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Hybrid Photovoltaic-Wind Microgrid With Battery Storage for Rural Electrification…

Hybrid Photovoltaic-Wind Microgrid With Battery Storage for Rural Electrification…

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    Hybrid Solar Wind System Market Size, Share Industry Analysis, By Type (Stand-Alone System, On-Grid System), By Application (Residential, Commercial, Industrial) And Regional Forecast 2023-2030

    A hybrid solar-wind system is a combination of wind and solar energy. It also comprises a battery, which is used to store the energy produced from both sources. Thus, this system has increased reliability and improved efficiency as compared to the individual mode of generation. A key advantage for wind-solar hybrid systems is that they can produce more consistent power because solar power is produced during the day, while wind power is typically strongest at night. Increasing off-grid electricity demand, growing concern regarding the environment, and depletion of fossil fuels, government initiatives are anticipated to be a key factor propelling the industry growth in the future timeframe.

    Based on type, the global hybrid solar-wind system market includes stand-alone systems and on-grid systems. The stand-alone system is expected to grow at the fastest growth rate during the forecast period owing to its cost-effectiveness in a remote area when compared with the extension of grid-connected power lines.

    Based on application, the global hybrid solar-wind system market is segmented into residential, commercial, and industrial. The residential segment is anticipated to hold a significant share of the global market over the forecast period. The residential segment witnessed significant adoption of the product in the last few years, which includes single-family homes, luxury apartments, and large multi-family buildings. Electricity production cost is very high in islands areas due to the high price of fuel. Integration of renewable power sources with diesel generators provides reliable and cleaner power by reducing carbon emissions. Further, the less availability of land space for gird infrastructure drives the hybrid power solutions in the residential sector.

    The rising demand for clean and renewable grid electricity is another major factor expected to propel the growth of global hybrid solar-wind systems in the foreseeable years. Also, a decrease in wind and solar equipment component cost along with the rising demand for clean energy among consumers is anticipated to complement the growth of the global solar wind hybrid systems market. However, the high initial investment for the installation of solar wind hybrid systems is a major factor projected to hinder the growth of the global market.

    Key Players Covered:

    Some of the major companies in the global hybrid solar-wind system market are ReGen Powertech, Blue Pacific Solar Product, Inc., UNITRON Energy System Pvt. Ltd, Alternate Energy Company, Polar Power, Inc, Alpha Windmills, Zenith Solar System, Gamesa, Supernova Technologies Private Limited, and Grupo Dragon.

    Regional Analysis:

    The global hybrid solar-wind system market is studied across different regions like North America, Europe, Asia Pacific, Latin America, and Middle East Africa. The Asia Pacific dominated the global market and is expected to grow at a significant pace during the forecast period. Thriving power industry, Rapid industrialization, and urbanization particularly in the emerging economies of China, India, and Southeast Asia fuelling the growth of the market. Additionally, favorable government policies to install solar-wind hybrid systems, technological advancements, and a growing number of regulations to reduce carbon footprints are anticipated to further propel this regional market in the future. The Prime Minister of India has ramped up its commitments to renewable sources, as the country aims to expand its clean energy capacity from 86.3GW to 175GW by 2022 and 450GW by 2030.

    North America is another major market for solar-wind hybrid systems. The U.S. is the main country for the region’s solar-wind hybrid systems owing to the ongoing government policies and guidelines for utility metering and rising FOCUS for cost reduction and energy efficiency. Europe is also expected to contribute notably to the global solar wind hybrid systems market due to the rising number of regulations for the installation of solar wind hybrid systems across the region. Encouraging government rules and regulations relating to energy efficiency along with rising concerns for curbing carbon emissions are expected to drive the solar wind hybrid systems market over the forecast period.

    Hybrid Photovoltaic-Wind Microgrid With Battery Storage for Rural Electrification: A Case Study in Perú

    Microgrids are autonomous systems that generate, distribute, store, and manage energy. This type of energy solution has the potential to supply energy to remote communities since they can integrate solar, wind, and back-up diesel generation. These systems are potentially beneficial in Peru, where there are approximately 1.5 million people without access to electricity. This paper studies the technical aspects of the implementation, operation, and social impact of a hybrid microgrid installed in Laguna Grande, Ica, Peru, a rural fishing community composed of about 35 families who have lived in this remote location for more than 40 years without access to electricity. The design of the microgrid comprised three main stages: assessment, sizing, and social management. According to resource assessment, this location has a very high wind potential with an average of 8 m/s and annual average irradiation of 6 kWh/m 2 /day. The microgrid was designed based on interviews with members of the community on energy use, social-economic aspects, and factors such as expected growth and available funds. The construction followed a participatory approach, involving the community in specific stages of the project. This hybrid microgrid is composed of a 6 kWp photovoltaic system and two wind turbines of 3 kW each. It has two coupled 4 kW inverters that deliver power to a 230 V AC distribution line to which all the community loads are connected. Energy is stored using a VRLA 800 Ah, 48 V battery bank, which is designed to work at 50% DOD. The installed microgrid has proven very effective in supplying the average daily demand of 23 kWh at an almost steady power of 1–1.2 kW. During almost 2 years of monitoring, it has presented a 10% loss of load due to peak increases in demand, technical problems, and occasional low solar and wind resources. PV/wind integration is very important since approximately 60% of the energy demand is nocturnal. The CAPEX of the project reached USD 36,000.00, obtaining a cost of energy levelized cost of energy of 0.267 USD per kWh. The project has a useful life of 20 years, with battery renewal every 3 years and wind turbines and electronics every 10.


    A fraction of the world population still has no access to electricity and its associated benefits. A total of 88.86% of the world population has access to electricity, but this number declines to 78.67% when only rural areas are taken into account (World Bank, 2019). The traditional approach to solve this situation has been, for decades, to extend the grid but different characteristics such as geographic location, accessibility, reduced consumption per household, and transportation infrastructure make this kind of undertaking difficult and unattractive for private investors (Ministerio de Energía and Minas, 2015). Consequently, communities are left isolated or may rely on expensive alternatives. For instance, the intermittent use of diesel generators is unsustainable and creates a strong dependence on fuel and spare supply (Kirubi et al., 2009; Loka et al., 2014).

    Energy consumption across the world will grow by nearly 50% between 2018 and 2050, and renewable energy/electricity share growth will soon exceed fossil fuels (EIA, 2019). over, the levelized cost of energy (LCOE) from different microgrids around the world is getting more competitive and could replace diesel generators in different scenarios (Rehman and El-Amin, 2015; IRENA, 2016; El-houari et al., 2019; Veilleux et al., 2020). The logical next step is to develop and invest in technologies and solutions that use renewable resources.

    With the current state of technology, services such as lighting, battery charging, irrigation, refrigeration, and others can be provided not only for private use but for income generation (World Bank, 2019), and a reliable and sustainable energy supply is the fundamental first step in this process. Substantial development in PV technology, storage, and power electronics has boosted competitive microgrid design and development in many rural areas of the world (Gastelo-Roque and Morales-Acevedo, 2017; López-González et al., 2017; El-houari et al., 2019; Salihu et al., 2020). These autonomous energy systems integrate solar, wind, and back-up diesel generation along with battery storage and energy management constitute the best solution to the energy supply challenge for remote communities (Schnitzer et al., 2014; Louie, 2016). It is of great importance to conduct a proper resource assessment and energy demand evaluation (Zhou et al., 2010; Kobayakawa and Kandpal, 2015; Rehman et al., 2020).

    In Peru, as of 2018, only 81.5% of the rural population has access to electricity (MINEM, 2020). Increasing coverage will require even more active government participation with renewable energy systems. This kind of project has elevated social revenue but for communities to improve and reach the goal of sustainable development, it is imperative to exceed the minimum power requirements that small isolated renewable energy systems have usually provided so that the productive use of energy is promoted (Canziani and Melgarejo, 2019).

    This work explores the case study of the 12 kW Laguna Grande hybrid rural microgrid, undertaking an analysis of design, construction, and operation. Solar radiation, wind speed, power demand, and battery voltage are monitored to study the behavior of the system and develop an initial assessment of the relationship between renewable resource availability and its impact on the quality and availability of energy.


    Location of Study

    This research was carried out in the “Muelle” sector of Laguna Grande, a rural fishing community founded in 1979, located in the Paracas National Reserve, a protected area for the conservation and sustainable use of desert and marine ecosystems, in the Ica region in the coast of Peru. The community is situated on the banks of a brackish lagoon of the same name, which is open to the Pacific Ocean through a channel, on coordinates 14°08′33.5″ S 76°15′43.6″ W. (Figure 1A). Currently, the entire population lives and works around fishing and related activities, and there are almost 90 residents in 35 homes.

    FIGURE 1. (A) Location of Laguna Grande in the Paracas National Reserve, (B) Picture of the community in 2018.

    Due to its location within a national protected area and the impossibility of installing electrical networks, the community of Laguna Grande has never had access to conventional electricity. Having no connection to the electricity grid, some residents use kerosene, flashlights, and candles for lighting, and generators to charge cell phones and refrigerate food.

    The climate of Laguna Grande is typical of the Peruvian coastal desert, usually warm with strong wind. The average annual temperature is 18°C, ranging between 22°C in February and 15°C in August. The rains are scarce and occur during winter (July–September). The nature of the terrain, the intensity of the irradiation, and the cold sea trigger famous dust storms known as “Paracas”.

    Limitation of the Study

    Due to the accuracy and uncertainty of both resource and consumption data and the absence of a comprehensive simulation model, the design method in the present research can be considered heuristic and experimental.

    Resource Assessment

    Two months of activity data were recorded and compared with solar and wind datasets from Peruvian meteorological institutions, NASA and NREL. Once validated, these datasets were used for the microgrid design and energy production estimation. Statistical tests were applied with the specialized software OriginPro (Martins et al., 2008).

    Solar irradiance was measured as global horizontal irradiance (GHI) and recorded on-site with a Symphonie LI-COR LI-200/R-BL pyranometer. Wind direction and wind speed were recorded on-site with an NRG 200P wind vane and an NRG#40C anemometer, respectively at 4.5 m from the ground. All the data was stored in a SympohniePlus 3 datalogger.

    The typical daily solar radiation curve and peak Sun hour values were obtained from the solar irradiance data. Wind speed data was processed into a Weibull cumulative statistical distribution. Finally, the Mean Bias Error (MBE) and the Root Mean Square Error (RMSE) were calculated to check the accuracy of the mentioned datasets.

    Energy Demand Evaluation

    Household and community energy demand were calculated following a three-step process. First, the team interviewed the interested families, then defined consumption profiles based on habits and economic activities. Finally, estimations for the growth rate of both consumption per household and new households were made for the next 5 years.

    The total AC power of the system and daily energy consumption was defined according to the formulas below, adapted from the Peruvian Ministry of Economy and Finance (Ministerio de Economía and Finanzas, 2011).

    EAC (kWh): the community’s daily energy consumption.

    CP1 (kWh): consumption for profile 1.

    nP1: number of households with consumption profile 1.

    GRCP1: consumption growth rate for profile 1.

    CP2 (kWh): consumption for profile 2.

    nP2: number of households with consumption profile 2.

    GRCP2: Consumption growth rate for profile 2.

    Y (years): number of years for growth projection.

    PAC (kW): the community’s maximum power demand.

    DP1 (kW): demand for profile 1.

    GRDP1: demand growth rate for profile 1.

    DP2 (kW): demand for profile 2.

    GRDP2: demand growth rate for profile 2.


    The microgrid sizing was carried out in Microsoft Excel. It considered the validated wind and solar daily datasets (monthly average) for the location of the project; the estimated daily energy demand; equipment efficiency; electrical losses under normal operating conditions; and funding limits. There were no area restrictions. PV power and wind power, as well as their respective energy production, were calculated as a function of the demand, as shown below.

    Photovoltaic nominal power, adapted from (Smets et al., 2016).

    PPV (kWp): photovoltaic nominal power (kWp).

    EAC (kWh): community’s daily energy consumption, covered by PV.

    R (kWh/m 2 d): daily solar radiation (Monthly average).

    AkWp (m 2 ): effective installed area of one kWp.

    ηmod (%): PV module efficiency.

    Wind Power (Swift and Walker 2015)

    PW (kW): wind nominal power (kW).

    EAC (kWh): the community’s daily energy consumption, covered by wind energy.

    ηt (%): wind turbine efficiency.

    Cp (%): wind turbine coefficient of performance (Model depending).

    A (m 2 ): wind rotor swept area.

    Vh 3 (m/s) hourly average wind velocity at which electricity is produced.

    The battery design is considered energy for storage and depth of discharge (Smets et al., 2016). The bank was designed with VRLA AGM 100 Ah, 12 V, batteries.

    EBS (kWh): energy for battery storage.

    C20 (Ah): battery nominal capacity at a 20-h rate.

    Construction Planning

    The construction of the microgrid followed four stages:

    Installation of PV modules and wind turbines.

    Installation of power electronics (inverters, electrical control, and safety equipment).

    Construction of the power distribution line and household meters connection.

    Microgrid’s Parameters Measurement

    To evaluate the initial performance of the microgrid after its construction and commissioning, five parameters are considered important: 1) Global Horizontal Irradiance (GHI), 2) Wind speed, 3) Wind direction, 4) Battery Voltage, and 5) Power demand.

    The constant measurement and registration required a Symphonie LI-COR LI-200/R-BL pyranometer, an NRG 200P wind vane, and an NRG#40C anemometer, incorporated into a SymphoniePlus 3 datalogger. The operation parameters required AC and DC current meters, and voltage meters connected to an eGauge Pro datalogger.

    Analysis and Results

    Renewable Resources

    Solar Radiation

    Solar radiation measurements were performed for the correct sizing of the photovoltaic system. The radiation was measured for two months before installation and then continued throughout the operation of the system.

    The database closest to the measured values was the NREL Database, which according to the MBE, overestimates the radiation by 1.76%. The NREL Database has an RMSE of 10.30% and a correlation factor of 0.943. Table 1 shows a comparison between main databases with the actual measured values (Liu et al., 2019; Manju and Sandeep, 2019).

    TABLE 1. Comparison between measured values and databases.

    The radiation data shows that in Laguna Grande there is solar radiation from 06:00 am to 05:00 pm with peaks of up to 1100 W/m 2. with an average total irradiance of 7 kWh/m 2 /day in the months of highest radiation (January, February, and March) and an average of 5 kWh/m 2 during June, July, and August. Figure 2 shows an hourly profile of solar radiation in Laguna Grande. The annual average is 6.4 kWh/m 2. which represents a high potential for photovoltaic systems according to OLADE (OLADE, 2017), being able to produce up to 1.25 kWh/m 2 /kWp of photovoltaic energy, positioning itself as one of the areas with the greatest potential in Peru.

    FIGURE 2. Hourly solar radiation in Laguna Grande.

    Wind Potential

    To assess the power generated by the wind turbine system and its relationship with the resource, wind speed and direction were measured.

    The energy production is first expressed in terms of wind speed. Among the many mathematical models used in wind power studies, the cumulative statistical distribution of Weibull (Azad et al., 2019; Hulio et al., 2019; Khalid Saeed et al., 2019) is the most appropriate for describing wind speed variations. To do this, a frequency graph of wind speed was made.

    From the frequency histogram shown in Figure 3, it was observed that the most frequent wind speed is 10 m/s, reaching peaks of up to 13.5 m/s. Figure 4 shows the average hourly wind speed, the hours with the highest wind speed range from 10:00 am to 03:00 pm, with a decrease in night hours. It is remarkable that the availability of night wind, on average 6 m/s, which as shown below is essential to provide energy at night to the community. Figure 5 shows that the wind direction in Laguna Grande is predominantly to the southeast.

    FIGURE 3. Wind speed frequency and Weibull distribution in Laguna Grande.

    FIGURE 4. Daily average wind speed in Laguna Grande.

    FIGURE 5. Wind levels in Laguna Grande.

    Temperature is an important parameter in the design of the photovoltaic system. The operating temperature of the photovoltaic modules is related to the room temperature. When there are low temperatures (below 25°C of temperature in the cell) the photovoltaic system operates at a voltage greater than the nominal one, which can cause overvoltage on the DC side and electrical risks in the system. On the other hand, high temperatures (higher than 25°C of temperature in the cell) cause the system to operate at lower than nominal voltages and low system efficiencies. As a result, we used room temperature to estimate the size of the photovoltaic and energy storage systems. Figure 6 shows the room temperature in Laguna Grande.

    FIGURE 6. Temperature in Laguna Grande.

    Energy Demand Estimation

    Only two consumption profiles are found in the community: a household or domestic consumption profile and a commercial consumption profile. From the 35 registered users, 30 have a domestic profile which reaches a total of 18 kWh/month and five users have a commercial profile of 30 kWh/month (Ministerio de Economía and Finanzas 2011). The latter are businesses dedicated to the sale of food and groceries.

    In order to maintain a controlled and continuous service, 2 A circuit breakers and 4 A circuit breakers were installed in households and businesses, respectively.

    According to the consumption profiles, the number of registered users, and growth rates applied for the next 5 years after commissioning, the system must provide a total of 29 kWh/day.


    Microgrid AC-DC Configuration

    The microgrid was designed to power AC loads at 230 V. No DC load is covered in the project. PV, energy storage, and wind turbines were all connected to a 48 Vdc bus bar (Figure 7; Table 2) and two 48Vdc 4kW inverter/chargers (MPP Solar 4048 MS) dispatch 230 VAC to power all the 32 registered households and three businesses. Pictures of the implemented microgrid are shown in Figure 8.

    FIGURE 7. One-line diagram of Laguna Grande microgrid.

    TABLE 2. Components of the Laguna Grande microgrid.

    FIGURE 8. Pictures of Laguna Grande microgrid. (A) Battery bank and inverters, (B) Photovoltaic Array, (C) Wind turbines.

    Each 3 kW wind turbine has its controller and dump load, and each 3 kWp solar array was assigned to an independent MPPT controller built into the inverter/charger unit.

    It is important to monitor the operation of the system to ensure proper functioning and provide quality energy to the community. During the operation of the system the incident radiation, wind speed, battery voltage, and power demands were measured. The evaluations in this paper were based on measurements of about a year.

    The system is autonomous and works exclusively with renewable energy (solar and wind energy), and stores the energy in the battery bank. We evaluated the relationship between energy production and the availability of renewable resources, as well as the quality of energy provided.

    Power and Energy Production

    The system has a peak power of 12 kWp between solar and wind, but it has an AC power of 8 kW, which is its installed capacity. Figure 9 shows that the system delivers an average of 1kW of power for most of the day. According to the data collected, the maximum historical demand of the community is 1.45 kW. This shows that due to the lack of access to electricity in recent years there is a corresponding lack of electrical appliances other than lamps, cell phones, and radios, as the community is not yet accustomed to consuming large amounts of energy. This current demand is significantly below the AC installed capacity and is expected to grow during the following years.

    FIGURE 9. Hourly average power demand in Laguna Grande.

    The system provides energy almost all day, on average it provides 23 kWh to the community on a typical day, which is less than the storage capacity of the batteries (800 Ah at 48 V, 38.4 kWh). The demand profile shows that the peak time occurs between 5:30 and 9:30 pm, decreasing a bit, but maintaining consumption of about 800 W during the night. The wind resource is very important here since there is good night wind speed and the battery bank does not run out and there are not too many interruptions in the micro network.

    The battery voltage measurement results are used to know how the system storage behaves and the cuts that occur in the system since the battery bank is responsible for providing the network parameters to the micro network. When the voltage in the batteries is less than 44 V, the system disconnects and stops providing power to the community. Figure 10 shows a time-series of battery voltage during a week of operation. There is a voltage drop in the battery and a power outage in the system on days 27 and 28, while the other days show typical behaviors in which the system offered power without cuts. It is clear that the battery is discharged during the night and charged during the day.

    FIGURE 10. Time-series of battery voltage.

    A database of resources and behavior of the microgrid can be found at Gastelo-Roque and Vargas (2020).

    Economic and Social Impacts

    Several benefits were identified at every stage of the project. For instance, before construction, residents’ sense of identity with the community was strengthened: even though some members were skeptical about the project, others signed up for the service because of curiosity, high expectations, and peer encouragement. The elderly were involved and people developed capabilities in terms of their knowledge of the construction and basic maintenance of the system. Finally, and most importantly, women got involved as leaders of the committee for the management of the system.

    Every stage of the project required different types of interaction with the community to have an appropriate integration. For instance, before the execution of the project and, to assure viability, the community was required to have a minimum organizational structure and defined leaders; additionally, during this stage, the community had a more specific and direct conversation with the design team, resulting in important adjustments to the project to satisfy the real needs. Domenech et al. reported disagreements in rural communities that could have been solved with more communication to identify their needs more realistically (Léga et al., 2014). During construction, community involvement and support in undertaking different tasks was also required, and they assisted with low risk activities that do not require exposure to electrical hazards.

    It is of great importance to address the responsibilities that arise when aiming for long term sustainability. The system implementation required the creation of a management program and committee as described by Canziani and Melgarejo, involving the owner of the system, the managing committee, the users, and a controller (Figure 11). The owner offers operational and maintenance services through a contract and receives payment. The committee assures that the service reaches the users and collects payments corresponding to each month of energy consumption according to the contract signed with each user, and the controller interacts with each of these three parties and settles any reclamation or dispute (2019). The committee in Laguna Grande is directed by Ms. Elsa Saravia and Mr. César García. There was initial resistance to registration since it implied accepting to pay a consumption tariff to a system that was not even commissioned, but the first registered users encouraged others to also be part of this program.

    FIGURE 11. System management model adopted by the community.

    For the system to be sustainable, the managing committee set a rate of 0.90 Peruvian Sol (PEN)/kWh (0.267 USD/kWh), plus a 3 USD fixed monthly fee. The community deposits the earnings into a bank account destined for general maintenance, replacement batteries, emergencies such as unexpected equipment failure, and other expenses. Though significantly higher than city energy rates (e.g. nearest city Ica: 0.56 PEN/kWh (Osinergmin 2019)), this microgrid rate allows the community to rely on a secure economic mechanism.

    The CAPEX of the project amounted to USD 36,000.00 and the LCOE was estimated at 0.90 PEN/kWh or 0.267 USD/kWh; this is slightly less than the LCOE values from other microgrids for rural electrification. For instance, Sofimieari et al., 2019 reported values of around 0.486 USD/kWh and Veilleux et al. (2020), of around 0.274 USD/kWh. These numbers tend to go down as installed capacity rises (Chaurey and Kandpal, 2010; Singh et al., 2016; Sajed Sadati et al., 2018; Sofimieari et al., 2019).


    According to the results and experiences from the project, it can be concluded that this is an effective, simple, and low-cost methodology for rural microgrid design. This method involves five stages from resource assessment, demand evaluation, construction and planning, to operation and system monitoring.

    Laguna Grande has a very high wind potential with an average wind speed of 8 m/s and annual average irradiation of 6 kWh/m 2 /day. It is one of the few places in the world with such a high combined potential.

    A hybrid microgrid composed of a 6 kWp photovoltaic system and two wind turbines of 3 kW each was implemented and has proven very effective in supplying an average daily demand of 23 kWh at an almost steady power of 1–1.2 kW. During almost 2 years of monitoring, the installed microgrid has presented 10% of power outages due to peak increases in demand, technical problems, and occasional low solar and wind resources. PV/wind integration is very important since approximately 60% of the energy demanded is nocturnal.

    During the design process, data was collected with some uncertainty. It was considered that days of low solar radiation could be compensated by wind but when it came to the actual operation there were days where both the solar and wind resources were low, resulting in loss-of-load events not foreseen in the design, especially on winter days with low irradiation and wind speed.

    The battery bank was designed with the assumption that there would be a constant pattern of charge and discharge cycles, however, during the actual operation, the charge and discharge cycles varied, with days where the batteries performed more cycles than those estimated.

    The CAPEX of the project reached USD 36,000.00, obtaining a LCOE of 0.267 USD per kWh. The project estimated a life of 20 years use, with battery renewal every 3 years and wind turbines and electronics replaced every 10.

    The human factor is a fundamental aspect in every stage of the project when aiming for a sustainable working model. It is of great importance to establish a direct, simple, and easy way of communicating with the community to know their real needs. The Laguna Grande 12 kW PV-wind hybrid microgrid has proven to be a successful example of community management but there cannot be sustainable development without social engagement.

    This work is an evaluation of the Laguna Grande microgrid, and new equipment has been implemented that will measure the individual production of the photovoltaic and wind system. Work in the future will examine this data in further detail and explore the relationship between resources and the operation of the system as well as the quality of energy generated.

    Data Availability Statement

    The datasets generated for this study are available on request to the corresponding author.

    Ethics Statement

    Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.

    Author Contributions

    All authors have made direct contributions to the work. FC drafted the proposal, grant application, microgrid implementation, literature review, and final revision of the manuscript. RV compiled the literature review, microgrid implementation, experimental setup, and proofread the manuscript. JG-R compiled the literature review, undertook the statistical analysis, and proofread the manuscript.


    The engineering, provision, construction, and social management of the Laguna Grande hybrid microgrid was partially funded by the Interamerican Development Bank. This funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. The project was granted USD 98,000 by the “BID Ideas 2015” contest and was executed by the Peruvian company Waira Energía SAC. The current research and monitoring of the system are carried out with private funds.

    Conflict of Interest

    Waira Energía was hired as EPC company to build the microgrid. Waira Energía doesn’t contribute directly with the project.

    The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


    The authors would like to thank the community of Laguna Grande, Sector Muelle, for their involvement, support, and collaboration with this project. Special acknowledgments to Esther Saravia, for her unconditional support and willingness to learn. Finally, the authors thank the IDB for the funding of the project.


    Azad, K., Rasul, M., Halder, P., and Sutariya, J. (2019). “Assessment of wind energy prospect by Weibull distribution for prospective wind sites in Australia,” in Energy procedia, 2nd international conference on energy and power, ICEP2018–15. Sydney, Australia. 13–15 December 2018. Vol. 348, 13–55. doi:10.1016/j.egypro.2019.02.167

    Canziani, F., and Melgarejo, Ó. (2019). “Design and implementation of rural microgrids,” En Microgrids design and implementation, editado por antonio carlos zambroni de souza y miguel castilla. Cham: Springer International Publishing. 477–504. doi:10.1007/978-3-319-98687-6_17

    Chaurey, A., and Kandpal, T. C. (2010). A techno-economic comparison of rural electrification based on solar home systems and PV microgrids. Energy Pol. 38 (6), 3118–3129. doi:10.1016/j.enpol.2010.01.052

    EIA (2019). International energy outlook 2019. Available at: (Accessed December 15, 2019).

    El-houari, H., Amine, A., Rehman, S., Buker, M. S., Kousksou, T., Jamil, A., et al. (2019). Design, simulation, and economic optimization of an off-grid photovoltaic system for rural electrification. Energies 12 (24), 4735. doi:10.3390/en12244735

    Gastelo-Roque, J. A., and Morales-Acevedo, A. (2017). “Design of a photovoltaic system using thermoelectric Peltier cooling for vaccines refrigeration”, in En 2017. IEEE MIT undergraduate research technology conference (URTC). Cambridge, MA. November 3‒5, 2017. 1–4. doi:10.1109/URTC.2017.8284211

    Gastelo-Roque, J. A., and Vargas, R. H. (2020). Data base of hybrid PV-wind microgrid with battery storage for rural electrification: a case study in Perú. Available at: (Accessed December 15, 2019).

    Hulio, Z. H., Jiang, W., and Rehman, S. (2019). Techno-economic assessment of wind power potential of Hawke’s Bay using Weibull parameter: a review. Energy Strategy Rev. 26, 100375. doi:10.1016/j.esr.2019.100375

    IRENA (2016). Innovation outlook: renewable mini-grids. Available at: (Accessed December 15, 2019).

    Khalid Saeed, M., Salam, A., Rehman, A. U., and Abid Saeed, M. (2019). Comparison of six different methods of Weibull distribution for wind power assessment: a case study for a site in the northern region of Pakistan. Sustain. Energy Technol. Assess. 36, 100541. doi:10.1016/j.seta.2019.100541

    Kirubi, C., Jacobson, A., Kammen, D. M., and Mills, A. (2009). Community-based electric micro-grids can contribute to rural development: evidence from Kenya. World Dev. 37 (7), 1208–1221. doi:10.1016/j.worlddev.2008.11.005

    Kobayakawa, T., and Kandpal, T. C. (2015). Analysis of electricity consumption under a photovoltaic micro-grid system in India. Sol. Energy 116, 177–183. doi:10.1016/j.solener.2015.04.001

    Léga, D., Bruno, L. F. M., Lillo, P., no, R. P., and Chiroque, J. (2014). A community electrification project: combination of microgrids and household systems fed by wind, PV or micro-hydro energies according to micro-scale resource evaluation and social constraints. Energy Sustain. Dev. J. Int. Energy Initiative 23, 275–285. doi:10.1016/j.esd.2014.09.007

    Liu, P., Tong, X., Zhang, J., Meng, P., Li, J., and Zhang, J. (2019). Estimation of half-hourly diffuse solar radiation over a mixed plantation in North China. Renew. Energy 149, 1360–1369. doi:10.1016/j.renene.2019.10.136

    Loka, P., Moola, S., Polsani, K., Reddy, S., Shannon, F., and Skumanich, A. (2014). A case study for micro-grid PV: lessons learned from a rural electrification project in India. Prog. Photovolt. Res. Appl. 22 (7), 733–743. doi:10.1002/pip.2429

    López-González, A., Domenech, B., Gómez-Hernández, D., and Ferrer-Martí, L. (2017). Renewable microgrid projects for autonomous small-scale electrification in andean countries. Renew. Sustain. Energy Rev. 79, 1255–1265. doi:10.1016/j.rser.2017.05.203

    Louie, H. (2016). Operational analysis of hybrid solar/wind microgrids using measured data. Energy Sustain. Dev. 31, 108–117. doi:10.1016/j.esd.2016.01.003

    Manju, S., and Sandeep, M. (2019). Prediction and performance assessment of global solar radiation in Indian cities: a comparison of satellite and surface measured data. J. Clean. Prod. 230, 116–128. doi:10.1016/j.jclepro.2019.05.108

    Martins, F. R., Pereira, E. B., Silva, S. A. B., Abreu, S. L., and Colle, S. (2008). Solar energy scenarios in Brazil, Part 1: resource assessment. Energy Pol. 36 (8), 2843–2854. doi:10.1016/J.ENPOL.2008.02.014

    MINEM (2020). Minem muestra en Alemania los avances del Perú en materia de energías renovables y los planes al 2021. Available at: (Accessed December 15, 2019).

    Ministerio de Economía and Finanzas (2011). Electrificación rural: Guía para la formulación de proyectos de inversión exitosos. Lima, Peru: Peru Government.

    Ministerio de Energía and Minas (2015). Plan nacional de electrificación rural (PNER) 2016-2025. Available at: (Accessed December 15, 2019).

    OLADE (2017). Anuario de Estadísticas Energéticas 2017. Buenos Aires, Argentina: OLADE.

    Rehman, S., and El-Amin, I. (2015). Study of a solar pv/wind/diesel hybrid power system for a remotely located population near arar, Saudi Arabia. Energy Explor. Exploit. 33 (4), 591–620. doi:10.1260/0144-5987.33.4.591

    Rehman, S., Rahman Habib, H. U., Wang, S., Buker, M. S., Alhems, L. M., and Al Garni, H. Z. (2020). Optimal design and model predictive control of standalone HRES: a real case study for residential demand side management. IEEE Access 8, 29767–29814. doi:10.1109/ACCESS.2020.2972302

    Sajed Sadati, S. M., Jahani, E., Taylan, O., and Baker, D. K. (2018). Sizing of photovoltaic-wind-battery hybrid system for a mediterranean island community based on estimated and measured meteorological data. J. Sol. Energy Eng. 140 (1), 011006. doi:10.1115/1.4038466

    Salihu, T. Y., Akorede, M. F., Abdulkarim, A., and Abdullateef, A. I. (2020). Off-grid photovoltaic microgrid development for rural electrification in Nigeria. Electr. J. 33 (5), 106765. doi:10.1016/j.tej.2020.106765

    Schnitzer, D., Lounsbury, D. S., Carvallo, J. P., Deshmukh, R., Apt, J., and Kammen, D. M. (2014). A critical review of best practices based on seven case studies. California: United Nations. 122.

    Singh, S., Singh, M., and Chandra Kaushik, S. (2016). Feasibility study of an islanded microgrid in rural area consisting of PV, wind, biomass and battery energy storage system. Energy Convers. Manag. 128, 178–190. doi:10.1016/j.enconman.2016.09.046

    Smets, A., Isabella, O., Jäger, K., van Swaaij, R., and Zeman, M. (2016). Solar Energy: the physics and engineering of photovoltaic conversion, technologies and systems. Cambridge, UK: UIT Cambridge Ltd.

    Sofimieari, I., Mustafa, M. W. B., and Obite, F. (2019). Modelling and analysis of a PV/Wind/Diesel hybrid standalone microgrid for rural electrification in Nigeria. Bull. Electric. Eng. Inform. 8 (4), 1468–1477. doi:10.11591/eei.v8i4.1608

    Swift, A., and Walker, R. (2015). En wind Energy Essentials, Conversion of power in the wind to electricity. New York, NY: John Wiley Sons. 71–99. doi:10.1002/9781119040934.ch4

    Veilleux, G., Potisat, T., Pezim, D., Ribback, C., Ling, J., Adam, K., et al. (2020). Techno-economic analysis of microgrid projects for rural electrification: a systematic approach to the redesign of Koh Jik off-grid case study. Energy Sustain. Dev. 54, 1–13. doi:10.1016/j.esd.2019.09.007

    Zhou, W., Lou, C., Li, Z., Lu, L., and Yang, H. (2010). Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems. Appl. Energy 87 (2), 380–389. doi:10.1016/j.apenergy.2009.08.012

    Keywords: solar energy, wind energy, microgrid, energy storage, rural electrification, Perú (Min5-Max 8)

    Citation: Canziani F, Vargas R and Gastelo-Roque JA (2021) Hybrid Photovoltaic-Wind Microgrid With Battery Storage for Rural Electrification: A Case Study in Perú. Front. Energy Res. 8:528571. doi: 10.3389/fenrg.2020.528571

    Received: 30 January 2020; Accepted: 13 November 2020; Published: 18 February 2021.

    Jeffrey Hardy, Imperial College London, United Kingdom

    Shafiqur Rehman, King Fahd University of Petroleum and Minerals, Saudi ArabiaPu Li, Technische Universität Ilmenau, Germany

    Copyright © 2021 Canziani, Vargas and Gastelo-Roque. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    Correspondence: José A. Gastelo-Roque,

    New power generation: Rural co-op makes bet on wind, solar hybrid

    The electricity we use is often generated hundreds of miles away. Dan Juhl wants to keep it local.

    The longtime energy developer is convinced that small, hybrid solar-and-wind projects are the future of electricity generation in rural areas. Much of the renewable electricity in the system now is generated by large wind farms or giant fields of solar panels. But Juhl envisions turning that approach on its head by creating dozens of small wind-and-solar sites that feed energy to consumers nearby.

    The time is coming. The technology is there. It’s reliable, it’s efficient,” said Juhl, who has for years been developing renewable energy in Minnesota. “We’re not a bunch of wild-eyed hippies anymore. It’s the real deal.”

    His concept: Pair two wind turbines and an array of solar panels to generate electricity that flows into the local energy grid.

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    The ultimate test of whether the approach is sustainable is the cost of the electricity it produces — and Juhl is certain that small solar-and-wind sites scattered around the state can produce electricity that’s cheaper than current market rates.

    To prove his theory, Juhl’s company — Juhl Energy — has built what he calls the first hybrid generating system in the country.

    Making renewable local

    To make this hybrid wind-and-solar approach work economically, Juhl first had to streamline the conversion process. Wind turbines and solar panels produce electricity differently, and that electricity must be converted before it can be sent to consumers. Juhl had to find a way to convert wind energy and solar energy into electricity through the same process.

    So, he partnered with electric behemoth General Electric to build the technology that would route the energy generated from wind turbines and solar panels through the same power conversion process, cutting the cost of combining wind and solar power at a single location.

    “We can produce and deliver clean power for less than the existing system,” Juhl said. He estimates the savings at about 2.5 cents per kilowatt-hour of electricity. The average residential price of a kilowatt-hour of electricity in Minnesota is about 14 cents.

    The challenge, said Juhl, is convincing rural electric cooperatives that renewable energy can save them money.

    Tim Thompson is convinced. He’s CEO of Pelican Rapids, Minn.-based Lake Region Electric Cooperative, which serves west-central Minnesota and is buying the electricity that’s being produced from the first Juhl Energy hybrid system.

    Juhl’s single wind turbine and solar array hybrid near Rothsay, Minn., has only been operating since March, but Thompson said he expects his co-op will save about 150,000 annually because the electricity is cheaper than the market price the co-op pays for the rest of the electricity it uses.

    hybrid, photovoltaic-wind, microgrid, battery, storage, rural

    Any time we can produce renewable energy at the local level, [and] our members consume that locally, we can save them a little bit of money in the process,” Thompson said. “That’s a perfect project for us.

    The electricity generated here flows into an existing Lake Region Electric substation 3 miles away. The power stays local: It’s used by the roughly 1,200 customers in the 150 square miles served by the substation.

    This 4.5 million project is smaller than what Juhl envisions as the ideal hybrid generation unit. The full system he’s designed would include solar panels combined with two wind turbines — double the amount at the Rothsay site.

    A smaller scale for energy resilience

    Renewable energy is often produced by massive wind farms or large fields of solar panels that generate electricity that’s transported onto the grid and used hundreds of miles away.

    But the U.S. Energy Information Administration predicts significant growth in smaller, locally produced electricity, known as distributed power generation, in the next 30 years, as solar panels become less expensive to buy and install.

    Juhl said the small distributed model of electrical generation makes the system more reliable — and resilient.

    If it’s not windy or sunny here, it’s probably windy or sunny [somewhere else],” he said. “And so a distributed model adds a much higher reliability to renewables than central station renewables.”

    The idea is that many small power generation units spread the risk when compared with large facilities that FOCUS generation in a single area.

    I mean, there’s no fuel, no emissions, no waste, no water and no transmission costs,” Juhl said. “How can it not be economical to deliver power like that?

    Juhl envisions eventually adding battery storage in rural communities to help utilize the locally generated power.

    A customer in co-ops

    While Juhl sees reluctance among many rural electric cooperatives to embrace the hybrid model, Thompson has no reservations.

    As a member-owned cooperative, we really pay very close attention to what our members want and need,” Thompson said. “And the feedback from members is that they do want more renewable energy.

    Does that mean Thompson expects to see more of these projects on the Lake Region Electric system? Probably not — at least not in the short term.

    Lake Region Electric buys the bulk of the electricity it distributes to customers from Great River Energy, and — as is the case with most co-ops’ contracts with big power producers — its contract with Great River limits how much renewable electricity the cooperative can buy from other sources. This hybrid project with Juhl makes up about half the total allowed.

    Great River Energy produces 58 percent of all the electricity it sells from coal, and 25 percent from renewable energy sources like wind or solar.

    Most rural electric cooperatives are locked into long-term contracts that limit how much electricity they can buy from other sources. That would make expanding the hybrid model on a large scale fairly difficult.

    But Juhl said he’s been getting more inquiries from members of electric cooperative boards since the Rothsay project went online — and he’s hopeful that soon, his vision for locally generated renewable energy will power more rural communities.

    Optimal design of solar–wind hybrid system-connected to the network with cost-saving approach and improved network reliability index

    In this paper, the optimal design of a grid-connected the hybrid energy system for a sample area in the north Iran is studied. A new innovative cost-based objective function is proposed which is combination of life cycle cost and reliability cost. Also, loss of power supply probability (LPSP) criteria, is considered as constraint for ensuring at the same time certain level of system reliability. Designing process is implemented in such a way that the total cost of the system reaches its minimum. For this purpose, a modified version of Bee algorithm has been proposed to achieve this goal. In order to carry out studies, the actual sample system, whose data has been available, has been studied. The results indicate the good performance of proposed hybrid system to reduce system cost.


    Renewable energy sources such as wind and solar have grown dramatically due to the need to preserve fossil fuel resources for future generations and to prevent the burning environmental damage caused by them, and they can be found near utilization centers in order to decrease losses [1,2,3]. For improve renewable resources performance, the sources work together and complement each other, known as hybrid systems. Because the power systems with two or more different sources of energy, they are more reliable than systems with one source. The hybrid of photovoltaic and wind turbine systems can provide a wide range of facilities. But these systems should be more robust and flexible in terms of power generation [4]. One solution to this is the optimal design of solar and wind combined systems. Various purposes for designing hybrid systems such as reducing costs, reducing emissions, improving power quality indicators, and improving reliability are considered [5].

    Designing optimal and determining the optimum capacity of different sources of energy production and with different approaches in these references has been discussed. In recent years, the use of renewable energy in order to generate energy and supply to the grid has increased steadily. For example, in [6], heuristic based algorithm is proposed for optimal design of independent solar and wind power system incorporating load forecasting. In [7], the design of a hybrid solar–wind and battery system, and considering the probability of losing power source (LPSP). In this paper, a differential evolution algorithm has been used. In [8], a hybrid search optimization algorithm is used for optimal design of a solar wind power plant with hydrogen sources is presented. In designing procedure, weather forecasting is also used for accurate results of simulations. In [9], a new optimization method called Swine Flu modeling based on quarantine optimization is proposed to determine the optimal location and size of dispersed generation units in the distribution network, in order to minimize the active power losses. The above algorithm performs randomization through quarantine and healing. The proposed algorithm has been applied to a 33-bus distribution system and the results of the proposed method have been compared with the results of the PSO optimization method. In [10], simulated annealing-chaotic search algorithm-based optimization is proposed optimal design of reverse osmosis hybrid desalination system driven by wind and solar energies. The model used in this work includes a solar-powered hybrid system with energy storage, or the same battery. In [11], applications of distributed generation sources are integrated and transmitted separately from the network. Homer, HOGA and Ret Screen were introduced in this reference. DE algorithm, particle communities, and harmonic search of intelligent methods have led to the design of optimal hybrid power generation systems. In this paper, the main objective of the design of the hybrid power generation system in the studied grid, the reduction of energy production costs and the improvement of system reliability indices such as unprotected energy (ENS) and LPSP in design considerations are taken. Considering the cost per kilowatt of energy not provided and adding this cost to energy costs, a single target goal of energy will be created. As a result, the algorithm must minimize this function. On the other hand, according to the defined standards, the LPSP limit value should be less than the permissible limit (2% per year), which is applied as an optimization limitation in the problem [12].

    In this paper a new comprehensive objective function is proposed for designing solar–wind hybrid system in an area in the north of Iran. The proposed objective function is a combination of life cycle cost and reliability cost. Also, reliability constraints are considered in the design process. A modified version of the bee algorithm is also proposed to solve the optimization problem.

    The remainder of this article is presented in the second part of the study network. In the third section, the relationships required for modeling the proposed system are described, and in Sect. 4, the Bee algorithm is briefly described. In the fourth section, simulation results were presented in three scenarios. Finally, this article ends with the results and conclusions in Sect. 5.

    Power generation hybrid system

    In recent years, distributed sources have been used abundantly in distributed electrical energy networks to reduce losses, improve reliability, reduce environmental pollution, and reduce energy costs, and so on. According to the statistics, among the distributed sources of production, solar and wind sources have been used more than other sources. The reason for this is the availability of solar and wind power in most parts of the world, as well as their lack of pollution. But the issue that is of great importance in this area is the power to extract solar and wind resources depending on the intensity of the sun’s radiation and wind speed in that area. Now, if there is not enough sun in the hours of daylight or wind speed, these two power supplies will not be produced. By combining solar, wind and solar resources together, a hybrid power generation system can provide more reliable reliability than systems with source [13]. It can be connected to the power grid so that there can be power exchange with the network. In Fig. 1, a hybrid power generation system is shown in which solar and wind resources are used as two sources of distributed generation that are responsible for supplying the region. The surplus power will be sold to the grid and in the event of a lack of power; the network will be used to supply the required electrical energy. In this system, meters are used to determine the amount of power exchanged with the network and load. One of the challenges ahead in power generation hybrid systems is the optimal size of each resource, which is strongly dependent on the amount of load in the area and its geographical condition [14]. The number of solar panels and the number of wind turbines used to minimize costs, in addition to supply, is a completely non-linear problem.

    Objective function and constraints

    The purpose of the design of the solar hybrid winding system for the studied network is to determine the number of solar panels and wind turbines with the aim of reducing energy costs and minimizing the cost of energy due to the energy not provided in the network. The total cost of the proposed system includes the total initial investment costs, the unprotected cost of energy and the net present value of all operating and maintenance costs [15]. This includes the replacement cost energy not supply cost (SCOC) and residual value of each component of the system plus the difference between the present value of the cost and the revenue from the delivery of power to the network, which is the cost function in the form of Eq. (1):

    The variable to be calculated is the total area of the solar panels and the swept surface of the wind turbine blades represented by the Apv and AW variables per square meter. Therefore, the total setup cost is:

    It is worth noting that the N-year evaluation horizon of the project is equivalent to the useful life of a solar panel (LPV), so the cost of replacing this component from the system is zero. (RNPV_PV = 0). The useful life of wind turbines (LW) is usually less than that of solar panels (here it is equal to N). Therefore, additional investment for wind turbines will be required before the horizon of the project is completed. The number of times the N-year horizon of the wind turbine project should be replaced is equal to XW = N/LW [16]. If αW is the initial investment in the current time in dollars pe r square meter, then the investment in year y is equal to:

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