Moving Toward the Expansion of Energy Storage Systems in Renewable Energy Systems—A Techno-Institutional Investigation with Artificial Intelligence Consideration
Abstract
:1. Introduction
2. Methodology
- This method reveals where the business is headed in terms of change, allowing us to adjust our strategy to accommodate the change instead of fighting it.
- Using this tool, we can analyze risks in the environment, helping us avoid launching projects that are likely to fail.
- We can develop a long-term strategy that is more effective.
3. Current Storage Technologies for Renewable Energy
3.1. (PHES)
3.2. Battery Energy Storage Technologies
3.3. Compressed Air Energy Storage (CAES)
3.4. Thermal Energy Storage (TES)
3.5. Hydrogen Storage
4. Analyses of ESS Based on PEST Analyses
4.1. Why the Role of PEST in the Development of ESS Is Important?
4.1.1. Importance of the Expansion of Energy Storage Systems for Policymakers
4.1.2. Energy Storage Systems Expansion from the Economic Point of View
4.1.3. Socio-Cultural Perspectives on Energy Storage Systems
4.1.4. Energy Storage Systems Expansion from a Technology Point of View
4.2. Causes and Barriers to Implement ESS
4.3. Comparison of the Current Study with Other Relevant Studies from the Point of View of PEST Analysis
4.4. The Role of AI in the Development of ESS
5. Important Findings and Suggestions
6. Future Works
- -
- Detailed analysis of different regions: The present work actually affects the political, economic, socio-cultural, and technological factors affecting energy storage systems. The aim of the present work is to provide a comprehensive overview. However, it is possible to examine more specific case examples that show how each factor affects energy savings in different contexts. This could include examining regulatory frameworks, market dynamics, and community engagement strategies in greater depth.
- -
- Alternative perspectives on energy storage systems: It is acknowledged that considering energy storage from different angles can yield valuable insights. In future reviews, we can include discussions on innovative business models, the role of decentralized energy storage solutions, and the impact of consumer behavior on energy conservation. In addition, environmental impact studies and life cycle assessments of different storage technologies can provide a more comprehensive understanding of their benefits and challenges.
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviation
AI | Artificial intelligence |
BEV | Battery-powered EVs |
BMS | Building management systems |
CAES | Compressed air energy storage |
ES | Energy storage |
ESS | Energy storage systems |
FCEV | Fuel cell EVs |
GHG | Greenhouse gas |
HBEV | Plug-in hybrid EVs |
HESSs | Hybrid energy storage systems |
HEV | Hybrid EVs |
IRENA | International Renewable Energy Agency |
LCOE | Levelized cost of electricity |
LIBs | Lithium-ion batteries |
PEST | Political, economic, socio-cultural, and technological |
PEV | Photovoltaic EVs |
PHS | Pumped hydroelectric storage |
RE | Renewable energy |
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No | Country | System Under Study | LCOE (USD/kWh) | References |
---|---|---|---|---|
1 | China | PV–Diesel Generator | 0.22–0.35 | [59] |
PV–Wind | 0.877–3.31 | [60] | ||
PV–Wind–Grid | 0.069–0.508 | [61] | ||
PV–Wind | - | [62] | ||
Wind | - | [63] | ||
PV | - | |||
2 | India | PV–Wind–Biogas–Fuel cell | 0.214 | [64] |
PV–Wind–Hydro–Diesel | 0.1–0.162 | [65] | ||
Generator | - | [66] | ||
Hydro | - | [67] | ||
PV–Grid | ||||
3 | United States | PV | 0.78–1.07 | [68] |
PV–Grid | 0.5–1.35 | [69] | ||
Evaluating of Pumped Storage | - | [70] | ||
4 | Indonesia | PV–Diesel Generator | 0.163 | [71] |
PV–Grid | 1.03–1.05 | [72] | ||
PV–Wind–Diesel Generator | 0.17–0.2 | [73] | ||
PV–Wind | 0.0362 | [74] | ||
5 | Pakistan | PV–Diesel Generator | 0.145–0.167 | [75] |
PV–Grid–Diesel Generator | 0.072–0.078 | [76] | ||
CHP (PV–Wind–Fuel Cell) | 0.934–0.974 | [77] | ||
PV–Wind–Hydro–Diesel Generator | - | |||
6 | Brazil | PV–Wind | 0.266–0.437 | [78] |
PV–Grid | 0.33 | [79] | ||
PV | - | [80] | ||
Hydro | - | [81] | ||
7 | Nigeria | PV | 0.312 | [82] |
PV–Wind–Diesel Cenerator | 0.138–0.212 | [83] | ||
Grid | - | [84] | ||
Hydro | - | [85] | ||
8 | Russia | PV–Wind–Diesel Generator | 0.24–0.71 | [86] |
PV–Wind–Biomass | 0.18–0.28 | [87] | ||
Hydro | - | [88] | ||
9 | Mexico | PV–Diesel Generator | 0.14 | [89] |
PV–Diesel Generator | 0.205–0.229 | [90] | ||
PV–Wind–Geothermal | - | [91] | ||
10 | Japan | PV–Wind–Diesel Generator | 0.249–0.526 | [92] |
PV–Wind | - | [93] | ||
PV–Wind | 0.086–0.110 | [94] |
Country | Role of AI in Renewable Energy |
---|---|
United States | AI is used for predictive maintenance, optimizing grid operations, and enhancing energy storage systems [192]. |
China | AI aids in forecasting energy production, managing large-scale solar and wind farms, and improving energy efficiency [193]. |
Germany | AI supports the integration of renewable energy into the grid, optimizing energy distribution, and reducing carbon emissions [194]. |
UK | Al is effective in enhancing energy efficiency in residential buildings [195] |
Brazil | The role of AI in enabling strategic hydropower planning across the Amazon basin for achieving sustainable hydropower [196] |
Australia | AI is used to optimize solar and wind energy production, manage energy storage, and improve grid reliability [197] |
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Razmjoo, A.; Ghazanfari, A.; Østergaard, P.A.; Jahangiri, M.; Sumper, A.; Ahmadzadeh, S.; Eslamipoor, R. Moving Toward the Expansion of Energy Storage Systems in Renewable Energy Systems—A Techno-Institutional Investigation with Artificial Intelligence Consideration. Sustainability 2024, 16, 9926. https://doi.org/10.3390/su16229926
Razmjoo A, Ghazanfari A, Østergaard PA, Jahangiri M, Sumper A, Ahmadzadeh S, Eslamipoor R. Moving Toward the Expansion of Energy Storage Systems in Renewable Energy Systems—A Techno-Institutional Investigation with Artificial Intelligence Consideration. Sustainability. 2024; 16(22):9926. https://doi.org/10.3390/su16229926
Chicago/Turabian StyleRazmjoo, Armin, Arezoo Ghazanfari, Poul Alberg Østergaard, Mehdi Jahangiri, Andreas Sumper, Sahar Ahmadzadeh, and Reza Eslamipoor. 2024. "Moving Toward the Expansion of Energy Storage Systems in Renewable Energy Systems—A Techno-Institutional Investigation with Artificial Intelligence Consideration" Sustainability 16, no. 22: 9926. https://doi.org/10.3390/su16229926
APA StyleRazmjoo, A., Ghazanfari, A., Østergaard, P. A., Jahangiri, M., Sumper, A., Ahmadzadeh, S., & Eslamipoor, R. (2024). Moving Toward the Expansion of Energy Storage Systems in Renewable Energy Systems—A Techno-Institutional Investigation with Artificial Intelligence Consideration. Sustainability, 16(22), 9926. https://doi.org/10.3390/su16229926