The advance of the distributed generation in Brazil makes it essential to investigate the applications and transformations that the use of these new arrangements may entail. The use of non-centralized generation technologies associated with energy storage is interesting for several sectors of the energy market, even if the market is in the process of maturing with these technologies. In the context of the time-of-use rate, these changes have allowed the consumer to use strategies to save energy bills costs,especially when its moment of most considerable consumption coincides with that of the highest tariff. In this paper, a Battery Energy Storage System (BESS) is used to perform commercial peak load reduction in a microgrid in connected mode. The microgrid also has a Photovoltaic (PV) Generator Farm as Renewable Energy Sources (RES) to provide load consumption and also to assist BESS in the peak shaving operation. The modeling and simulation of the system are performed by MATLAB/Simulink. The analysis demonstrates that the peak load reduction produces the expected financial benefits under a Brazilian time-of-use rate known as White Rate, in addition to carrying out the operation in a manner consistent with the technique from an electrical point of view. The software Homer Grid validates the potentials savings. Thus, the results showed that the use of energy storage associated with renewable generation under a peak shaving strategy allows greater freedom for the consumer in the face of costs with main grid purchases.

A crucial way to reach future sustainable society concern the path towards nearly-zero energy buildings because of large amount of energy at stake. The present work proposes an approach for the optimal integration of small-scale technologies (renewable and traditional) to enhance the pathway of existing and inefficient buildings towards low-carbon system in a cost-benefit effective manner. Operation optimization as well as an innovative combined design and operation optimization are investigated with the goal of selecting the capacity of the technologies to be installed depending on the expected operations. The renewable technologies are integrated with proper storage units, such as batteries and latent thermal storage, which allows reducing the space required for the installation. Two different non-linear programming approaches are used with the aim of finding an optimal solution. The optimization allows reducing operation costs of 22% for RES fed dwellings. The combined operation and design optimization leads to a reduction of installation and operating costs of 7%. In the analyzed case, the adoption of the advanced optimization approach shows that latent heat storage is more suitable to be installed than electric storage (−2.5% cost).

The State-of-Charge (SOC) real-time estimation plays an essential role in effective energy management. This paper proposes the use of an Artificial Neural Network (ANN) to design a state of charge estimator for a Graphite/LiCoO2 lithium-ion battery pack. The software MATLAB was used to develop and test several network configurations to find the ideal weights to perform the ANN. Results demonstrate that the Mean Squared Error (MSE) achieved rendered the ANN as an effective technique. Thus, it predicted the battery bank’s SOC values with accuracy using only voltage, current, and charge/discharge time as input.

To meet the global demand of energy requires an alternative source preferably with less concern of climate change. Biochar production from agricultural biomass waste by pyrolysis, deals a unique solution for producing a useful source of green energy. Biochar is carbon rich product with high heating value which is comparable with our primary energy sources (fossils fuels). Biochar can be utilized for various purposes such as energy production, soil enhancement and etc. Biochar can be more suitable for steelmaking, in view of their chemical and thermo-chemical characteristics including low ash, higher heating values (HHV), high surface area, etc. Biochar also can be selectively utilised selectively for soil amelioration, C-sequestration, and waste water treatment, in view of the suitability of their characteristics (such as higher values of pH, mineral content and surface area, etc.) for meeting the requirements for a particular purpose. This study associates the characteristics of biochar produced by slow pyrolysis at 800 °C for two biomass residues: corn cob and coconut shell. These results can be used to establish ideal utilization means of biomass for energy and/or biochar production.

The purpose of the work is to determine factors internal and external affecting the cooling energy demand of the building. During the research, the impact of weather conditions and the level of hotel occupancy on cooling energy, which is necessary to obtain indoor comfort conditions, was analyzed. The subject of research is energy consumption in the Turówka hotel located in Wieliczka (Southern Poland). In the article, the designer of neural networks was used in the Statistica statistical package. To design the network, a widely-used multilayer perceptron model with an algorithm with backward error propagation was used. Based on the collected input and output data, various MLP networks were tested to determine the relationship most accurately reflecting actual energy consumption. Based on the results obtained, factors that significantly affect the consumption of thermal energy in the building were determined and a predictive energy demand model for the analyzed object was presented. The result of the work is a forecast of cooling energy demand, which is particularly most important in a hotel facility. The prepared predictive model will enable proper energy management in the facility, which will lead to reduced consumption and thus costs related to facility operation.

The building sector plays a vital role in Switzerland’s climate policy. In order to support the energy transition in the building sector, Rolle, a suburban area located along the shore of Lake Geneva is considered in this study to understand the promising future scenarios for integration of renewable energy technologies. The area is clustered into 12 clusters and distributed energy system is designed for each cluster. Subsequently, three energy systems having contrasting densities are taken for further comparison to understand the impact of urban density on the design of the distributed energy system. The study reveals that urban density will influence the peak as well as the annual energy demand of the energy hubs. The study reveal that the energy technologies used in the energy hubs are strongly influenced by the capacity of the system (peak and annual energy demand). Energy systems having higher capacities are less sensitive to the market changes when compared to the systems having lower capacities (leading to sparse suburban areas).

This study addresses passive adaptation strategies to reduce the effects of global warming on housing, focusing on low-income houses, for which passive adaptation strategies should be prioritized, aiming for environmental sustainability. The passive strategy chosen is thermal mass for cooling, through the adoption of earth-sheltered walls in contact with the ground. Thus, the goal of this study is to evaluate the thermal load and thermal impact of implementing a thermal mass strategy for cooling, using bermed earth-sheltered walls in bedrooms, for a building located in a tropical climate region. For that, a base scenario (1961–1990) is considered alongside two future scenarios: 2020 (2011 to 2040) and 2050 (2041 to 2070), both considering the effects of climate change, according to the Fourth Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The methodologies adopted are (i) the computational simulation of the annual thermal load demand and (ii) the quantification of the Cooling Degrees-Hours (CDH) with the subsequent comparative analysis. The results show that in both the 2020 and 2050 scenarios there will be an increase in the thermal loads for cooling and the CDH, regardless of using a bermed earth-sheltered wall. Nonetheless, it is shown that this passive strategy works as a global warming adaptation measure, promoting building sustainability in tropical climate regions.

In recent years the climate change issue, coupled with the concern of resource depletion, are favouring the blossoming of renewable energy conversion systems. Particularly, the development of new technologies for the combustion of biomass, have drawn a special attention to the possibility of coupling thermoelectric modules with stove-fireplaces. The current thermoelectric generators have many attractive points, such as a solid structure, absence of noise, and no maintenance required, however, due to their very low efficiency (4–8%), they are still economically non-attractive. However, if the modules are applied to a heat source, which otherwise would be wasted, the interest of the solution certainly grows. In this study an exergy analysis of a stove-fireplace coupled with thermo-electric modules is performed, with the aim of identifying the critical issues of the overall system. The obtained exergy efficiency of the whole system resulted to be of 36.2%. A sensitivity analysis on the main parameters affecting the second law efficiency of the system (such as number of cells, dimension of the stove fireplace, heat input ...) is also carried out.

Atmosphere is one of the most significant factors in the thermal decomposition of biomass. In domestic or industrial biomass boilers, ambient oxygen concentration varies along the time which means that the reaction will change from pyrolysis to combustion. In this way, to analyze and compare each thermochemical conversion processes a simple analytical method, the non-isothermal thermogravimetric analysis, is carried out under oxidative (air) and non-oxidative (argon) environments at 10 °C/min and as a function of different flow rates (2 to 150 mL/min). Additionally, this work was complemented by a kinetic analysis considering a first-order reaction to each conversion stage and using the Coats-Redfern method. The effect of the atmosphere on the thermal decomposition behavior was evident. It was observed that the thermal decomposition of pine wood particles varied from three to two stages when the oxidative or inert atmosphere was applied. The presence of oxygen changes the mass loss curve mainly at high temperature, around 350 °C, where char reacts with oxygen. The maximum mass loss rate from experiments with the oxidative atmosphere is 15% higher than in an inert atmosphere, the average char combustion rate is approximately 5 times higher and the heat released reaches 3.44 times higher than in an inert atmosphere. Ignition and combustion indexes were also defined and its results revealed that particles are ignited faster under oxidative atmosphere and, on average the combustion index is 1.7 times higher which reinforces the more vigorously way that the samples are burned and how faster char is burned out in the experiments with air. Regarding the kinetics analysis, higher activation energies and, consequently, lower reactivity was obtained under the oxidative atmosphere for the second stage (~125 kJ/mol) and under the inert atmosphere for the third thermal conversion stage(~190 kJ/mol).

This paper explores the advantages of using relative free energy instead of exergyto build a mathematical theory of thermodynamic costs to diagnose malfunctions in thermalsystems. This theory is based on the definition of a linearized characteristic equation that representsthe physical behavior of each component. The physical structure of the system described by itsenergy interrelationships is called “primal”, and its derivatives are the costs and consumptions.The obtained costing structure is the mathematical “dual” of its primal. The theory explains whythe F and P cost assessment rules and any other suggestion may (or may not be) rational under a givendisaggregation scheme. A result of the theory is a new thermodynamic function, called the relative free energy, and a new parameter called deterioration temperature due to a component’s deteriorationcause, characterized by a h-s thermodynamic trajectory describing the effects on the exiting stream.The relative free energy function allows for an exact relationship between the amount of usedresources and the increase in entropy generation caused by the deterioration path of the component.This function allows the obtaining of, for the first time, an appropriate characteristic equation fora turbine and a new definition of efficiency that does not depend on the environment temperaturebut on its deterioration temperature. Also, costing with relative free energy instead of exergy mayopen a new path for more precise and straightforward assessments of component deteriorations.