Methodology for Monitoring Sustainable Development of Isolated Microgrids in Rural Communities
2. Related Works
3. Definition of Sustainable Isolated Microgrid
- Technical sustainability: The implementation of the microgrid project must be possible with current available technologies without compromising the operation of critical elements.
- Economical sustainability: The microgrid project must be implemented so that the efficient use of the energy allows the community and the microgrid profitable functioning over time.
- Social sustainability: The microgrid project must be accepted by the community and must promote its social development and engagement.
- Environmental sustainability: The microgrid project must bring larger environmental benefits than the use of traditional electrification alternatives (e.g., only diesel-based electrification projects).
4. General Aspects for the Selection and Definition of the Indicators
4.1. Representation of Sustainability Dimensions
4.2. Requirements on the Indicators
- Be understandable by the community including those who are not experts .
- Be defined based on available data in the microgrid or information that can be gathered if necessary .
- For each indicator, it must be possible to define a lower and upper threshold in order to perform a normalization process.
5. Indicators of Sustainable Development Applied to Isolated Microgrids
5.1. Enviromental Dimension
- Greenhouse gas emission: Several gases are released into the atmosphere during the combustion process of fossil fuels due to the operation of diesel generators [1,7]. Depending on the technology used and on the fuel quality, these gases may have a direct impact on the health of the community and contribute to the greenhouse effect and global warming . Thus, monitoring such emissions helps to formulate strategies to reduce the negative effects associated with the intensive use of these energy sources.
- Noise and contamination: In addition to gas and particulate matter emissions, a microgrid project could involve the use of hazardous substances for the environment and human health (e.g., substances used in battery storage systems, biogas production, and the diesel itself) . Furthermore, the noise produced by power converters and fossil-fueled generators might threaten the health of the environment surrounding an isolated microgrid. Hence, monitoring the use of hazardous substances, levels of noise and how wastes are managed is essential for the sustainability of a microgrid project.
5.2. Social Dimension
- Equity and affordability: Equity and affordability in microgrid projects regards the coverage of electricity service in a community and the price the users must pay for such service. For a proper social development, coverage should be maximized while the price of the service must be kept at a fair level. Thus, a continuous monitoring of these variables is required as well as the definition of policies to guarantee that the aforementioned objectives are achieved .
- Community development: Community development criteria express the social progress obtained by the implementation of a microgrid project. Given a baseline (the situation of the community before implementing a microgrid), monitoring the extent to which economical activities have grown, new economic activities have appeared, the relationship among the inhabitants has strengthened, and common objectives have been achieved, provides information about the impact of the microgrid project in the community and allows defining strategies to foster its sustainability .
- Health and risks: health and risk in microgrid projects refer to the use of electricity for medical purposes. In particular, the extent to which health care has increased since the implementation of the microgrid. This includes available hours for attention, quality of service, quality of the medicines, coverage level, and the effects that these factors have in the members of the community .
- Community engagement: The community engagement in a microgrid project involves the relationship between the members of the community and the developers of the microgrid project . In particular, it concerns how the community has organized to monitor the state of the microgrid. The formation of committees in charge of the maintenance of the energy sources, of assessing the energy use, and of gathering the resources for equipment replacement are examples of community organization around a microgrid project.
5.3. Economic Dimension
- Investment: The investment is one of the most common indicators to evaluate energy systems from an economic perspective . From a sustainability viewpoint, monitoring the investment not only at the initial stage but also throughout the evolution of the project allows determining the economic viability of an isolated microgrid project. Often, the investment indicator includes expansion of the grid and increasing the capacity of the energy sources. However, the economic viability of the project should not only be evaluated in terms of economic profit. The improvement in the corporate image and other externalities that produce indirect incentives for the investment should be also included in the viability assessment.
- Operation and maintenance costs: Operation and maintenance costs involve the normal operation of the microgrid and all activities done to keep the microgrid operative . Examples of these activities are the cleaning of solar panels, the inspection of the distribution grid to identify possible sources of abnormal operation, and keeping the fuel at a level that guarantees the operation of diesel generators. The monitoring of operation and maintenance activities is part of the assessment of the economic viability of an isolated microgrid project, and allows for the definition of policies to foster its sustainability.
- Fuel costs: Fuel cost refers to the costs spent for the provision of fuel necessary for the microgrid operation. This includes transportation, storage, and the cost of the fuel itself. The monitoring of the fuel costs allows predicting its availability in the future and formulating strategies of consumption and provisioning to avoid power outages, especially during the night hours.
- Electricity costs: Electricity cost has been used as a criterion to evaluate the economic performance of energy systems from the viewpoint of consumers. In isolated microgrid projects, this value is associated with investment and operational costs. Although this value is easy to calculate, often in isolated microgrids the price paid by the customers for the electricity does not reflect its real cost. This situation arises because inhabitants of remote communities normally have little income and therefore the electricity must be subsidized. Thus, keeping a balance between investment, operation and maintenance, as well as electricity costs is necessary for the sustainability of the project.
5.4. Technical Dimension
- Efficiency: Efficiency refers to how the energy produced by the sources in a microgrid is used. Compared with bulk power systems, in general in isolated microgrid projects load centers are placed nearer the energy sources. Consequently, distribution losses are reduced. However, in isolated microgrids the energy resources are limited. Hence, a proper use of the energy by the customers must be promoted. Thereby, the monitoring of the use of electricity through the behavior of the demand (e.g., peak values, tendency, and location of peak values) is essential to guarantee the sustainability of the project from a technical viewpoint, since demand side management strategies could be designed to foster a rational use of electricity.
- Primary energy use: Primary energy is defined as a type of energy found in nature that has not been subjected to any conversion or transformation process. In isolated microgrid projects, solar radiation, wind speed, diesel, and chemical reactions are typically used as primary energies. Due to the environmental and economic costs associated with the use of diesel as primary energy source, monitoring the percentage of the demand supplied with diesel is required for sustainable development purposes. Indeed, reducing the use of diesel as primary energy source has a positive impact in economic and environmental dimensions and might foster the sustainability of the project.
- Reliability and power quality: Reliability and power quality indicators measure the vulnerability of a microgrid from a technical viewpoint. As in large power systems, frequency and voltage deviations from their desired values (nominal values) as well as the number of power outages in a predefined period of study are used to measure this indicator. Since frequency and voltage deviations as well as power outages might affect the electrical equipment within a microgrid, monitoring these variables helps to take actions to reduce their number so that economic activities and domestic equipment are not severely affected. Consequently, a positive (complimentary) effect on economic and social dimensions is envisioned.
- Microgrid management: Microgrid management regards the activities carried out by the community to keep the performance of a microgrid at a desired level. Often, the performance of a microgrid is measured by means of the quality of service provided to the customers. Therefore, fulfilling the electricity requirements of the community implies continuously monitoring the quality of service provided. From the sustainability perspective, microgrid management has a complimentary effect on social and economic dimensions. In this sense, microgrid management is an important aspect of the sustainability of the project.
5.5. Further Classification of Indicators
5.6. Methodology to Obtain the CSI
5.6.1. Normalization of the Indicators
5.6.2. Definition of Weighting Factors
5.6.3. Definition of Sub-Indexes for Each Dimension
5.6.4. Composite Sustainability Index
6. Proposed Framework for Monitoring the Sustainable Development of Microgrids
- Determination of sub-indexes and CSI
- Analysis of the temporal evolution of the sub-indexes and of the CSI
- Adaptation of the weighting factors
- Corrective measures (if needed)
7. Obtained Results
7.1. Case Study Huatacondo
- Photovoltaic (PV) plant of 23 kW with inverters.
- Diesel generator of 108 kW.
- Lead-acid battery for energy storage of 27 kW/127 kWh, BESS (acronym of battery energy storage system).
- SCADA (acronym of supervisory control and data acquisition) system for control and monitoring.
- Energy management system for optimal operation.
- Social SCADA. Computational tool located at the head office of the neighborhood council, developed to provide information in real-time to the community and stakeholders. Historical operation data of the microgrid are also available. The tool also incorporates key performance indicators to support the decision-making and management support maintenance .
7.2. Example of Application of the Methodology
7.3. Obtained Results Considering Real Data
- The events indicated as “a” are known as the Bolivian winter. This natural phenomenon occurs each year in January, which is the month of the year with increased rainfall in the region.
- The event “b” occurs every year in August. It corresponds to a Catholic Feast for the Virgin, which gathers about 400 people coming to Huatacondo during one week.
- The event “c” corresponds to an atypical situation that occurred in May 2013. It was a fault in the tracking system in one of the six sections of the PV plant, thus decreasing the PV capacity to 83% of its nominal capacity during two months.
7.4. Obtained Results Considering Corrective Measures
Conflicts of Interest
Appendix A. Environmental Indicators
|Gas Emission||CO2 emission||CO2 emissions||OI||(0–0.5) kg-CO2/kWh, data for Latin America |
|Perception about emissions||Community perception about emissions||PI||0%–100%|
|Noise and Contamination||Noise measurement||Noise level measurement||OI||(0–70) dB |
|Waste produced||Waste generated due to electricity generation compared with previous system||II||kg/kWh. Where is the existing level in the community before the microgrid.|
|Perception noise and contamination||Community perception about noise and contamination||PI||0%–100%|
Appendix B. Economic Indicators
|Investment||Investment||Investment per generation technology||OI||(500–6500) $/kW Biomass |
(1.175–6.000) $/kW Hydropower
(2.150–7.000) $/kW Solar PV
(1.900–6.040) $/kW Wind 
|Stakeholders perception about the “profits” gained through the microgrid||Profits in rural microgrids projects may not necessary be monetary. An example of other kind of “profits” is the image improvement in case of mining projects affecting a rural community||II||0%–100%|
|O & M Cost||O & M global cost||O & M global cost per kWh produced (all technologies)||II||According to the O & M cost per technology and specific technologies using by the microgrid: |
(106–112) $/kW Biomass
(21–22) $/kW Biomass cofiring
(136–144) $/kW Biomass combined heat and power (CHP) medium
(186–197) $/kW Biomass CHP small
(292–310) $/kW Biomass-waste incineration CHP
(64–68) $/kW Hydropower small scale
(34–36) $/kW Solar PV
(40–43) $/kW Wind 
(0.7) $/h Diesel, cost per hour of operation 
|Fuel Cost||Fuel cost||Fuel cost per kWh produced||OI||(0.00–0.27) $/kWh |
|Electricity Cost||Electricity cost comparison with the region||Microgrid electricity cost compared with the costs of the region||OI||(0.06–0.45) $/kWh |
|Electricity cost comparison previous system (if apply)||Comparison of microgrid electricity cost with the previous system||II||$/kWh. Where is the existing electricity cost in the community before the microgrid|
Appendix C. Social Indicators
|Equity & Affordability||Electricity expenses||Household electricity expenses||OI||(0.07–0.49) $/kWh |
|Electrification level||Household with electricity service||II||(70–90)% |
|Perceived affordability||Perceived affordability of electric service||PI||0%–100%|
|Community Development||New jobs||New direct jobs due to the microgrid||II||(0.25–6.21) jobs/MW; New jobs due to construction, manufacturing, and installation of the microgrid |
(0.27–4.80) jobs/MW O & M and fuel management 
|Development achieved perception||Community perception about development achieved due to the microgrid||PI||0%–100%|
|Health and Risk||Training in health risk||Training sessions in health risk related to the electricity||OI||(0–30) h/year |
|Improvements health perception||Perception of improvements in health due to the microgrid||PI||0%–100%|
|Community Engagement||Attendance at meetings||Attendance at meetings for community training and engagement||OI||0%–100%|
|Community O & M tasks||Community engagement in O & M tasks||II||0%–100%|
|Community perception||Community satisfaction level about the microgrid operation||PI||0%–100%|
Appendix D. Technical Indicators
|Efficiency||Distribution losses||Distribution network losses||OI||5%–15% |
|Consumption comparison||Comparison between the household average consumption with the region average||II||0%–100%|
|Capacity factor||Capacity factor per technology||PI||50%–90% Biomass |
10%–25% Solar PV
25%–40% Wind 
|Primary Energy Ratio||Ratio of generation||Ratio between renewable generation and fossil fuel||PI||(70–100)% |
|Reliability and Power Quality||Voltage deviation||Average deviation of the voltage from its nominal value during a period of time.||OI||It depends on local grid codes for low distribution systems. In Chile is .|
|Frequency deviation||Average deviation of the frequency from its nominal value during a period of time.||OI||It depends on local grid codes for low distribution systems. In Chile is .|
|Hours without energy (HWE)||HWE within the community compared to the situation before the microgrid||II||hours/month. Where are the hours per day that the community had no electricity before the microgrid (if apply)|
|Perception reliability and quality service||Community perception about reliability and quality service||PI||0%–100%|
|Microgrid Management||Compliance maintenance plan||Compliance of the maintenance plan||II||0%–100%|
|Mean time to repair (MTTR)||Mean time to repair||PI||hours/event. Where depends on the particular conditions of the microgrid. For instance, in the case of Huatacondo, the technical support of the microgrid is located in Santiago. Then, if a critical event occurs, the MTTR is, at least, the time it takes the support team to flight to Huatacondo.|
- Wang, J.-J.; Jing, Y.-Y.; Zhang, C.-F.; Zhao, J.-H. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renew. Sustain. Energy Rev. 2009, 13, 2263–2278. [Google Scholar] [CrossRef]
- Vera, I.; Langlois, L. Energy indicators for sustainable development. Energy 2007, 32, 875–882. [Google Scholar] [CrossRef]
- Word Bank. Energy Overview 2015. Available online: http://www.worldbank.org/en/topic/energy/overview (accessed on 30 October 2016).
- Martínez-Cid, R.; O’Neill-Carrillo, E. Sustainable microgrids for isolated systems. In Proceedings of the IEEE PES Transmission and Distribution Conference and Exposition, New Orleans, LA, USA, 19–22 April 2010.
- Prete, C.L.; Hobbs, B.F.; Norman, C.S.; Cano-Andrade, S.; Fuentes, A.; von Spakovsky, M.R.; Mili, L. Sustainability and reliability assessment of microgrids in a regional electricity market. Energy 2012, 41, 192–202. [Google Scholar] [CrossRef]
- Alvial-Palavicino, C.; Garrido-Echeverría, N.; Jiménez-Estévez, G.; Reyes, L.; Palma-Behnke, R. A methodology for community engagement in the introduction of renewable based smart microgrid. Energy Sustain. Dev. 2011, 15, 314–323. [Google Scholar] [CrossRef]
- Chatzimouratidis, A.I.; Pilavachi, P.A. Multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process. Energy Policy 2008, 36, 1074–1089. [Google Scholar] [CrossRef]
- Afgan, N.H.; Carvalho, M.G. Multi-criteria assessment of new and renewable energy power plants. Energy 2002, 27, 739–755. [Google Scholar] [CrossRef]
- Mamlook, R.; Akash, B.A.; Nijmeh, S. Fuzzy sets programming to perform evaluation of solar systems in Jordan. Energy Convers. Manag. 2001, 42, 1717–1726. [Google Scholar] [CrossRef]
- Meyar-naimi, H.; Vaez-zadeh, S. Sustainability Assessment of a Power Generation System Using DSR-HNS Framework. IEEE Trans. Energy Convers. 2013, 28, 327–334. [Google Scholar] [CrossRef]
- La Rovere, E.L.; Soares, J.B.; Oliveira, L.B.; Lauria, T. Sustainable expansion of electricity sector: Sustainability indicators as an instrument to support decision making. Renew. Sustain. Energy Rev. 2010, 14, 422–429. [Google Scholar] [CrossRef]
- Astier, M.; Masera, O.R.; Galván, Y. Evaluación de Sustentabilidad: Un Enfoque Dinámico y Multidimensional; Proyecto MESMIS: Valencia, España, 2008. [Google Scholar]
- Costa, P.M.; Matos, M.A. Economic Analysis of Microgrids Including Reliability Aspects. In Proceedings of the International Conference on Probabilistic Methods Applied to Power Systems, Stockholm, Sweden, 11–15 June 2006.
- Moldan, B.; Janoušková, S.; Hák, T. How to understand and measure environmental sustainability: Indicators and targets. Ecol. Indic. 2012, 17, 4–13. [Google Scholar] [CrossRef]
- United Nations. Chapter 2: Towards Sustainable Development. In Our Common Future; United Nations: Oslo, Norway, 1987. [Google Scholar]
- Lior, N. Sustainable energy development: The present situation and possible paths to the future. Energy 2008, 33, 842–857. [Google Scholar] [CrossRef]
- Nunes, B.; Alamino, R.C.; Shaw, D.; Bennett, D. Modelling sustainability performance to achieve absolute reductions in socio-ecological systems. J. Clean. Prod. 2015, 132, 32–44. [Google Scholar] [CrossRef]
- Office of Educator Preparation. OECD Environmental Indicators; Office of Educator Preparation: Paris, France, 2003. [Google Scholar]
- Global Reporting Iniative. Suatainability Reporting Guidelines; Global Reporting Iniative: Amsterdam, The Netherlands, 2013. [Google Scholar]
- United Nations Division for Sustainable Development. Indicators of Sustainable Development: Guidelines and Methodologies Indicators of Sustainable Development, 3rd ed.; United Nations: New York, NY, USA, 2007. [Google Scholar]
- Meyar-Naimi, H.; Vaez-Zadeh, S. Developing a DSR-HNS policy making framework for electric energy systems. Energy Policy 2012, 42, 616–627. [Google Scholar] [CrossRef]
- Feng, S.C.; Joung, C.B. An Overview of a Proposed Measurement Infrastructure for Sustainable Manufacturing. In Proceedings of the 7th Global Conference on Sustainable Manufacturing, Chennai, India, 2–4 December 2009.
- Kobayakawa, T.; Kandpal, T.C. Photovoltaic micro-grid in a remote village in India: Survey based identification of socio-economic and other characteristics affecting connectivity with micro-grid. Energy Sustain. Dev. 2014, 18, 28–35. [Google Scholar] [CrossRef]
- Liposcak, M.; Afgan, N.H.; Duic, N.; da Graca Carvalho, M. Sustainability assessment of cogeneration sector development in Croatia. Energy 2006, 31, 1940–1948. [Google Scholar] [CrossRef]
- Wang, J.J.; Jing, Y.Y.; Zhang, C.F.; Zhang, X.T.; Shi, G.H. Integrated evaluation of distributed triple-generation systems using improved grey incidence approach. Energy 2008, 33, 1427–1437. [Google Scholar] [CrossRef]
- Dialynas, E.; Member, S.; Hatziargyriou, N.D. Impact of Microgrids on Service Quality. In Proceedings of the Power Engineering Society General Meeting IEEE, Tampa, FL, USA, 24–28 June 2007.
- Parmenter, D. Key Performance Indicators, 2nd ed.; John Wiley and Sons: Hoboken, NJ, USA, 2010. [Google Scholar]
- Frangopoulos, C.; Keramioti, D. Multi-Criteria evaluation of energy systems with sustainability considerations. Entropy 2010, 12, 1006–1020. [Google Scholar] [CrossRef]
- Afgan, N.H.; da Graça Carvalho, M. Energy system assessment with sustainability indicators. Energy Policy 2000, 28, 603–612. [Google Scholar] [CrossRef]
- Palma-Behnke, R.; Ortiz, D.; Reyes, L.; Garrido, N. A Social SCADA Approach for a Renewable based Microgrid—The Huatacondo Project. In Proceedings of the IEEE PES Innovative Smart Grid Technologies, Washington, DC, USA, 16–18 January 2012.
- Mertz, B.; Kuijpers, L.; Solomon, S.; Andersen, S.O.; Davidson, O.; Pons, J.; de Jager, D.; Kestin, T.; Manning, M.; Meyer, L. Safeguarding the Ozone Layer and the Global Climate System: Issues Related to Hydrofluorocarbons and Perfluorocarbons; Cambridge University Press: Cambridge, UK, 2005. [Google Scholar]
- World Health Organization. 2012. Available online: http://www.who.int/docstore/peh/noise/Comnoise-4.pdf (accessed on 30 October 2016).
- Flavin, C.; Gonzalez, M.; Ochs, A.; da Rocha, M.; Tagwerker, P. Study on the Development of the Renewable Energy Market in Latin America and the Caribbean; Inter-American Development Bank: Washington, DC, USA, 2014. [Google Scholar]
- World Energy Outlook, IEA. 2015. Available online: http://www.worldenergyoutlook.org/weomodel/investmentcosts/ (accessed on 30 October 2016).
- Bartolini, M.; Gamberi, M.; Graziani, A.; Pilati, F. Economic and environmental bi-objective design of an off-grid photovoltaic–battery–diesel generator hybrid energy system. Energy Convers. Manag. Rev. 2015, 106, 1024–1038. [Google Scholar] [CrossRef]
- Yepez-Garcia, R.A.; Johnson, T.M.; Andrés, L.A. Meeting the Electricity Supply/Demand Balance in Latin America & the Caribbean; World Bank: Washington, DC, USA, 2010. [Google Scholar]
- Canese, M. La tarifa social de la energía América Latina y el Caribe; Organización Latinoamericana de Energía: Quito, Ecuador, 2013. [Google Scholar]
- Wei, M.; Patadia, S.; Kammen, D.M. Putting renewables and energy efficiency to work: How many jobs can the clean energy industry generate in the US? Energy Policy 2010, 38, 919–931. [Google Scholar] [CrossRef]
- OSHA Recommendations. Available online: https://www.osha.gov (accessed on 30 October 2016).
|Social||Electrification level||Household with electricity service in Huatacondo||%|
|Technical||Ratio of generation||Ratio between renewable generation and fossil fuel generation||%|
|Fuel consumed per energy produced||Total amount of fuel consumed divided by the total energy produced in the microgrid||L/kWh|
|Consumption comparison||Comparison of the household average consumption with the region average||%|
|Capacity factor of the photovoltaic (PV) panels||Defined as the ratio between the total amount of energy that the PV plant produced during a period of time and the amount of energy that the plant would have produced at full capacity over the same period of time||%|
|Voltage deviation||Average deviation of the voltage from its nominal value during a period of time||V|
|Frequency deviation||Average deviation of the frequency from its nominal value during a period of time||Hz|
|Environmental||CO2 emissions||CO2 total emissions per energy produced||kg-CO2/kWh|
|Economic||Fuel cost||Fuel cost per energy produced||$/kWh|
|Electricity cost comparison with the region||Microgrid electricity cost compared with the costs of the region||$/kWh|
|Indicators of the Technical Dimension (||Value in January 2011||Lower Limit ()||Upper Limit ()||Normalized Value of the Indicator () (Non-Dimensional)|
|Ratio of generation [%]||0.21||0.7||1.0||0, since|
|Fuel consumed per energy produced [L/kWh]||0.191||0.05||0.18||0, since|
|Consumption comparison [%]||0.25||0||1.0|
|Capacity factor of the photovoltaic panels [%]||0.05||0.1||0.25||0, since|
|Voltage deviation [V]||0.09866||0||0.1|
|Frequency deviation [Hz]||0.03946||0||0.04|
|Dimension||Indicator||Weighting Factor () of Indicator from Dimension|
|Technical||Ratio of generation|
|Fuel consumed per energy produced|
|Capacity factor of the photovoltaic (PV) panels|
|Electricity cost comparison with the region|
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Rahmann, C.; Núñez, O.; Valencia, F.; Arrechea, S.; Sager, J.; Kammen, D. Methodology for Monitoring Sustainable Development of Isolated Microgrids in Rural Communities. Sustainability 2016, 8, 1163. https://doi.org/10.3390/su8111163
Rahmann C, Núñez O, Valencia F, Arrechea S, Sager J, Kammen D. Methodology for Monitoring Sustainable Development of Isolated Microgrids in Rural Communities. Sustainability. 2016; 8(11):1163. https://doi.org/10.3390/su8111163Chicago/Turabian Style
Rahmann, Claudia, Oscar Núñez, Felipe Valencia, Susana Arrechea, Jalel Sager, and Daniel Kammen. 2016. "Methodology for Monitoring Sustainable Development of Isolated Microgrids in Rural Communities" Sustainability 8, no. 11: 1163. https://doi.org/10.3390/su8111163