A Review of Energy Modeling Tools for Energy Efficiency in Smart Cities
Abstract
:1. Introduction
2. Smart City Concept and Energy Efficiency
3. Methodology
- Optimization tools: include the design optimization of endogenous systems;
- Simulation tools: provide the simulation of exogenously defined energy systems;
- Equilibrium tools or models: incorporate a larger econometric model of the society.
- Ability to evaluate each alternative in absolute terms, and not just in comparison with others;
- Independence from scales, to allow the inclusion of impacts measured in different units and even impacts measured in qualitative terms.
- Choice, to select the “best” alternative or a reduced set of “best” alternatives;
- Ranking, to rank the alternatives from the “best” one to the “worst” one;
- Sorting, to distribute alternatives into predefined categories.
- (1)
- A quarter (25%) of the total weight of the kj would be allocated according to the criterion that the tool allows analyzing energy efficiency as a result (g6), as the final use of the tool will be to model the contribution of energy efficiency for an energy system.
- (2)
- For the same reason, but with less importance, it was considered that 15% would be the weight for the evaluation criterion concerning the tools that allow analyzing the impact of demand response measures (g4).
- (3)
- Below the average, a weight of 10% was considered for the criterion that assessed whether the tool is paid or not (g5), as it will always be important to assess the initial costs for such academic exercise.
- (4)
- As a less important criterion, the criterion with geographic coverage was considered, which would be 1/5 of the criterion with the greatest weight, 5% (g2). This decision is supported by the previous analysis of the available tools, which practically all cover a city geographic scenario.
- (5)
- The remaining criteria were given the average remaining value of 9%, as they have the same relative importance.
4. Results
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Tool | Download Information | |
---|---|---|
Weblink | Availability | |
Calliope | [112] | Open-source |
DER-CAM | [113] | Free to download |
EnergyPLAN | [114] | Free to download |
energyPRO | [115] | Commercial |
Ficus | [116] | Open-source |
HOMER Pro | [117] | Commercial |
LEAP | [118] | Commercial/free for developing countries and students |
MESSAGEix | [119] | Open-source |
oemof | [120] | Open-source |
RETScreen | [121] | Free to download |
Temoa | [122] | Open-source |
TIMES | [123] | Commercial |
TRNSYS16 | [124] | Commercial |
Urbs | [125] | Open-source |
Criteria | Information | |
---|---|---|
Scales | Definition | |
temporal resolution (g1) | 1 to 3 | The tool allows simulating minutes (1), hours (2), or years (3). |
geographic coverage (g2) | 1 to 4 | The tool allows simulating at the city level (1), regional level (2), national level (3), continental or international level (4). |
sectoral coverage (g3) | 1 to 4 | The smallest number of sectors covered by the tool, both on the supply and demand side, up to a maximum of 4 sectors. For example, if a tool covers 5 sectors on the supply side and only 2 on the demand side, it should have (2). |
demand response (g4) | 0 or 1 | The tool allows analyzing demand response measures, if yes (1) and no (0). |
accessibility (g5) | 0 to 2 | The tool is paid (0), free (1), or open-source (2). |
energy efficiency (g6) | 0 or 1 | The tool allows analyzing energy efficiency as a result, if yes (1) and no (0). |
emissions (g7) | 0 or 1 | The tool allows analyzing energy emissions as a result, if yes (1) and no (0). |
financial (g8) | 0 or 1 | The tool allows analyzing investments as a result, if yes (1) and no (0). |
social (g9) | 0 or 1 | The tool allows analyzing social impact as a result, if yes (1) and no (0). |
kj | g1 | g2 | g3 | g4 | g5 | g6 | g7 | g8 | g9 |
---|---|---|---|---|---|---|---|---|---|
Weight | 9% | 5% | 9% | 15% | 10% | 25% | 9% | 9% | 9% |
Tool | g1 | g2 | g3 | g4 | g5 | g6 | g7 | g8 | g9 |
---|---|---|---|---|---|---|---|---|---|
Calliope | 3 | 4 | 4 | 1 | 2 | 0 | 0 | 1 | 0 |
DER-CAM | 3 | 1 | 4 | 1 | 1 | 0 | 0 | 1 | 0 |
EnergyPLAN | 2 | 4 | 3 | 0 | 1 | 1 | 1 | 1 | 1 |
energyPRO | 1 | 2 | 3 | 0 | 0 | 0 | 0 | 1 | 0 |
Ficus | 1 | 3 | 4 | 0 | 2 | 0 | 0 | 1 | 0 |
HOMER Pro | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |
LEAP | 3 | 3 | 4 | 1 | 1 | 1 | 1 | 1 | 1 |
MESSAGEix | 3 | 4 | 4 | 1 | 2 | 1 | 1 | 1 | 1 |
oemof | 3 | 4 | 4 | 1 | 2 | 1 | 1 | 1 | 1 |
RETScreen | 3 | 4 | 3 | 0 | 1 | 1 | 1 | 1 | 1 |
Temoa | 3 | 4 | 4 | 0 | 2 | 0 | 0 | 1 | 0 |
TIMES | 3 | 4 | 4 | 0 | 0 | 0 | 0 | 1 | 0 |
TRNSYS16 | 1 | 2 | 2 | 0 | 0 | 0 | 1 | 1 | 0 |
Urbs | 3 | 3 | 4 | 1 | 2 | 0 | 1 | 1 | 0 |
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Martins, F.; Patrão, C.; Moura, P.; de Almeida, A.T. A Review of Energy Modeling Tools for Energy Efficiency in Smart Cities. Smart Cities 2021, 4, 1420-1436. https://doi.org/10.3390/smartcities4040075
Martins F, Patrão C, Moura P, de Almeida AT. A Review of Energy Modeling Tools for Energy Efficiency in Smart Cities. Smart Cities. 2021; 4(4):1420-1436. https://doi.org/10.3390/smartcities4040075
Chicago/Turabian StyleMartins, Fernando, Carlos Patrão, Pedro Moura, and Aníbal T. de Almeida. 2021. "A Review of Energy Modeling Tools for Energy Efficiency in Smart Cities" Smart Cities 4, no. 4: 1420-1436. https://doi.org/10.3390/smartcities4040075
APA StyleMartins, F., Patrão, C., Moura, P., & de Almeida, A. T. (2021). A Review of Energy Modeling Tools for Energy Efficiency in Smart Cities. Smart Cities, 4(4), 1420-1436. https://doi.org/10.3390/smartcities4040075