Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration Article Swipe
Ousama M.T. Ajami
,
Rodney H.G. Tan
,
N. Mithulananthan
,
Farah Adilah Jamaludin
,
Adlan Bagus Pradana
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.prime.2024.100805
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.prime.2024.100805
Concerns over fossil fuel emissions and their hazardous effects have led to a shift away from conventional power plants and focus more on the expansion of renewable energy sources. This shift has resulted in reduced inertia and resulted in poor frequency control within electrical power systems. Hybrid Energy Storage Systems (HESS) have been proposed as an effective solution to enhance frequency stability and address the reduced inertia issue. This research evaluates three distinct control models for HESS, Incorporating Supercapacitor Energy Storage (SCES) and Battery Energy Storage Systems (BESS). To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. The performances of the three control models are evaluated based on three test scenarios incorporating uncertainties, reduced inertia, and uniform and random load disturbances. The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. Conversely, the Simultaneously Optimized Virtual Inertia And Virtual Synchronous Generator Controlled HESS (SO VI-VSG-HESS) excel in mitigating small frequency fluctuations with an average improvement in frequency standard deviation of 87.65 %. The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.prime.2024.100805
- OA Status
- gold
- Cited By
- 7
- References
- 42
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403096720Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.prime.2024.100805Digital Object Identifier
- Title
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Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetrationWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-10-03Full publication date if available
- Authors
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Ousama M.T. Ajami, Rodney H.G. Tan, N. Mithulananthan, Farah Adilah Jamaludin, Adlan Bagus PradanaList of authors in order
- Landing page
-
https://doi.org/10.1016/j.prime.2024.100805Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.prime.2024.100805Direct OA link when available
- Concepts
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Penetration (warfare), Frequency regulation, Control theory (sociology), Electric power system, Optimal control, Computer science, Power (physics), Control (management), Mathematical optimization, Engineering, Mathematics, Physics, Operations research, Artificial intelligence, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
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2025: 7Per-year citation counts (last 5 years)
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42Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.have | 9, 51 |
| abstract_inverted_index.load | 157 |
| abstract_inverted_index.more | 21 |
| abstract_inverted_index.over | 1 |
| abstract_inverted_index.poor | 39 |
| abstract_inverted_index.sets | 99 |
| abstract_inverted_index.test | 147 |
| abstract_inverted_index.that | 162 |
| abstract_inverted_index.time | 176 |
| abstract_inverted_index.with | 93, 102, 127, 186, 212, 238, 246 |
| abstract_inverted_index.(VSG) | 121 |
| abstract_inverted_index.87.65 | 221 |
| abstract_inverted_index.HESS, | 76 |
| abstract_inverted_index.based | 144 |
| abstract_inverted_index.excel | 206 |
| abstract_inverted_index.focus | 20 |
| abstract_inverted_index.least | 181 |
| abstract_inverted_index.nadir | 185 |
| abstract_inverted_index.power | 17, 44 |
| abstract_inverted_index.shift | 13, 30 |
| abstract_inverted_index.small | 209 |
| abstract_inverted_index.their | 6 |
| abstract_inverted_index.three | 71, 110, 139, 146 |
| abstract_inverted_index.time. | 252 |
| abstract_inverted_index.(HESS) | 50 |
| abstract_inverted_index.(SCES) | 81 |
| abstract_inverted_index.Energy | 47, 79, 84 |
| abstract_inverted_index.Hybrid | 46 |
| abstract_inverted_index.energy | 27 |
| abstract_inverted_index.fossil | 2 |
| abstract_inverted_index.issue. | 67 |
| abstract_inverted_index.models | 74, 112, 141 |
| abstract_inverted_index.nadir, | 237 |
| abstract_inverted_index.offers | 179 |
| abstract_inverted_index.plants | 18 |
| abstract_inverted_index.random | 156 |
| abstract_inverted_index.slight | 248 |
| abstract_inverted_index.within | 42 |
| abstract_inverted_index.(BESS). | 87 |
| abstract_inverted_index.Battery | 83 |
| abstract_inverted_index.Inertia | 124, 197 |
| abstract_inverted_index.Storage | 48, 80, 85 |
| abstract_inverted_index.Systems | 49, 86 |
| abstract_inverted_index.Virtual | 118, 123, 166, 196, 199, 226 |
| abstract_inverted_index.address | 63 |
| abstract_inverted_index.average | 188, 214, 240 |
| abstract_inverted_index.control | 41, 73, 91, 111, 126, 133, 140 |
| abstract_inverted_index.effects | 8 |
| abstract_inverted_index.enhance | 59 |
| abstract_inverted_index.inertia | 35, 66 |
| abstract_inverted_index.reduced | 34, 65, 151 |
| abstract_inverted_index.uniform | 154 |
| abstract_inverted_index.Concerns | 0 |
| abstract_inverted_index.achieves | 172 |
| abstract_inverted_index.distinct | 72 |
| abstract_inverted_index.findings | 160 |
| abstract_inverted_index.increase | 249 |
| abstract_inverted_index.indicate | 161 |
| abstract_inverted_index.inertia, | 152 |
| abstract_inverted_index.optimize | 89 |
| abstract_inverted_index.possible | 98 |
| abstract_inverted_index.proposed | 53 |
| abstract_inverted_index.provides | 233 |
| abstract_inverted_index.research | 69 |
| abstract_inverted_index.resulted | 32, 37 |
| abstract_inverted_index.settling | 175, 251 |
| abstract_inverted_index.solution | 57 |
| abstract_inverted_index.sources. | 28 |
| abstract_inverted_index.standard | 218 |
| abstract_inverted_index.studied. | 108 |
| abstract_inverted_index.systems. | 45 |
| abstract_inverted_index.Generator | 120, 168, 201, 228 |
| abstract_inverted_index.Optimized | 165, 195, 225 |
| abstract_inverted_index.VSG-HESS) | 171, 232 |
| abstract_inverted_index.deviation | 219 |
| abstract_inverted_index.different | 104 |
| abstract_inverted_index.effective | 56 |
| abstract_inverted_index.emissions | 4 |
| abstract_inverted_index.evaluated | 143 |
| abstract_inverted_index.evaluates | 70 |
| abstract_inverted_index.expansion | 24 |
| abstract_inverted_index.frequency | 40, 60, 184, 210, 217, 236 |
| abstract_inverted_index.hazardous | 7 |
| abstract_inverted_index.renewable | 26 |
| abstract_inverted_index.scenarios | 148 |
| abstract_inverted_index.stability | 61 |
| abstract_inverted_index.Controlled | 202, 229 |
| abstract_inverted_index.algorithms | 106 |
| abstract_inverted_index.considered | 113 |
| abstract_inverted_index.electrical | 43 |
| abstract_inverted_index.mitigating | 208 |
| abstract_inverted_index.objectives | 101 |
| abstract_inverted_index.parameters | 92 |
| abstract_inverted_index.Conversely, | 192 |
| abstract_inverted_index.Synchronous | 119, 167, 200, 227 |
| abstract_inverted_index.improvement | 182, 215, 241 |
| abstract_inverted_index.incorporate | 117 |
| abstract_inverted_index.independent | 128 |
| abstract_inverted_index.objectives, | 96 |
| abstract_inverted_index.parameters. | 134 |
| abstract_inverted_index.VI-VSG-HESS) | 205 |
| abstract_inverted_index.conventional | 16 |
| abstract_inverted_index.fluctuations | 211 |
| abstract_inverted_index.optimization | 105, 131 |
| abstract_inverted_index.performances | 136 |
| abstract_inverted_index.simultaneous | 130 |
| abstract_inverted_index.Incorporating | 77 |
| abstract_inverted_index.Independently | 164 |
| abstract_inverted_index.disturbances. | 158 |
| abstract_inverted_index.incorporating | 149 |
| abstract_inverted_index.Simultaneously | 194, 224 |
| abstract_inverted_index.Supercapacitor | 78 |
| abstract_inverted_index.uncertainties, | 150 |
| abstract_inverted_index.post-contingency | 177 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.6800000071525574 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.87321599 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |