This paper discusses energy management in the formation process of lead acid batteries. Battery production and electricity consumption in during battery formation in a battery plant was analyzed over a 4 year period. The main parameters affecting the energy performance of battery production were identified and different actions to improve it were proposed. Furthermore, an Energy Performance Indicator (EnPI), based on the electricity consumption of battery formation (a difficult and rather expensive parameter to measure), is introduced to assess its energy efficiency. Therefore, a Soft Sensor to measure the electricity consumption in real-time (based on the voltage and current measured during battery formation), and to calculate the EnPI is developed. Moreover, Energy Management (EM), aided by the use of energy baselines and control charts is implemented to assess the energy performance of battery formation, allowing the implementation of rapid corrective actions toward higher efficiency standards. This resulted on the average in a 4.3% reduction of the electricity consumption in battery formation.
The aim of this study is to improve energy performance at a battery factory in Colombia by introducing the energy management approach defined in ISO 50001. In the study, the main energy consumptions were identified in the battery formation, the compressed air system and the large electric motors. An energy review was performed in the factory using measurement equipment and statistical techniques. Different actions were proposed to improve energy performance. As a result, a 3.48% reduction in electricity consumption was achieved during the implementation of the proposed measures.
this paper presents a prediction model of solar radiation for dimensioning photovoltaic generation systems in the Atlantic Coast of Colombia, using artificial neural networks. As a case of study is presented the municipality "El Carmen de Bolivar" located in this region. To obtain the model, the average data of daily temperature, relative humidity and solar radiation from the last ten years, reported by weather stations in this city were used. Six neural networks were designed with six variants of input variables (temperature, humidity and month) and the output variable (solar radiation). The best result was obtained using all input variables. In the training process, the correlation index (R) between solar radiation estimated by the model and the recorded data was 0.8. In validating the correlation index was 0.77.
Currently, the data and variables of a control system are the most important elements to be safeguarded in an industrial network, so it is vitally important to ensure their safety. This paper presents the design and simulation of a demilitarized network (DMZ) using firewalls to control access to all the information that is stored in the servers of the industrial network of the Hermanos Díaz Refinery in Santiago de Cuba, Cuba. In addition, the characteristics, configurations, methods, and rules of DMZs and firewalls are shown, select the configuration with three multi-legged firewalls as the most appropriate for our application, since it allows efficient exchange of data guaranteeing security and avoiding the violation of the control system. Finally, the simulation of the proposed network is carried out.
<span lang="EN-US">As modern control systems are becoming more complex, and the implemented technology more sophisticated, the importance of the different characteristics of those systems, such as reliability, availability, security, and protection, is increasing. In this article, an automation design for the air conditioning system of classified areas of the Parenteral solutions plant of the eastern pharmaceutical laboratory company of Santiago de Cuba province, Cuba, is proposed because there is a lack of optimal environmental conditions for development and production of pharmaceuticals at a large scale. The proposal is focused on the design of a supervision system and automatic control of the environmental variables that influence the drug production process. The entire algorithm for the design was developed to monitor critical and non-critical variables and control values of temperature, relative humidity, differential pressure, and air velocity according to standards established by pharmaceutical companies. The design of the automation system includes, apart from the control and supervision algorithm for operation efficiency, the necessary instrumentation.</span>
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