consumption cost while the optimal scheduling of natural gas appliances has been overlooked. Due to the increasing popularity of natural gas appliances in modern smart homes, the electricity consumption of residential customers connected to the natural gas network is significantly affected by the use of natural gas appliances. To consider the interaction between electric and natural gas appliances in households, a day-ahead optimal joint scheduling model of electric and natural gas appliances for HEMS is proposed. Firstly, all household appliances are classified into several categories and the mathematical model of each appliance is presented. Then, a day-ahead optimal joint scheduling model of both electric and natural gas appliances for HEMS is formulated, in which the objective function is to minimize the household's energy cost and the dissatisfaction level caused by the shifting, reduction and replacement of loads in response to the time varying prices. Case studies using realistic data indicate that the proposed model can save the total energy costs up to 30% for customers whilst ensuring their satisfaction levels. INDEX TERMS Home energy management system, natural gas, demand response, joint scheduling, dissatisfaction. A. SUPERSCRIPTS bch Battery charging bdch Battery discharging dw Dishwasher eac Electric air conditioner el Electric light es Electric stove ev Electric vehicle ewh Electric water heater gahs Gas air heating system The associate editor coordinating the review of this manuscript and approving it for publication was Alexander Micallef. gs Gas stove gwh Gas water heater ua Uncontrollable appliance s Stove wh Water heater wm Washing machine B. INDEXES AND SETS

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“…Zhen et al [14] presented a different way to forecast PV generation, and the study applies particle swarm optimisation to evaluate sky images. Thus, it's possible to predict the movement of clouds concerning its speed.…”

Section: Introductionmentioning

confidence: 99%