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Ethics & Disclosures
Statistical machine learning model for capacitor planning considering uncertainties in photovoltaic power
It is obvious that renewable energy is becoming more and more important in the modern energy system because of its environmental friendliness. In recent years, photovoltaic (PV) have developed rapidly. Renewable energy integration and flexible demand response make smart grid operation scenarios complex and changeable, which bring challenges to network planning. If every possible scenario is considered, the solution to the planning can become extremely time-consuming and difficult. This paper introduces statistical machine learning (SML) techniques to carry out multi-scenario based probabilistic power flow calculations and describes their application to the stochastic planning of distribution networks. The proposed SML includes linear regression, probability distribution, Markov chain, is oprobabilistic transformation, maximum likelihood estimator, stochastic response surface and center point method. Based on the above SML model, capricious weather, photovoltaic power generation, thermal load, power flow and uncertainty programming are simulated. Taking a 33-bus distribution system as an example, this paper compares the stochastic planning model based on SML with the traditional models published in the literature. The results verify that the proposed model greatly improves planning performance while meeting accuracy requirements. Read more.
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Fault identification scheme for protection and adaptive reclosing in a hybrid multi-terminal HVDC system
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Comparative framework for AC-microgrid protection schemes: challenges, solutions, real applications, and future trends
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Time–frequency multiresolution of fault-generated transient signals in transmission lines using a morphological filter
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Voltage imbalance mitigation in an active distribution network using decentralized current control
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Design of a P-&-O algorithm based MPPT charge controller for a stand-alone 200W PV system
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Developments of power system protection and control
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A survey on control issues in renewable energy integration and microgrid
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An improved MPPT control strategy based on incremental conductance algorithm
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Modern improvement techniques of direct torque control for induction motor drives - a review
Open thematic series
Article Collections
Power System Protection and Control Containing Renewable Energy Power Generation
Edited by : Xinzhou Dong, Aiqin Zhang
Energy Storage across Multiple Energy Systems
Edited by: Jinyu Wen, Jiakun Fang, Jialin Li, Gangu Yan, Jinghua Li
Integrating Centralized and Distributed Renewables in Future Power Systems
Edited by: Chongqing Kang, Ning Zhang
Power System Protection and Control
Edited by: Zhiqian Bo, Jinmei Shi, Xinli Jiang
Forecasting and Scheduling Method of Wind and Solar Power Generations
Advances in Energy Management of User and Building-level Integrated Energy Systems
https://pcmp.springeropen.com/aem-bies
Special Issue on “Energy System Planning and Operation Under the Coupled Carbon Trading Market and Power Market”
Aims and scope
Protection and Control of Modern Power Systems is an international academic journal co-published by Power System Protection and Control Press and Springer. The journal is devoted to presenting new theories, technologies and top-level academic achievements in the field of protection and control in modern power systems. It strives to accelerate the development of the field by serving as a bridge between Chinese and global researchers in the field. In doing so, Protection and Control of Modern Power Systems makes an important contribution to the power industry.
The journal has an international authorship and a broad scope, including contemporary topics such as:
- power system relay protection
- power system analysis and control
- power system planning
- internet of energy
- alternative energy generation
- smart substations
- intelligent power transmission and utilization techniques
- interactions between large-scale electric vehicles and power grids
- microgrid techniques
- application of power electronics in power systems
- electric power automation and remote control techniques
- power system communication
- power quality
- electricity market
Affiliated with
Protection and Control of Modern Power Systems is affiliated with Power System Protection and Control Press.
Annual Journal Metrics
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Citation impact
10.500 - 2 Year Impact Factor (2021)
7.139 - 5 Year Impact Factor (2021)
4.727 - Source Normalized Impact per Paper (SNIP)
3.240 - SCImago Journal Rank (SJR)
22.8 - CiteScoreSpeed
39 days to first decision for all manuscripts (Median)
63 days to first decision for reviewed manuscripts only (Median)Usage
240,818 downloads (2022)
- ISSN: 2367-0983 (electronic)
The journal is indexed by
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- ProQuest-ExLibris Summon
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- Institute of Scientific and Technical Information of China
- Naver
- Chinese Academy of Sciences (CAS) - GoOA
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