Super-capacitor energy storage system to recuperate regenerative braking energy in elevator operation of high buildings

<span>In operating phases of elevators, accelerating, braking modes occur frequently, so braking energy recuperation of elevators has contributed considerably to decrease the total electric energy consumption for operating elevators in multi-floor buildings. In this paper, the supercapacitor energy storage system is used to recover regenerative braking energy of elevators when they operate down full-load and up no-load, reducing fluctuation of voltage on DC bus as well. Therefore, super-capacitor energy storage system (SCESS) will be parallel with line utility to recuperate regenerative braking energy in braking phase and support energy for acceleration phase. The surplus energy will be stored in the supercapacitors thanks to a DC-DC converter capable of exchanging energy bidirectionally in buck/boost modes, and designing control strategy including two control loops. Inner loop-current loop: controlling charge/discharge process of supercapacitors by current iL complying with operation characteristic of elevator; Outer loop-voltage loop: managing UDC-link at a fixed value. Simulation results with elevator system of the ten-floor building, Hanoi, Vietnam installed SCESS have been verified on MATLAB Simulink, SimPowerSystem with saving energy level about 30%.</span>

Analysis of Electric Energy Consumption Profiles Using a Machine Learning Approach: A Paraguayan Case Study

Correctly defining and grouping electrical feeders is of great importance for electrical system operators. In this paper, we compare two different clustering techniques, K-means and hierarchical agglomerative clustering, applied to real data from the east region of Paraguay. The raw data were pre-processed, resulting in four data sets, namely, (i) a weekly feeder demand, (ii) a monthly feeder demand, (iii) a statistical feature set extracted from the original data and (iv) a seasonal and daily consumption feature set obtained considering the characteristics of the Paraguayan load curve. Considering the four data sets, two clustering algorithms, two distance metrics and five linkage criteria a total of 36 models with the Silhouette, Davies–Bouldin and Calinski–Harabasz index scores was assessed. The K-means algorithms with the seasonal feature data sets showed the best performance considering the Silhouette, Calinski–Harabasz and Davies–Bouldin validation index scores with a configuration of six clusters.

Financial Viability of a Photovoltaic System: the case of University Hospital at the UFSCar/Brazil

Considering the negative consequences of the excessive use of non-renewable energy and the development of technologies related to photovoltaic energy, the present paper aims to analyze if the photovoltaic systems are economically viable for university hospitals. A photovoltaic system was designed in the parking lot of the University Hospital of the Federal University of São Carlos (UFSCar) and analyzed the financial viability of its installation. As a result, the photovoltaic system is financially viable, with an expected generation of 194.2 MWh in the first year and a payback of 7 years. Thus, this paper contributes to the feasibility of photovoltaic projects in university hospitals and the reduction of electric energy consumption, reducing its operational costs, reducing the emission of pollution, and diversification of the Brazilian energy matrix. Furthermore, the results can be used as a scientific basis for other fields, such as public and private hospitals and clinics.

Implementation of a Floating Head Pressure Condensation Control to Reduce Electrical Energy Consumption in an Industrial Refrigeration System

The growing global demand for energy and the costly taxes on electric energy demonstrate the importance of seeking new techniques to improve energy efficiency in industrial facilities. Refrigeration units demand a large amount of electricity due to the high power needs of the components of the system. One strategy to reduce the electric energy consumption in these facilities is pressure condensation control. The objective here was to develop a logical control model where the physical quantities in the thermodynamic process can be monitored and used to determine the optimum point of the condensation pressure and the mass flow rate of the air in the evaporative condenser. The algorithm developed was validated through experiments and was posteriorly implemented in an ammonia industrial system of refrigeration over a period of sixteen months (480 days). The results showed that the operation of the evaporative condenser with a controlled air mass flow rate by logical modeling achieved a reduction of 7.5% in the consumption of electric energy, leading to a significant reduction in the operational cost of the refrigeration plant.

Controlling Volatility of Wind-Solar Power In Germany

The main advantage of wind-solar power is the electric power production free of CO2. Its main disadvantage is the huge volatility of the system [national electric energy consumption powered by wind-solar power]. In fact, if this power production, averaged over one year, corresponds to the averaged electric consumption and is intended to replace all other electric power generating devices, then controlling the volatility of this system by using storage alone requires huge capacities of about 30TWh, capacities not available in Germany. However, based on German power data over the last six years (2015 till 2020) we show that the required storage capacity is decisively reduced, provided i) a surplus of wind-solar power is supplied, ii) smart meters are installed, iii) a different kind of wind turbines and solar panels is partially used, iv) a novel function describing this volatile system, is introduced. The new function, in turn, depends on three characteristic numbers, which means, that the volatility of this system is characterized by those numbers. When applying our schemes the results suggest that all the present electric energy in Germany can be obtained from controlled wind-solar power. And our results indicate that controlled wind-solar power can produce the energy for transportation, warm water, space heating and in part for process heating, requirering an increase of the electric energy production by a factor of 5. Then, however, a huge number of wind turbines and solar panels is required changing the appearance of German landscapes fundamentally.

Comparison of Single- and Multipipe Earth-to-Air Heat Exchangers in Terms of Energy Gains and Electricity Consumption: A Case Study for the Temperate Climate of Central Europe

Earth-to-air heat exchangers (EAHEs) can be used in the ventilation systems of various types of buildings. Multipipe structures can be found in large-volume buildings, yet scientific analysis of such systems is rare. Annual energy gains and electricity consumption for equivalent single-pipe and multipipe systems are typically not available. This paper bridges this gap, presenting the results of experimental studies on pressure losses in three-, five- and seven-pipe EAHEs and analysis for the annual energy gains and electric energy consumption as compared to a single-pipe exchanger. The results showed that the multipipe EAHE can be successfully replaced by a single-pipe structure with the same thermal performance and similar pressure losses if a tube with the appropriate diameter is used. However, multipipe heat exchangers can also use pipes of larger diameter (manifolds and/or branches), which improves their energy efficiency and may then make them more advantageous than single-pipe structures. From this reason, ultimately, the final selection of exchanger geometry should take into account economic and environmental issues and also user preferences and their importance in the hierarchy.

Calculation of specific rates of the electric energy consumption at frequency regulation of electric drives: A case study of pumping stations

The issues of developing a methodology for calculating the specific rates of electrical energy consumption during frequency regulation of electric drives of pumping stations are considered. When calculating specific consumption rates, experimental studies were carried out at the Chirchik pumping station. When developing the methodology, technological, design parameters, water consumption, as well as the total capacity of pumping units based on frequency-controlled electric drives are taken into account. At the same time, the characteristics of the main parameters that must be taken into account when choosing variable frequency drives for pumping units are determined.

Assessment of the impact of the main technological characteristics of wells on the power consumption of pumps

The issue of assessing the impact of the main technological characteristics of wells on the power consumption of pumps is one of the important issues. Based on the analysis of the data obtained in the article, the electric energy consumption of the well pump device the rotational speed of the pump (co); the density of the solution (liquid) (p); the pressure generated by the pump (H); the performance of the pump aggregate (q); depth of the well (H); hydrodynamic resistance (dp); Also, on the basis of the STATISTICA program, the calculation work is carried out, the binding function of the pumps is determined to what extent the factor affects the electricity consumption, and is described in the Pareto diagram.

Long Short-Term Memory Network-Based Metaheuristic for Effective Electric Energy Consumption Prediction

The Electric Energy Consumption Prediction (EECP) is a complex and important process in an intelligent energy management system and its importance has been increasing rapidly due to technological developments and human population growth. A reliable and accurate model for EECP is considered a key factor for an appropriate energy management policy. In recent periods, many artificial intelligence-based models have been developed to perform different simulation functions, engineering techniques, and optimal energy forecasting in order to predict future energy demands on the basis of historical data. In this article, a new metaheuristic based on a Long Short-Term Memory (LSTM) network model is proposed for an effective EECP. After collecting data sequences from the Individual Household Electric Power Consumption (IHEPC) dataset and Appliances Load Prediction (AEP) dataset, data refinement is accomplished using min-max and standard transformation methods. Then, the LSTM network with Butterfly Optimization Algorithm (BOA) is developed for EECP. In this article, the BOA is used to select optimal hyperparametric values which precisely describe the EEC patterns and discover the time series dynamics in the energy domain. This extensive experiment conducted on the IHEPC and AEP datasets shows that the proposed model obtains a minimum error rate relative to the existing models.

Evaluation of Home Energy Efficiency Improvements in a Hot Desert Climate in Northwestern Mexico: The Energy Saving vs. Money Saving Conflict

Reducing household energy consumption is one of the most important strategies used to decrease fossil fuel consumption and greenhouse gases emissions, and to encourage renewable energy utilization. Most energy conservation strategies in the domestic sector are aimed at preferential loans, i.e., purchasing renewable electricity or to improve the efficiency of home appliances, such as air conditioning and lighting. However, despite the relative economic successes of these technologies, they have not had expected impacts in regard to energy consumption. In this work, the authors analyzed the consumption patterns of two equivalent households—one was adapted with improved thermal insulation and a 1.2 kW photovoltaic system to reduce consumption from the electrical grid. The results show that dwellings where no improvements were made registered lower electric energy consumption, due the fact that users were aware that no strategy had been implemented, and its consumption; hence, electricity payments depended solely on one’s attention over the electronic device operations. On the other hand, energy conservation strategies in households promotes confident and relaxed attitudes toward the use of energy, leading to lower energy billings, but a higher gross energy consumption.