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Currently, the industrial sector consumes more than 60% of the energy produced in Mexico, mainly from fossil fuels, causing negative impacts on the environment and human beings. Solar energy helps companies diversify their energy sources, generate savings, and reduce dependence on fossil fuels. Moreover, the environmental impact can be reduced when CO2 emissions are reduced. Nevertheless, in Mexico, less than 3.5% of the electricity comes from solar energy, and along with a lack of information about the technical and social aspects involved in photovoltaic (PV) systems, it is difficult for companies to analyze and evaluate relevant data, and thus make effective decisions based on their needs. As such, companies cannot understand the complete lifecycle of PV systems, and, usually, the economic, environmental, and technical decisions are made only using the installation analysis, which is only one stage in the lifespan of PV systems. This paper proposes an S4 framework with the sensing, smart, sustainable, and social features that small and medium-sized companies must consider to install, operate, and dispose of PV systems, considering the Mexican context. The current literature does not show a complete classification to cover the essential S4 features to describe PV systems, so companies only have partial information when deciding about the installation of PV systems. This framework considers all the needs that may exist during the PV systems' lifecycle, making a detailed evaluation of each of its elements in each lifecycle stage. Consequently, this S4 framework gives a complete guideline allowing companies to decide on PV systems. Finally, this paper presents a case study about a Mexican company that uses the proposed S4 framework to analyze the PV's lifespan. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the possibility of using a stand-alone photovoltaic system (SAPVS) for electricity generation in urban areas in Southern Mexico. In Mexico, an urban area is defined as an area where more than 2500 inhabitants live. Due to constant migration from the countryside to the cities, the number of inhabitants of urban localities has been increasing. Global horizontal irradiation (GHI) data were recorded every 10 min during 2014-2016 in Coatzacoalcos in the state of Veracruz located on 18°'8''9'' N and 94°27'48'' W. In this study, batteries represented 77% of the total cost, 12 PV panels of 310 W could export 5.41 MWh to the grid, and an inverter with an integrated controller and charger was selected, which decreased the initial cost. The city of Coatzacoalcos was chosen because the average annual temperature is 28°, with an average relative humidity of 75% and an average irradiance of 5.3 kWh/m2/day. An emission factor 0.505 tCO2/MWh of greenhouse gases (GHG) were obtained, based on the power system, the reduction of net annual GHG would be 11 tCO2 and a financial revenue of 36.951 × 103 $/tCO2 would be obtained. Financial parameters such as a 36.3% Internal Rate Return (IRR) and 3.4 years payback show the financial viability of this investment. SAPVSs in [ABSTRACT FROM AUTHOR]

Many rural communities in developing countries rely on diesel-fueled power generation, in which the use of hybrid renewable energy systems (HRES) is an environmentally and economically attractive option. The main objective of this study is to analyze the feasibility to implement a HRES based on photovoltaic technology. The main contribution is to present a reliable and adaptable methodology to optimize an energy system sizing and fuel consumption to meet the power demand in rural areas, regardless of the geographic location or load profile, that can be easily implemented in freely available tools. For this purpose, a typical load scenario provided by an industrial partner is considered. This consumption data was compiled from experimental measurements in different rural communities, which averages a daily consumption of approximately 300 kWh. Three different power systems are analyzed: (i) a diesel generator with battery storage, (ii) a photovoltaic system with storage, and (iii) a photovoltaic system with diesel generator and battery storage. For each case, three storage technologies were considered, namely: lead–acid, Li-ion and absorbent glass mat (AGM), from which the first one was the least expensive. These storage systems were operated within the limits of maximum load and minimum discharge that each technology establishes. The photovoltaic/diesel-generator/AGM battery hybrid power system turned out to be the least expensive and the most feasible, with a net present cost of USD311,632.53 and a cost of energy (COE) of USD0.14/kWh. The presented results demonstrate the advantages and disadvantages of each system, as well as their economic and technical feasibility. A cost reduction was found regarding the COE when comparing the system proposed in this study to other reported studies. Additionally, a sensitivity analysis was performed to report the impact of cost variations on the overall COE. These results prove that it is possible to satisfy the electrical demand of rural communities at a reasonable and accessible cost. • Spreadsheet-based optimization model developed for rural hybrid systems. • Battery SOC was the main decision-making variable. • Renewable energy penetration still relies on hydrocarbon fuels. • A minimum COE of USD0.14/kWh was calculated for the optimized system. • A sensitivity analysis delivered the capital cost of the PVS as the most relevant. [ABSTRACT FROM AUTHOR]

Abstract: The Mexican territory has a large potential for renewable energy development, such as geothermal, hydro, biofuels, wind and solar. Thus, a 2.5 kW hybrid power system (solar, wind and hydrogen) was designed and installed to meet the power demand for a stand-alone application at the University of Zacatecas. The hybrid unit integrates three power energy sources –a photovoltaic system (PV), a micro-wind turbine (WT), a prototype of a unitized regenerative fuel cell (URFC) and energy storage devices (batteries)– in addition to their interaction methodology. The main contribution of this work is the URFC integration to a hybrid power system for the production of H2 (water electrolyzer mode) and energy (fuel cell mode). These three energy technologies were connected in parallel, synchronized to the energy storage system and finally coupled to a power conversion module. To achieve the best performance and energy management, an energy management and control strategy was developed to the properly operation of the power plant. A meteorological station that has wireless sensors for the temperature, the humidity, the solar radiation and the wind speed provides the necessary information (in real time) to the monitor and control software, which computes and executes the short and mid–term decisions about the energy management and the data storage for future analysis. [Copyright &y& Elsevier]

In this manuscript, distinct approaches were used in order to obtain the best electrical power estimation from photovoltaic systems located at different selected places in Mexico. Multiple Linear Regression (MLR) and Gradient Descent Optimization (GDO) were applied as statistical methods and they were compared against an Adaptive Neuro-Fuzzy Inference System (ANFIS) as an intelligent technique. The data gathered involved solar radiation, outside temperature, wind speed, daylight hour and photovoltaic power; collected from on-site real-time measurements at Mexico City and Hermosillo City, Sonora State. According to our results, all three methods achieved satisfactory performances, since low values were obtained for the convergence error. The GDO improved the MLR results, minimizing the overall error percentage value from 7.2% to 6.9% for Sonora and from 2.0% to 1.9% for Mexico City; nonetheless, ANFIS overcomes both statistical methods, achieving a 5.8% error percentage value for Sonora and 1.6% for Mexico City. The results demonstrated an improvement by applying intelligent systems against statistical techniques achieving a lesser mean average error. [ABSTRACT FROM AUTHOR]