Peanut Shell for Energy: Properties and Its Potential to Respect the Environment

The peanut (Arachys hypogaea) is a plant of the Fabaceae family (legumes), as are chickpeas, lentils, beans, and peas. It is originally from South America and is used mainly for culinary purposes, in confectionery products, or as a nut as well as for the production of biscuits, breads, sweets, cereals, and salads. Also, due to its high percentage of fat, peanuts are used for industrialized products such as oils, flours, inks, creams, lipsticks, etc. According to the Food and Agriculture Organization (FAO) statistical yearbook in 2016, the production of peanuts was 43,982,066 t, produced in 27,660,802 hectares. Peanuts are grown mainly in Asia, with a global production rate of 65.3%, followed by Africa with 26.2%, the Americas with 8.4%, and Oceania with 0.1%. The peanut industry is one of the main generators of agroindustrial waste (shells). This residual biomass (25–30% of the total weight) has a high energy content that is worth exploring. The main objectives of this study are, firstly, to evaluate the energy parameters of peanut shells as a possible solid biofuel applied as an energy source in residential and industrial heating installations. Secondly, different models are analysed to estimate the higher heating value (HHV) for biomass proposed by different scientists and to determine which most accurately fits the determination of this value for peanut shells. Thirdly, we evaluate the reduction in global CO2 emissions that would result from the use of peanut shells as biofuel. The obtained HHV of peanut shells (18.547 MJ/kg) is higher than other biomass sources evaluated, such as olive stones (17.884 MJ/kg) or almond shells (18.200 MJ/kg), and similar to other sources of biomass used at present for home and industrial heating applications. Different prediction models of the HHV value proposed by scientists for different types of biomass have been analysed and the one that best fits the calculation for the peanut shell has been determined. The CO2 reduction that would result from the use of peanut shells as an energy source has been evaluated in all production countries, obtaining values above 0.5 ‰ of their total emissions

Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico

The Energetic Transition Law in Mexico has established that in the next years, the country has to produce at least 35% of its energy from clean sources in 2024. Based on this, a proposal in this study is the cogeneration between the principal thermal power plants along the Mexican states of the Gulf of Mexico with modeled wind farms near to these thermal plants with the objective to reduce peak electricity demand. These microscale models were done with hourly MERRA-2 data that included wind speed, wind direction, temperature, and atmospheric pressure with records from 1980–2018 and taking into account roughness, orography, and climatology of the site. Wind speed daily profile for each model was compared to electricity demand trajectory, and it was seen that wind speed has a peak at the same time. The amount of power delivered to the electric grid with this cogeneration in Rio Bravo and Altamira (Northeast region) is 2657.02 MW and for Tuxpan and Dos Bocas from the Eastern region is 3196.18 MW. This implies a reduction at the peak demand. In the Northeast region, the power demand at the peak is 8000 MW, and for Eastern region 7200 MW. If wind farms and thermal power plants work at the same time in Northeast and Eastern regions, the amount of power delivered by other sources of energy at this moment will be 5342.98 MW and 4003.82 MW, respectively

GIS-Based Wind and Solar Power Assessment in Central Mexico

In Mexico, the economic and industrial development is in the center and north; this represents more than 50% of the country’s total consumption. Data on population and energy consumption will be obtained from the following sources: the National Institute of Geography and Statistics (INEGI), and the Energy Information System. Regarding meteorological data, two databases are used: the Automatic Weather Stations (AWS) (for solar irradiance data) and the MERRA-2 reanalysis data (for wind data). These data will be analyzed for use in a geographic information system (GIS) using kriging interpolation to create maps of solar and wind energy. The area studied includes the following states: Mexico City, Puebla, State of Mexico, Hidalgo, Morelos, Zacatecas, Queretaro, San Luis Potosi, Guanajuato, Aguascalientes and Tlaxcala. The results showed that the areas with the highest solar potential are Hidalgo, Estado de México, Morelos, northern Puebla, southern Queretaro, northwestern Guanajuato, and northern Zacatecas, with 5.89 kWh/m2/day, and the months with the highest solar potential are March, April, May, and June. Regarding wind potential, the maximum wind power density is in Puebla, with 517 W/m2, and the windy season in central Mexico spans June, July, August, September, October, and November

Worldwide Research Trends on Optimizing Wind Turbine Efficiency

In a world in which electricity is increasingly necessary, it is vitally important to ensure that the supply of this electricity is safe, reliable, sustainable, and environmentally friendly, reducing CO2 emissions into the atmosphere and the use of fossil fuels. Renewable energies, and wind energy, in particular, make a significant contribution to this. Wind energy research dates to the last century, yet efforts to improve wind turbine performance continue around the world. Advances in blade aerodynamics and wind resource assessment are outstanding [...

Optimal location and sizing of PV sources in DC networks for minimizing greenhouse emissions in diesel generators

This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid

Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves

This paper presents an optimization model for the optimal placement and sizing of wind turbines, considering their reactive power capacity, wind speed, and demand curves. The optimization model is nonlinear and is focused on minimizing power losses in AC distribution networks. Also, paired wind turbine and power conversion systems are treated via chargeability factor η at the peak hour. This factor represents the percentage of usage of the power conversion system in the nominal wind speed conditions, and allows to support reactive power dynamically during all periods of the day as a function of the distribution system requirements. In addition, an artificial neural network is used for short-term forecasting to deal with uncertainties in wind power generation. We assume that the number of wind power distributed generators could be from zero to three generators integrated into the system, considering unit power factors and reactive power injections to follow up the effect of reactive power compensation in the daily operation. The General Algebraic Modeling System (GAMS) is employed to solve the proposed optimization model

Analysis of a novel proposal using temperature and efficiency to prevent fires in photovoltaic energy systems

Fires in photovoltaic (PV) electrical systems are a real and serious problem because this phenomenon can have severe consequences for the safety of people and the environment. In some cases, fires result from a lack of maintenance or improper installation of PV modules. It is essential to consider prevention and continuous monitoring of the electrical parameters to minimize these risks, as these factors increase the temperature of the photovoltaic modules. The use of thermal analysis techniques can prevent hotspots and fires in photovoltaic systems; these techniques allow detecting and correcting problems in the installation, such as shadows, dirt, and poor-quality connections in PVs. This paper presents a case study of the implementation of thermal analysis in an installation of photovoltaic modules connected to a solar pumping system to identify the formation of hotspots through thermal images using an unmanned aerial vehicle (UAV). Here, a novel methodology is proposed based on the comparison of temperature increases concerning the values of short circuit current, open circuit voltage, and real efficiency of each PV module. In addition, an electrical safety methodology is proposed to design a photovoltaic system that prevents fires caused by hotspots, contemplating critical parameters such as photovoltaic power, number of photovoltaic modules, DC:AC conversion ratio, electrical conductor selection, control devices, and electrical protection; the performance power expected was obtained using standard power test conditions, including irradiance factor, photovoltaic module (PVM) temperature factor, and power reduction factor

Sustainable Thermal Energy Generation at Universities by Using Loquat Seeds as Biofuel

Global energy consumption has increased the emission of greenhouse gases (GHG), these being the main cause of global warming. Within renewable energies, bioenergy has undergone a great development in recent years. This is due to its carbon neutral balance and the fact that bioenergy can be obtained from a range of biomass resources, including residues from forestry, agricultural or livestock industries, the rapid rotation of forest plantations, the development of energy crops, organic matter from urban solid waste, and other sources of organic waste from agro-food industries. Processing factories that use loquats to make products such as liqueurs and jams generate large amounts of waste mainly in the form of skin and stones or seeds. These wastes are disposed of and sent to landfills without making environmentally sustainable use of them. The University of Almeria Sports Centre is made up of indoor spaces in which different sports can be practiced: sports centre pavilion (central court and two lateral courts), rocodrome, fitness room, cycle inner room, and indoor swimming pool. At present, the indoor swimming pool of the University of Almeria (UAL) has two fuel oil boilers, with a nominal power of 267 kW. The main objective of this study is to propose an energetic analysis to determine, on the one hand, the energetic properties of the loquat seed and, on the other hand, to evaluate its suitability to be used as a solid biofuel to feed the boilers of the heated swimming pool of the University of Almeria (Spain), highlighting the significant energy and environmental savings obtained. Results show that the higher calorific value of loquat seed (17.205 MJ/kg), is like other industrial wastes such as wheat straw, or pistachio shell, which demonstrates the energy potential of this residual biomass. In addition, the change of the fuel oil boiler to a biomass (loquat seed) boiler in the UAL’s indoor swimming pool means a reduction of 147,973.8 kg of CO2 in emissions into the atmosphere and an annual saving of 35,739.5 €, which means a saving of 72.78% with respect to the previous fuel oil installation. A sensitivity analysis shows that fuel cost of base case is the variable with the most sensitivity changing the initial cost and net present value (NPV)

Wave energy resource assessment at southern coast of the Gulf of Mexico

Find alternative energy sources is one of the challenges that came with XXI century and this paper makes an analysis about wave energy, which presents several advantages over fossil based energy and even other renewable energy sources. Among them are its low environmental impact and its high energy density. Wave energy is beginning to be considered as an important and promising renewable resource in many countries. The objective of this paper is to evaluate the wave energy potential at the southern coast of the Gulf of Mexico; the sea states were observed and was obtained that the available mean wave power is 55.91 W/m. In addition, this paper shows that, in the study site, the most energetic season is fall and the less energetic season is spring. This differs from the global trend, were the most energetic season is winter, and the less energetic season is spring

Renewable Energies in the Agricultural Sector: A Perspective Analysis of the Last Three Years

Renewable energy arises as a tool for the supply of energy to the agriculture sector. Currently, there is a growing concern for the environment. This circumstance has led to technological progress in energy use in relation to natural resources and their availability for all productive sectors, including agriculture. The main objective of this work is to perform analysis from a bibliometric point of view and to analyze scientific advances in renewable energy and agriculture worldwide that have occurred in the last three years (2019–2021). The purpose of this study is to provide an overview of the last three years on the topic in order to contribute to the international scientific community, specifically towards collaboration between authors, institutions, and countries. A keyword analysis using community detection was applied to detect the five main clusters of this research and was largely dedicated to the following topics: renewable energy technologies in agriculture, bioenergy, sustainable agriculture, biomass energy, and the environmental impact of agriculture. The main countries found to be conducting research on renewable energy and agriculture include India, China, the United States, Italy, the United Kingdom, Poland, Indonesia, Germany, the Russian Federation, and Spain; the most important institutions conducting research in this area include the Ministry of Agriculture of the People’s Republic of China, the Tashkent Institute of Irrigation and Agricultural Mechanization Engineers at the National Research University in Uzbekistan, the Chinese Academy of Agricultural Sciences, and the Grupo de Investigação em Engenharia e Computação Inteligente para a Inovação e o Desenvolvimento in Portugal. These results may contribute to the identification of new research needs and therefore to the development of future directions of research on renewable energies in the agricultural sector