Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1
Abstract
:1. Introduction
1.1. Framework and Concept
1.2. Previous Literature
1.3. Ambition and Contribution to Research
- What are the predominantly proposed technical integration pathways of hydrogen for electrification and clean cooking and respective energy-system topologies?
- What are the current challenges impairing studies on the use of hydrogen in electrification or clean cooking?
- What are potential chances for the market entry of hydrogen in the Global South?
- What are the lessons learned and the way forward for studies of hydrogen application in contributing to SDG 7.1?
- Which research methods have been used in the field, and did they change over time?
2. Materials and Methods
2.1. Search
2.2. Appraisal
- Search string: Papers were only considered when including the predefined keywords as a whole or at least in combination in title, keywords, or abstract.
- Type of paper: Only original research papers were considered. This essentially excluded reviews, patent analyses, book chapters, and proceedings.
- Language: Only papers written in English were considered.
- Year: To limit the scope of the databank search, we filtered for papers published (print version) from the beginning of the SDG period in 2015 until July 2022 (31 June 2022).
- Geopolitical scope: Given the hotspots of deficit in SDG 7.1.1 and SDG 7.1.2 identified by the most recent SDG 7 progress report [6], we only consider papers essentially focusing on countries in the Global South. Notably, the term Global South is more than a geographical denotation of a geographical region. The terminus rather focuses on geopolitical relations of power, therefore essentially excluding regions in Europe and North America, but broadly including the regions of Latin America, Asia, Africa, and Oceania [31]. We relied on the United Nations’ Finance Center for South–South Cooperation´s list of countries accounting for the Global South [32]. As of 2022, the list comprises 78 countries (including China).
- Rationale: Articles included in our review had to be in alignment with the rationale of SDG 7.1.1 or SDG 7.1.2. This implies that the articles present work that directly contributes to increasing the share of people having access to electricity or clean cooking, respectively, on a household level. Notably, this excludes applications providing energy services to buildings or infrastructure, which that do not primarily serve as housing for people. Examples are telecommunication stations [33], public buildings [34], or hospitals [35]. Articles proposing an alternative energy supply to an existing, reliable, and clean status quo, such as modernization of energy services for urban buildings [36], were excluded. Further, mobility applications do not meet the rationale of SDG 7.1.
- Specificity: Our review only includes articles that specifically address the utilization of hydrogen at the end-use. This excludes work that focuses on the production of hydrogen but insufficiently describes the foreseen utilization (e.g., [37]), and work introducing hydrogen as a broad concept only (i.e., the concept of a “hydrogen economy” such as in [38]).
- Renewable hydrogen: SDG 7.1.1 does not specify the source of electricity supply to increase the share of the population with access to electricity. McCollum et al. [1] thereby detected negative correlations between targets and indicators of SDG 7, e.g., when electrification is enhanced via diesel generators (DGs). However, to not harm other targets of the SDGs, especially SDG 7.2 (increase the share of renewables), we only considered renewable hydrogen as eligible for our review. We further only considered the utilization of hydrogen in its pure form, but not hydrogen-rich fuels such as biomethane.
2.3. Synthesis
- Geospatial information system (GIS) model: Formalized representation of a real system that attempts to emulate combined processes of acquiring and using energy to satisfy the energy demands of a given area over an extended period of time [41].
- Life-cycle assessment (LCA): Assessment of the environmental impact (e.g., damages to human health, ecosystems, or resources) through all the life-cycle stages of an energy system or energy technology [42].
- Experiment: The setup of a physical experiment, i.e., manipulation of variables to establish cause-and-effect relationships.
- Optimization model: A mathematical attempt to determine the maximum or minimum value of a complex objective function that serves as a definite recommendation for the energy system.
- Simulation model: A mathematical attempt to determine an energy system´s response to different inputs, while—in contrast to optimization—not defining a clear recommendation.
- Multi-criteria decision analysis (MCDA): MCDA is an operational evaluation and decision-support approach comparing the performance of various energy system or energy technology options along multiple criteria. In contrast to the multi-objective optimization included in the method category “optimization model,” the MCDA method may include qualitative aspects, such as risks, available human resources, or political drivers [42].
- Rigorous analysis: A procedure or test following a strict methodology but not included in the above-mentioned methods.
- Environmental dimension: This dimension includes environmental impacts on the local or aggregated level. We further include effects on human health in this dimension [45].
- Economic dimension: The economic dimension covers any economic assessment on the individual, system, or aggregated level.
- Social dimension: This dimension covers the impact on, or interaction with, people, including societal structures and ethical aspects.
2.4. Analysis
3. Results and Discussion
3.1. Technical Integration in Energy Systems
- Setting specific variables: Load demand; seasonality influences towards load and supply.
- Economic parameters: Project parameters including weighted average cost of capital (WACC), investment costs, operation and maintenance costs, replacement costs, fuel costs.
- Availability of resources: Grid availability for interconnection, availability of renewable energy sources, availability of fossil fuels.
- System configuration: Technology availability, control algorithm, technology configuration.
- Environmental constraints: Renewable energy share, maximum emissions.
- Technical constraints: Loss of power supply probability, energy shortage, energy excess.
- (A)
- Off-grid power supply:
- (B)
- Separate power supply and hydrogen cooking via combustion
- The higher hydrogen-air flame temperature allows for quick and flexible heating.
- The high diffusion coefficient is a great safety advantage.
- Hydrogen can be ignited within a wide flammability range with low ignition energy required.
- Hydrogen has a high (gravimetric) energy density, offering great potential for storage and transport.
Property | Unit | Hydrogen (H2) | Propane (C3H8) | Methane (CH4) |
---|---|---|---|---|
Molecular weight | u | 2.01594 [59] | 44.1 | 16.4 |
Gravimetric energy content | MJ/kg | 120 [60] | 46.4 [60] | 50 [60] |
Higher heating value (HHV) | MJ/Nm3 (MJ/l Propane) | 12.75 [61] | 26.5 [62] | 39.82 [61] |
Flammability range (Equivalence ratio) | 0.1 ∼ 7.1 [60] | 0.51 ∼ 2.5 [60] | 0.5 ∼ 1.7 [60] | |
Max. laminar burning velocity | m/s | 2.91 [60] | 0.43 [60] | 0.37 [60] |
Adiabatic flame temperature in air | °C | 2.110 [60] | 2.000 [60] | 1.950 [60] |
Diffusion coefficient in air | Cm2/s | 0.61 [59] | 0.1318 | 0.221 |
Minimum auto ignition temperature | °C | 520 [60] | 450 [60] | 630 [60] |
3.2. Economic Prospective
3.3. Environmental Performance
3.4. Social Considerations
4. Concluding Remarks
Source | Year | Study Location | Methods | Software | Dimensions of Sustainability | Highlights | System Description |
---|---|---|---|---|---|---|---|
[84] | 2012 | Cuba |
|
|
|
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[89] | 2013 | Cuba |
|
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|
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[70] | 2013 | Brazil |
|
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|
|
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[95] * | 2014 | Iran |
|
|
|
|
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[71] | 2015 | Gulf of Guinea |
| Odyssey (CEA) |
|
|
|
[96] | 2015 | India |
|
|
|
|
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[73] | 2016 | Ethiopia |
|
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|
|
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[53] * | 2016 | Iran |
|
|
|
|
|
[97] | 2017 | India |
| HOMER |
|
|
|
[98] | 2017 | Malaysia |
| HOMER |
|
|
|
[99] | 2018 | United Arab Emirates |
| Not mentioned. |
|
|
|
[54] * | 2018 | Ethiopia |
| HOMER |
|
|
|
[100] | 2018 | Ecuador |
|
System Optimization: HOMER |
|
|
|
[52] * | 2018 | South Africa |
|
|
|
|
|
[74] | 2019 | Iran | Optimization |
|
|
|
|
[101] | 2019 | Iran |
| HOMER |
|
|
|
[102] | 2019 | Iran |
| HOMER |
|
|
|
[103] | 2019 | Egypt |
| MATLAB |
|
|
|
[104] | 2020 | Archetype rural community in sub-Saharan Africa |
| MATLAB |
|
|
|
[105] | 2020 | Saudi Arabia |
| HOMER |
|
|
|
[75] | 2021 | Tanzania |
| MATLAB |
|
|
|
[106] | 2021 | Iran | Optimization | MATLAB |
|
|
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[107] | 2021 | India |
| HOMER |
|
|
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[108] | 2021 | Iran |
|
|
|
|
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[109] | 2021 | Brazil | Experiment | / | Technical |
|
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[72] | 2021 | Tibet/China |
| MATLAB |
|
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[94] | 2021 | Unspecified Africa, Middle east, Asia | Rigorous analysis | MATLAB | Technical |
|
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[50] | 2022 | Nigeria |
| HOMER |
|
|
|
Source | Year | Study Location | Methods | Software | Dimensions of Sustainability | Highlights | System Description |
---|---|---|---|---|---|---|---|
[49] | 2020 | Iran |
|
|
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[46] | 2021 | Nepal | Rigorous analysis | Not mentioned |
|
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[47] | 2021 | Nigeria |
|
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|
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Source | Year | Study Location | Methods | Software | Dimensions of Sustainability | Highlights | System Description |
---|---|---|---|---|---|---|---|
[57] | 2007 | Bhutan |
| Not mentioned |
|
|
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[58] | 2015 | Jamaica |
| TRYNSYS |
|
|
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[48] | 2016 | Ecuador |
| Not specified |
|
|
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[66] | 2016 |
|
| TRYNSYS |
|
|
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[77] | 2018 | Jamaica | LCA | GaBi V6.110 | Environmental |
|
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[63] | 2017 | India |
| Aspen Plus |
|
|
|
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
Abbreviation | |
AEL | Alkaline electrolysis |
AFC | Alkaline fuel cell |
AEMEL | Anion exchange membrane electrolysis |
BAT | Battery |
BG | Biogas |
CAPEX | Capital expenditure |
CHP | Combined heat and power |
DG | Diesel generator |
EL | Electrolysis |
FC | Fuel cell |
GIS | Geospatial information system |
HECRAS | Hydrologic Engineering Center’s River Analysis System |
HKT | Hydrokinetic turbine |
HOGA | Hybrid Optimization by Genetic Algorithms |
HOMER | Hybrid Optimization of Multiple Energy Resources |
H2 | Hydrogen |
LCA | Life-cycle assessment |
LCOE | Levelized costs of electricity |
MCDA | Multi-criteria decision analysis |
OPEX | Operational expenditure |
PAFC | Phosphoric acid fuel cell |
PV | Photovoltaic |
PEMEL | Polymer membrane exchange electrolysis |
PEMFC | Polymer membrane exchange fuel cell |
PGM | Platinum group metals |
PRISMA | Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
P2H2P | Power-to-hydrogen-to-power |
rSOC | Reversible solid oxide fuel cell |
SASA | Search, Appraisal, Synthesis, and Analysis |
SDG | Sustainable Development Goal |
SOEL | Solid oxide electrolysis |
SOFC | Solid oxide fuel cell |
SSA | Sub-Saharan Africa |
WT | Wind turbine |
Appendix A
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Parameter | Unit | AEL | AEMEL | PEMEL | SOEL |
---|---|---|---|---|---|
Electrolyte | / | 10–30% KOH | Quaternary ammonia polysulfide or dilute caustic solution [14] | Perfluoro sulfonic acid | Ionic conductor consisting of ZrO2 doped with 8 mol % Y2O3 [14] |
Anode reaction [13] | / | 2OH− → ½ O2 + H2O + 2e− | 4OH− → 2H2O + O2 + 4e− | H2O → ½ O2 + 2H+ + 2e− | H2O + 2e− → H2 + O2− |
Cathode reaction [13] | / | 2H2O + 2e− → H2 + 2OH− | 4H2O + 4e− → 2H2 + 4OH− | 2H+ + 2e− → H2 | O2− → ½ O2 + 2e− |
Operating temperature | °C | 70–90 | 40–60 | 50–80 | 700–900 |
Operating pressure | bar | <30 | <35 | <70 | <10 |
Catalyst material [15] | / | Ni-coated perforated stainless steel | High surface area nickel or NiFeCo alloys | Platinum groups/Iridium oxide | Perovskite-type/Ni/YSZ |
Efficiency 1 (System, LHV) | % | 51–60 | 70–75 | 46–60 | 76–81 |
Start-up time (cold 2/warm) | / | 1–2 h 1–5 min | <20 min <<20 min | 5–10 min <10 s | Hours 15 min |
Minimum part load | % | 20 | 5 | 0–5 | / |
CAPEX | USD/kW | 500–1000 | / | 700–1400 | <2000 |
Parameter | Unit | AFC | PAFC | PEMFC | SOFC |
---|---|---|---|---|---|
Electrolyte [18] | / | 10–30% KOH solution in a matrix | Liquid phosphoric acid soaked in a matrix | Solid organic polymer Perfluoro sulfonic acid | Yttria stabilized zirconia |
Anode reaction [16] | / | H2 + 2OH− → 2H2O + 2e− | H2 → 2H+ + 2e− | H2 → 2H+ + 2e− | H2 + O2− → H2O + 2e− |
Cathode reaction [16] | / | 0.5O2 + H2O + 2e− → 2OH− | 0.5O2 + 2H+ + 2e− → H2O | 0.5O2 + 2H+ + 2e− → H2O | 0.5O2 + 2e− → O2− |
Operating temperature | °C | 60–120 | 150–220 | 50–100 | 800–1,000 |
Efficiency (System, LHV) | % | 45–60 | 40–55 | 45–65 | 35–40 |
CAPEX | USD/kW | 700–1800 | 4000–5000 | 1400–4000 | 1500–8000 |
Asset | H2 Blending Uncritical | Adjustment Needed | Further Research Required |
---|---|---|---|
Meters | <30% | 30%–70% | >70% |
CNG storage tank | <30% | 30%–50% | >50% |
House installs | <30% | 30%–50% | >50% |
Home gas burner/stove | <10% | 10%–50% | >50% |
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Schöne, N.; Heinz, B. Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1. Energies 2023, 16, 1658. https://doi.org/10.3390/en16041658
Schöne N, Heinz B. Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1. Energies. 2023; 16(4):1658. https://doi.org/10.3390/en16041658
Chicago/Turabian StyleSchöne, Nikolas, and Boris Heinz. 2023. "Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1" Energies 16, no. 4: 1658. https://doi.org/10.3390/en16041658
APA StyleSchöne, N., & Heinz, B. (2023). Semi-Systematic Literature Review on the Contribution of Hydrogen to Universal Access to Energy in the Rationale of Sustainable Development Goal Target 7.1. Energies, 16(4), 1658. https://doi.org/10.3390/en16041658