Example of Protection and Control of Modern Power Systems format
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recommended Recommended

Protection and Control of Modern Power Systems — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Safety, Risk, Reliability and Quality #1 of 165 down down by None rank
Energy Engineering and Power Technology #5 of 224 down down by None rank
Electrical and Electronic Engineering #17 of 693 down down by None rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 101 Published Papers | 1625 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 02/07/2020
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Related Journals

open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 10.1
SJR: 1.57
SNIP: 2.33
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CiteRatio: 10.2
SJR: 1.57
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IEEE

Quality:  
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CiteRatio: 7.9
SJR: 1.482
SNIP: 1.906
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IEEE

Quality:  
High
CiteRatio: 10.0
SJR: 1.544
SNIP: 2.169

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

16.1

104% from 2019

CiteRatio for Protection and Control of Modern Power Systems from 2016 - 2020
Year Value
2020 16.1
2019 7.9
2018 0.9
graph view Graph view
table view Table view

2.831

64% from 2019

SJR for Protection and Control of Modern Power Systems from 2019 - 2020
Year Value
2020 2.831
2019 1.73
graph view Graph view
table view Table view

5.451

48% from 2019

SNIP for Protection and Control of Modern Power Systems from 2019 - 2020
Year Value
2020 5.451
2019 3.682
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 104% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 64% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 48% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Protection and Control of Modern Power Systems

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Springer

Protection and Control of Modern Power Systems

Approved by publishing and review experts on SciSpace, this template is built as per for Protection and Control of Modern Power Systems formatting guidelines as mentioned in Springer author instructions. The current version was created on and has been used by 515 authors to write and format their manuscripts to this journal.

Energy generation

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Last updated on
02 Jul 2020
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ISSN
1606-8610
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
White faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Citation Type
Author Year
(Blonder et al, 1982)
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Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1186/S41601-019-0122-8
A survey on control issues in renewable energy integration and microgrid
Faisal R. Badal1, Purnima Das2, Subrata K. Sarker1, Sajal K. Das1

Abstract:

This paper describes the usefulness of renewable energy throughout the world to generate power. Renewable energy adds a remarkable scope in power system. Renewable energy sources act as the prime mover of a microgrid. The Microgrid is a small network of power system with distributed generation (DG) units connected in parallel... This paper describes the usefulness of renewable energy throughout the world to generate power. Renewable energy adds a remarkable scope in power system. Renewable energy sources act as the prime mover of a microgrid. The Microgrid is a small network of power system with distributed generation (DG) units connected in parallel. The integration challenges of renewable energy sources and the control of microgrid are described in this paper. The varied nature of DG system produces voltage and frequency deviation. The unknown nature of the load produces un-modeled dynamics. This un-modeled dynamic introduces measurable effects on the performance of the microgrid. This paper investigates the performance of the microgrid against different scenarios. The voltage of the microgrid is controlled by using different controllers and their results are also investigated. The performance of controllers is investigated using MATLAB/Simulink SimPowerSystems. read more read less

Topics:

Microgrid (74%)74% related to the paper, Distributed generation (56%)56% related to the paper, Renewable energy (53%)53% related to the paper, Electric power system (52%)52% related to the paper, Prime mover (51%)51% related to the paper
View PDF
220 Citations
open accessOpen access Journal Article DOI: 10.1186/S41601-019-0147-Z
Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems
V. V. S. N. Murty1, Ashwani Kumar1

Abstract:

Microgrid with hybrid renewable energy sources is a promising solution where the distribution network expansion is unfeasible or not economical. Integration of renewable energy sources provides energy security, substantial cost savings and reduction in greenhouse gas emissions, enabling nation to meet emission targets. Microg... Microgrid with hybrid renewable energy sources is a promising solution where the distribution network expansion is unfeasible or not economical. Integration of renewable energy sources provides energy security, substantial cost savings and reduction in greenhouse gas emissions, enabling nation to meet emission targets. Microgrid energy management is a challenging task for microgrid operator (MGO) for optimal energy utilization in microgrid with penetration of renewable energy sources, energy storage devices and demand response. In this paper, optimal energy dispatch strategy is established for grid connected and standalone microgrids integrated with photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), diesel generator (DG) and battery energy storage system (ESS). Techno-economic benefits are demonstrated for the hybrid power system. So far, microgrid energy management problem has been addressed with the aim of minimizing operating cost only. However, the issues of power losses and environment i.e., emission-related objectives need to be addressed for effective energy management of microgrid system. In this paper, microgrid energy management (MGEM) is formulated as mixed-integer linear programming and a new multi-objective solution is proposed for MGEM along with demand response program. Demand response is included in the optimization problem to demonstrate it’s impact on optimal energy dispatch and techno-commercial benefits. Fuzzy interface has been developed for optimal scheduling of ESS. Simulation results are obtained for the optimal capacity of PV, WT, DG, MT, FC, converter, BES, charging/discharging scheduling, state of charge of battery, power exchange with grid, annual net present cost, cost of energy, initial cost, operational cost, fuel cost and penalty of greenhouse gases emissions. The results show that CO2 emissions in standalone hybrid microgrid system is reduced by 51.60% compared to traditional system with grid only. Simulation results obtained with the proposed method is compared with various evolutionary algorithms to verify it’s effectiveness. read more read less

Topics:

Microgrid (68%)68% related to the paper, Energy management (62%)62% related to the paper, Energy storage (59%)59% related to the paper, Demand response (58%)58% related to the paper, Renewable energy (57%)57% related to the paper
View PDF
216 Citations
open accessOpen access Journal Article DOI: 10.1186/S41601-019-0126-4
From demand response to integrated demand response: review and prospect of research and application
Wujing Huang1, Ning Zhang1, Chongqing Kang1, Mingxuan Li1, Molin Huo

Abstract:

In the traditional power system demand response, customers respond to electricity price or incentive and change their original power consumption pattern accordingly to gain additional benefits. With the development of multi-energy systems (MES) in which electricity, heat, natural gas and other forms of energy are coupled with... In the traditional power system demand response, customers respond to electricity price or incentive and change their original power consumption pattern accordingly to gain additional benefits. With the development of multi-energy systems (MES) in which electricity, heat, natural gas and other forms of energy are coupled with each other, all types of energy customers are able to participate in demand response, leading to the concept of integrated demand response (IDR). In IDR, energy consumers can response not only by reducing energy consumption or opting for off-peak energy consumption but also by changing the type of the consumed energy. Taking the traditional demand response in power system as a starting point, the studies of the fundamental theory, framework design and potential estimation of demand response in power system are reviewed, and the practical cases and software development of demand response are introduced. Finally, the current theoretical research and application of IDR are assessed. read more read less

Topics:

Demand response (73%)73% related to the paper, Energy consumption (62%)62% related to the paper, Forms of energy (51%)51% related to the paper, Electric power system (50%)50% related to the paper
View PDF
179 Citations
open accessOpen access Journal Article DOI: 10.1186/S41601-017-0040-6
Optimal energy management for industrial microgrids with high-penetration renewables
Han Li, Abinet Tesfaye Eseye1, Jianhua Zhang1, Dehua Zheng

Abstract:

This paper presents a day-ahead optimal energy management strategy for economic operation of industrial microgrids with high-penetration renewables under both isolated and grid-connected operation modes. The approach is based on a regrouping particle swarm optimization (RegPSO) formulated over a day-ahead scheduling horizon w... This paper presents a day-ahead optimal energy management strategy for economic operation of industrial microgrids with high-penetration renewables under both isolated and grid-connected operation modes. The approach is based on a regrouping particle swarm optimization (RegPSO) formulated over a day-ahead scheduling horizon with one hour time step, taking into account forecasted renewable energy generations and electrical load demands. Besides satisfying its local energy demands, the microgrid considered in this paper (a real industrial microgrid, “Goldwind Smart Microgrid System” in Beijing, China), participates in energy trading with the main grid; it can either sell power to the main grid or buy from the main grid. Performance objectives include minimization of fuel cost, operation and maintenance costs and energy purchasing expenses from the main grid, and maximization of financial profit from energy selling revenues to the main grid. Simulation results demonstrate the effectiveness of various aspects of the proposed strategy in different scenarios. To validate the performance of the proposed strategy, obtained results are compared to a genetic algorithm (GA) based reference energy management approach and confirmed that the RegPSO based strategy was able to find a global optimal solution in considerably less computation time than the GA based reference approach. read more read less

Topics:

Microgrid (61%)61% related to the paper, Intermittent energy source (61%)61% related to the paper, Energy management (60%)60% related to the paper, Grid (53%)53% related to the paper, Renewable energy (52%)52% related to the paper
View PDF
165 Citations
open accessOpen access Journal Article DOI: 10.1186/S41601-016-0016-Y
Short-term wind power prediction based on extreme learning machine with error correction
Zhi Li1, Lin Ye1, Yongning Zhao1, Xuri Song2, Jingzhu Teng1, Jingxin Jin

Abstract:

Large-scale integration of wind generation brings great challenges to the secure operation of the power systems due to the intermittence nature of wind. The fluctuation of the wind generation has a great impact on the unit commitment. Thus accurate wind power forecasting plays a key role in dealing with the challenges of powe... Large-scale integration of wind generation brings great challenges to the secure operation of the power systems due to the intermittence nature of wind. The fluctuation of the wind generation has a great impact on the unit commitment. Thus accurate wind power forecasting plays a key role in dealing with the challenges of power system operation under uncertainties in an economical and technical way. In this paper, a combined approach based on Extreme Learning Machine (ELM) and an error correction model is proposed to predict wind power in the short-term time scale. Firstly an ELM is utilized to forecast the short-term wind power. Then the ultra-short-term wind power forecasting is acquired based on processing the short-term forecasting error by persistence method. For short-term forecasting, the Extreme Learning Machine (ELM) doesn’t perform well. The overall NRMSE (Normalized Root Mean Square Error) of forecasting results for 66 days is 21.09 %. For the ultra-short term forecasting after error correction, most of forecasting errors lie in the interval of [−10 MW, 10 MW]. The error distribution is concentrated and almost unbiased. The overall NRMSE is 5.76 %. The ultra-short-term wind power forecasting accuracy is further improved by using error correction in terms of normalized root mean squared error (NRMSE). read more read less

Topics:

Wind power forecasting (70%)70% related to the paper, Wind power (61%)61% related to the paper, Electric power system (53%)53% related to the paper, Extreme learning machine (52%)52% related to the paper
View PDF
133 Citations
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To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Protection and Control of Modern Power Systems?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Protection and Control of Modern Power Systems. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Protection and Control of Modern Power Systems?

The 5 most common citation types in order of usage for Protection and Control of Modern Power Systems are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Protection and Control of Modern Power Systems Endnote style according to Elsevier guidelines.

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