Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithm Article Swipe
Adel A. Abou El‐Ela
,
Ragab A. El‐Sehiemy
,
Abdullah M. Shaheen
,
Ayman S. Shalaby
,
Mohamed T. Mouwafi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s00521-024-09485-5
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s00521-024-09485-5
Robust reliability Generation Expansion Planning (GEP) turns out to be a crucial step for an efficient energy management system in a modern power grid, especially under renewable energy employment. The integration of all such components in a GEP model makes it a large-scale, nonlinear, and mixed-variable mathematical modeling problem. In this paper, the presence of wind energy uncertainty is analyzed. Both long and short-term uncertainties are incorporated into the proposed GEP model. The first step concerns the impact of long-term wind uncertainties through the annual variations of the capacity credit of two real sites in Egypt at Zafaranh and Shark El-ouinate. The second step deals with the short-term uncertainties of each wind site. The wind speed uncertainty of each wind site is modeled by probability distribution function. Then, wind power is estimated from the wind power curve for each wind site and Monte-Carlo Simulation is performed. Fast Gas Turbine and/or Pump Hydro Storage are incorporated to cope with short-term uncertainties. Sensitivity analysis is implemented for 3, 6, and 12 stages as short and long planning horizons to minimize the total costs with wind energy penetration and emission reduction over planning horizons. Also, a novel Honey Badger Algorithm (HBA) with model modifications such as Virtual Mapping Procedure, Penalty Factor Approach, and the Modified of Intelligent Initial Population Generation is utilized for solving the proposed GEP problem. The obtained results are compared with other algorithms to ensure the superior performance of the proposed HBA. According to the results of the applicable test systems, the proposed HBA performs better than the others, with percentage reductions over CSA, AO, BES, and PSO ranging up to 4.2, 2.72, 2.7, and 3.4%, respectively.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s00521-024-09485-5
- https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdf
- OA Status
- hybrid
- Cited By
- 4
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392109536
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4392109536Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/s00521-024-09485-5Digital Object Identifier
- Title
-
Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-23Full publication date if available
- Authors
-
Adel A. Abou El‐Ela, Ragab A. El‐Sehiemy, Abdullah M. Shaheen, Ayman S. Shalaby, Mohamed T. MouwafiList of authors in order
- Landing page
-
https://doi.org/10.1007/s00521-024-09485-5Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdfDirect OA link when available
- Concepts
-
Renewable energy, Badger, Computer science, Penetration (warfare), Algorithm, Mathematical optimization, Mathematics, Electrical engineering, Engineering, Operations research, Biology, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 1Per-year citation counts (last 5 years)
- References (count)
-
59Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4392109536 |
|---|---|
| doi | https://doi.org/10.1007/s00521-024-09485-5 |
| ids.doi | https://doi.org/10.1007/s00521-024-09485-5 |
| ids.openalex | https://openalex.org/W4392109536 |
| fwci | 1.47667389 |
| type | article |
| title | Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithm |
| biblio.issue | 14 |
| biblio.volume | 36 |
| biblio.last_page | 7952 |
| biblio.first_page | 7923 |
| topics[0].id | https://openalex.org/T10424 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2208 |
| topics[0].subfield.display_name | Electrical and Electronic Engineering |
| topics[0].display_name | Electric Power System Optimization |
| topics[1].id | https://openalex.org/T10454 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.998199999332428 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2208 |
| topics[1].subfield.display_name | Electrical and Electronic Engineering |
| topics[1].display_name | Optimal Power Flow Distribution |
| topics[2].id | https://openalex.org/T10603 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9965000152587891 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2208 |
| topics[2].subfield.display_name | Electrical and Electronic Engineering |
| topics[2].display_name | Smart Grid Energy Management |
| is_xpac | False |
| apc_list.value | 2390 |
| apc_list.currency | EUR |
| apc_list.value_usd | 2990 |
| apc_paid.value | 2390 |
| apc_paid.currency | EUR |
| apc_paid.value_usd | 2990 |
| concepts[0].id | https://openalex.org/C188573790 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6977171301841736 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q12705 |
| concepts[0].display_name | Renewable energy |
| concepts[1].id | https://openalex.org/C2777146433 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6458690762519836 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q638105 |
| concepts[1].display_name | Badger |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5872817039489746 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C80107235 |
| concepts[3].level | 2 |
| concepts[3].score | 0.4351350963115692 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7162625 |
| concepts[3].display_name | Penetration (warfare) |
| concepts[4].id | https://openalex.org/C11413529 |
| concepts[4].level | 1 |
| concepts[4].score | 0.3933465778827667 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[4].display_name | Algorithm |
| concepts[5].id | https://openalex.org/C126255220 |
| concepts[5].level | 1 |
| concepts[5].score | 0.3926513195037842 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[5].display_name | Mathematical optimization |
| concepts[6].id | https://openalex.org/C33923547 |
| concepts[6].level | 0 |
| concepts[6].score | 0.22166183590888977 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[6].display_name | Mathematics |
| concepts[7].id | https://openalex.org/C119599485 |
| concepts[7].level | 1 |
| concepts[7].score | 0.17839717864990234 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q43035 |
| concepts[7].display_name | Electrical engineering |
| concepts[8].id | https://openalex.org/C127413603 |
| concepts[8].level | 0 |
| concepts[8].score | 0.16073104739189148 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[8].display_name | Engineering |
| concepts[9].id | https://openalex.org/C42475967 |
| concepts[9].level | 1 |
| concepts[9].score | 0.15705904364585876 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q194292 |
| concepts[9].display_name | Operations research |
| concepts[10].id | https://openalex.org/C86803240 |
| concepts[10].level | 0 |
| concepts[10].score | 0.15663200616836548 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[10].display_name | Biology |
| concepts[11].id | https://openalex.org/C18903297 |
| concepts[11].level | 1 |
| concepts[11].score | 0.1077655553817749 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[11].display_name | Ecology |
| keywords[0].id | https://openalex.org/keywords/renewable-energy |
| keywords[0].score | 0.6977171301841736 |
| keywords[0].display_name | Renewable energy |
| keywords[1].id | https://openalex.org/keywords/badger |
| keywords[1].score | 0.6458690762519836 |
| keywords[1].display_name | Badger |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.5872817039489746 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/penetration |
| keywords[3].score | 0.4351350963115692 |
| keywords[3].display_name | Penetration (warfare) |
| keywords[4].id | https://openalex.org/keywords/algorithm |
| keywords[4].score | 0.3933465778827667 |
| keywords[4].display_name | Algorithm |
| keywords[5].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[5].score | 0.3926513195037842 |
| keywords[5].display_name | Mathematical optimization |
| keywords[6].id | https://openalex.org/keywords/mathematics |
| keywords[6].score | 0.22166183590888977 |
| keywords[6].display_name | Mathematics |
| keywords[7].id | https://openalex.org/keywords/electrical-engineering |
| keywords[7].score | 0.17839717864990234 |
| keywords[7].display_name | Electrical engineering |
| keywords[8].id | https://openalex.org/keywords/engineering |
| keywords[8].score | 0.16073104739189148 |
| keywords[8].display_name | Engineering |
| keywords[9].id | https://openalex.org/keywords/operations-research |
| keywords[9].score | 0.15705904364585876 |
| keywords[9].display_name | Operations research |
| keywords[10].id | https://openalex.org/keywords/biology |
| keywords[10].score | 0.15663200616836548 |
| keywords[10].display_name | Biology |
| keywords[11].id | https://openalex.org/keywords/ecology |
| keywords[11].score | 0.1077655553817749 |
| keywords[11].display_name | Ecology |
| language | en |
| locations[0].id | doi:10.1007/s00521-024-09485-5 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S147897268 |
| locations[0].source.issn | 0941-0643, 1433-3058 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 0941-0643 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Neural Computing and Applications |
| locations[0].source.host_organization | https://openalex.org/P4310319900 |
| locations[0].source.host_organization_name | Springer Science+Business Media |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319900, https://openalex.org/P4310319965 |
| locations[0].source.host_organization_lineage_names | Springer Science+Business Media, Springer Nature |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Neural Computing and Applications |
| locations[0].landing_page_url | https://doi.org/10.1007/s00521-024-09485-5 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5089504367 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4195-4436 |
| authorships[0].author.display_name | Adel A. Abou El‐Ela |
| authorships[0].countries | EG |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I63601056 |
| authorships[0].affiliations[0].raw_affiliation_string | Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shebeen El-Kom, 32511, Egypt |
| authorships[0].institutions[0].id | https://openalex.org/I63601056 |
| authorships[0].institutions[0].ror | https://ror.org/05sjrb944 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I63601056 |
| authorships[0].institutions[0].country_code | EG |
| authorships[0].institutions[0].display_name | Menoufia University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Adel A. Abou El-Ela |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shebeen El-Kom, 32511, Egypt |
| authorships[1].author.id | https://openalex.org/A5019940948 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-3340-4031 |
| authorships[1].author.display_name | Ragab A. El‐Sehiemy |
| authorships[1].countries | EG |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I130309236 |
| authorships[1].affiliations[0].raw_affiliation_string | Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El-Shaikh, 33516, Egypt |
| authorships[1].institutions[0].id | https://openalex.org/I130309236 |
| authorships[1].institutions[0].ror | https://ror.org/04a97mm30 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I130309236 |
| authorships[1].institutions[0].country_code | EG |
| authorships[1].institutions[0].display_name | Kafrelsheikh University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ragab A. El-Sehiemy |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafr El-Shaikh, 33516, Egypt |
| authorships[2].author.id | https://openalex.org/A5073173597 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Abdullah M. Shaheen |
| authorships[2].countries | EG |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I130009713 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez, 43221, Egypt |
| authorships[2].institutions[0].id | https://openalex.org/I130009713 |
| authorships[2].institutions[0].ror | https://ror.org/00ndhrx30 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I130009713 |
| authorships[2].institutions[0].country_code | EG |
| authorships[2].institutions[0].display_name | Suez University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Abdullah M. Shaheen |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Electrical Engineering, Faculty of Engineering, Suez University, Suez, 43221, Egypt |
| authorships[3].author.id | https://openalex.org/A5043369689 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Ayman S. Shalaby |
| authorships[3].affiliations[0].raw_affiliation_string | Middle Delta Electricity Production Company (MDEPCo), Talkha, Mansoura, Egypt |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Ayman S. Shalaby |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Middle Delta Electricity Production Company (MDEPCo), Talkha, Mansoura, Egypt |
| authorships[4].author.id | https://openalex.org/A5087465320 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Mohamed T. Mouwafi |
| authorships[4].countries | EG |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I63601056 |
| authorships[4].affiliations[0].raw_affiliation_string | Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shebeen El-Kom, 32511, Egypt |
| authorships[4].institutions[0].id | https://openalex.org/I63601056 |
| authorships[4].institutions[0].ror | https://ror.org/05sjrb944 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I63601056 |
| authorships[4].institutions[0].country_code | EG |
| authorships[4].institutions[0].display_name | Menoufia University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Mohamed T. Mouwafi |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Electrical Engineering Department, Faculty of Engineering, Menoufiya University, Shebeen El-Kom, 32511, Egypt |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdf |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Robust generation expansion planning in power grids under renewable energy penetration via honey badger algorithm |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10424 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2208 |
| primary_topic.subfield.display_name | Electrical and Electronic Engineering |
| primary_topic.display_name | Electric Power System Optimization |
| related_works | https://openalex.org/W2112305438, https://openalex.org/W2959721070, https://openalex.org/W1998661317, https://openalex.org/W2081097368, https://openalex.org/W2121265471, https://openalex.org/W4315571368, https://openalex.org/W2793703921, https://openalex.org/W2040927977, https://openalex.org/W2142023952, https://openalex.org/W2024085986 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1007/s00521-024-09485-5 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S147897268 |
| best_oa_location.source.issn | 0941-0643, 1433-3058 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 0941-0643 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Neural Computing and Applications |
| best_oa_location.source.host_organization | https://openalex.org/P4310319900 |
| best_oa_location.source.host_organization_name | Springer Science+Business Media |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319900, https://openalex.org/P4310319965 |
| best_oa_location.source.host_organization_lineage_names | Springer Science+Business Media, Springer Nature |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Neural Computing and Applications |
| best_oa_location.landing_page_url | https://doi.org/10.1007/s00521-024-09485-5 |
| primary_location.id | doi:10.1007/s00521-024-09485-5 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S147897268 |
| primary_location.source.issn | 0941-0643, 1433-3058 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 0941-0643 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Neural Computing and Applications |
| primary_location.source.host_organization | https://openalex.org/P4310319900 |
| primary_location.source.host_organization_name | Springer Science+Business Media |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319900, https://openalex.org/P4310319965 |
| primary_location.source.host_organization_lineage_names | Springer Science+Business Media, Springer Nature |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://link.springer.com/content/pdf/10.1007/s00521-024-09485-5.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Neural Computing and Applications |
| primary_location.landing_page_url | https://doi.org/10.1007/s00521-024-09485-5 |
| publication_date | 2024-02-23 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W4241480798, https://openalex.org/W2276743969, https://openalex.org/W4205632625, https://openalex.org/W3086927368, https://openalex.org/W2171287075, https://openalex.org/W2072927385, https://openalex.org/W2922019030, https://openalex.org/W2998338030, https://openalex.org/W2886654412, https://openalex.org/W2553208471, https://openalex.org/W4221082824, https://openalex.org/W3217472841, https://openalex.org/W2965499408, https://openalex.org/W2046542878, https://openalex.org/W2180654895, https://openalex.org/W2917620054, https://openalex.org/W2334562106, https://openalex.org/W2147437954, https://openalex.org/W2810158549, https://openalex.org/W2070949522, https://openalex.org/W2891793807, https://openalex.org/W2907476519, https://openalex.org/W2129901118, https://openalex.org/W2014009254, https://openalex.org/W2078159352, https://openalex.org/W2183895547, https://openalex.org/W2944477055, https://openalex.org/W1968136817, https://openalex.org/W2418462392, https://openalex.org/W2064675550, https://openalex.org/W4291237123, https://openalex.org/W3009464600, https://openalex.org/W3015310782, https://openalex.org/W3047501681, https://openalex.org/W4285732009, https://openalex.org/W4293415935, https://openalex.org/W4210417841, https://openalex.org/W4283514201, https://openalex.org/W4210605004, https://openalex.org/W3201825191, https://openalex.org/W2899447236, https://openalex.org/W2913342767, https://openalex.org/W2580615269, https://openalex.org/W3156717848, https://openalex.org/W4224223195, https://openalex.org/W2998655527, https://openalex.org/W2255207632, https://openalex.org/W1903269325, https://openalex.org/W2225775026, https://openalex.org/W2480645692, https://openalex.org/W3118082266, https://openalex.org/W4221088732, https://openalex.org/W3135401634, https://openalex.org/W2130883117, https://openalex.org/W3196661916, https://openalex.org/W2306115793, https://openalex.org/W3139484821, https://openalex.org/W2954876896, https://openalex.org/W4362721096 |
| referenced_works_count | 59 |
| abstract_inverted_index.a | 11, 21, 37, 42, 193 |
| abstract_inverted_index.12 | 169 |
| abstract_inverted_index.3, | 166 |
| abstract_inverted_index.6, | 167 |
| abstract_inverted_index.In | 50 |
| abstract_inverted_index.an | 15 |
| abstract_inverted_index.as | 171, 203 |
| abstract_inverted_index.at | 97 |
| abstract_inverted_index.be | 10 |
| abstract_inverted_index.by | 124 |
| abstract_inverted_index.in | 20, 36, 95 |
| abstract_inverted_index.is | 59, 122, 131, 145, 163, 218 |
| abstract_inverted_index.it | 41 |
| abstract_inverted_index.of | 32, 55, 79, 87, 91, 110, 118, 213, 239, 247 |
| abstract_inverted_index.to | 9, 156, 177, 234, 244, 271 |
| abstract_inverted_index.up | 270 |
| abstract_inverted_index.AO, | 265 |
| abstract_inverted_index.GEP | 38, 71, 224 |
| abstract_inverted_index.Gas | 148 |
| abstract_inverted_index.HBA | 254 |
| abstract_inverted_index.PSO | 268 |
| abstract_inverted_index.The | 30, 73, 102, 114, 226 |
| abstract_inverted_index.all | 33 |
| abstract_inverted_index.and | 45, 63, 99, 142, 168, 173, 186, 210, 267, 275 |
| abstract_inverted_index.are | 66, 154, 229 |
| abstract_inverted_index.for | 14, 138, 165, 220 |
| abstract_inverted_index.out | 8 |
| abstract_inverted_index.the | 53, 69, 77, 84, 88, 107, 134, 179, 211, 222, 236, 240, 245, 248, 252, 258 |
| abstract_inverted_index.two | 92 |
| abstract_inverted_index.2.7, | 274 |
| abstract_inverted_index.4.2, | 272 |
| abstract_inverted_index.BES, | 266 |
| abstract_inverted_index.Both | 61 |
| abstract_inverted_index.CSA, | 264 |
| abstract_inverted_index.Fast | 147 |
| abstract_inverted_index.HBA. | 242 |
| abstract_inverted_index.Pump | 151 |
| abstract_inverted_index.cope | 157 |
| abstract_inverted_index.each | 111, 119, 139 |
| abstract_inverted_index.from | 133 |
| abstract_inverted_index.into | 68 |
| abstract_inverted_index.long | 62, 174 |
| abstract_inverted_index.over | 189, 263 |
| abstract_inverted_index.real | 93 |
| abstract_inverted_index.site | 121, 141 |
| abstract_inverted_index.step | 13, 75, 104 |
| abstract_inverted_index.such | 34, 202 |
| abstract_inverted_index.test | 250 |
| abstract_inverted_index.than | 257 |
| abstract_inverted_index.this | 51 |
| abstract_inverted_index.wind | 56, 81, 112, 115, 120, 129, 135, 140, 183 |
| abstract_inverted_index.with | 106, 158, 182, 199, 231, 260 |
| abstract_inverted_index.(GEP) | 6 |
| abstract_inverted_index.(HBA) | 198 |
| abstract_inverted_index.2.72, | 273 |
| abstract_inverted_index.3.4%, | 276 |
| abstract_inverted_index.Also, | 192 |
| abstract_inverted_index.Egypt | 96 |
| abstract_inverted_index.Honey | 195 |
| abstract_inverted_index.Hydro | 152 |
| abstract_inverted_index.Shark | 100 |
| abstract_inverted_index.Then, | 128 |
| abstract_inverted_index.costs | 181 |
| abstract_inverted_index.curve | 137 |
| abstract_inverted_index.deals | 105 |
| abstract_inverted_index.first | 74 |
| abstract_inverted_index.grid, | 24 |
| abstract_inverted_index.makes | 40 |
| abstract_inverted_index.model | 39, 200 |
| abstract_inverted_index.novel | 194 |
| abstract_inverted_index.other | 232 |
| abstract_inverted_index.power | 23, 130, 136 |
| abstract_inverted_index.short | 172 |
| abstract_inverted_index.site. | 113 |
| abstract_inverted_index.sites | 94 |
| abstract_inverted_index.speed | 116 |
| abstract_inverted_index.total | 180 |
| abstract_inverted_index.turns | 7 |
| abstract_inverted_index.under | 26 |
| abstract_inverted_index.Badger | 196 |
| abstract_inverted_index.Factor | 208 |
| abstract_inverted_index.Robust | 1 |
| abstract_inverted_index.and/or | 150 |
| abstract_inverted_index.annual | 85 |
| abstract_inverted_index.better | 256 |
| abstract_inverted_index.credit | 90 |
| abstract_inverted_index.energy | 17, 28, 57, 184 |
| abstract_inverted_index.ensure | 235 |
| abstract_inverted_index.impact | 78 |
| abstract_inverted_index.model. | 72 |
| abstract_inverted_index.modern | 22 |
| abstract_inverted_index.paper, | 52 |
| abstract_inverted_index.second | 103 |
| abstract_inverted_index.stages | 170 |
| abstract_inverted_index.system | 19 |
| abstract_inverted_index.Initial | 215 |
| abstract_inverted_index.Mapping | 205 |
| abstract_inverted_index.Penalty | 207 |
| abstract_inverted_index.Storage | 153 |
| abstract_inverted_index.Turbine | 149 |
| abstract_inverted_index.Virtual | 204 |
| abstract_inverted_index.crucial | 12 |
| abstract_inverted_index.modeled | 123 |
| abstract_inverted_index.others, | 259 |
| abstract_inverted_index.ranging | 269 |
| abstract_inverted_index.results | 228, 246 |
| abstract_inverted_index.solving | 221 |
| abstract_inverted_index.through | 83 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Modified | 212 |
| abstract_inverted_index.Planning | 5 |
| abstract_inverted_index.Zafaranh | 98 |
| abstract_inverted_index.analysis | 162 |
| abstract_inverted_index.capacity | 89 |
| abstract_inverted_index.compared | 230 |
| abstract_inverted_index.concerns | 76 |
| abstract_inverted_index.emission | 187 |
| abstract_inverted_index.horizons | 176 |
| abstract_inverted_index.minimize | 178 |
| abstract_inverted_index.modeling | 48 |
| abstract_inverted_index.obtained | 227 |
| abstract_inverted_index.performs | 255 |
| abstract_inverted_index.planning | 175, 190 |
| abstract_inverted_index.presence | 54 |
| abstract_inverted_index.problem. | 49, 225 |
| abstract_inverted_index.proposed | 70, 223, 241, 253 |
| abstract_inverted_index.superior | 237 |
| abstract_inverted_index.systems, | 251 |
| abstract_inverted_index.utilized | 219 |
| abstract_inverted_index.According | 243 |
| abstract_inverted_index.Algorithm | 197 |
| abstract_inverted_index.Approach, | 209 |
| abstract_inverted_index.Expansion | 4 |
| abstract_inverted_index.analyzed. | 60 |
| abstract_inverted_index.efficient | 16 |
| abstract_inverted_index.estimated | 132 |
| abstract_inverted_index.function. | 127 |
| abstract_inverted_index.horizons. | 191 |
| abstract_inverted_index.long-term | 80 |
| abstract_inverted_index.reduction | 188 |
| abstract_inverted_index.renewable | 27 |
| abstract_inverted_index.Generation | 3, 217 |
| abstract_inverted_index.Population | 216 |
| abstract_inverted_index.Procedure, | 206 |
| abstract_inverted_index.Simulation | 144 |
| abstract_inverted_index.algorithms | 233 |
| abstract_inverted_index.applicable | 249 |
| abstract_inverted_index.components | 35 |
| abstract_inverted_index.especially | 25 |
| abstract_inverted_index.management | 18 |
| abstract_inverted_index.nonlinear, | 44 |
| abstract_inverted_index.percentage | 261 |
| abstract_inverted_index.performed. | 146 |
| abstract_inverted_index.reductions | 262 |
| abstract_inverted_index.short-term | 64, 108, 159 |
| abstract_inverted_index.variations | 86 |
| abstract_inverted_index.El-ouinate. | 101 |
| abstract_inverted_index.Intelligent | 214 |
| abstract_inverted_index.Monte-Carlo | 143 |
| abstract_inverted_index.Sensitivity | 161 |
| abstract_inverted_index.employment. | 29 |
| abstract_inverted_index.implemented | 164 |
| abstract_inverted_index.integration | 31 |
| abstract_inverted_index.penetration | 185 |
| abstract_inverted_index.performance | 238 |
| abstract_inverted_index.probability | 125 |
| abstract_inverted_index.reliability | 2 |
| abstract_inverted_index.uncertainty | 58, 117 |
| abstract_inverted_index.distribution | 126 |
| abstract_inverted_index.incorporated | 67, 155 |
| abstract_inverted_index.large-scale, | 43 |
| abstract_inverted_index.mathematical | 47 |
| abstract_inverted_index.modifications | 201 |
| abstract_inverted_index.respectively. | 277 |
| abstract_inverted_index.uncertainties | 65, 82, 109 |
| abstract_inverted_index.mixed-variable | 46 |
| abstract_inverted_index.uncertainties. | 160 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5019940948 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I130309236 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8899999856948853 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.77117834 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |