Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers

Microgrids, comprising distributed generation, energy storage systems, and loads, have recently piqued users’ interest as a potentially viable renewable energy solution for combating climate change. According to the upstream electricity grid conditions, microgrid can operate in grid-connected and islanded modes. Energy storage systems play a critical role in maintaining the frequency and voltage stability of an islanded microgrid. As a result, several energy management systems techniques have been proposed. This paper introduces a microgrid system, an overview of local control in a microgrid, and an efficient EMS for effective microgrid operations using three smart controllers for optimal microgrid stability. We designed a microgrid consisting of renewable sources, Li-ion batteries, the main grid as a backup system, and AC/DC loads. The proposed system control was based on supplying loads as efficiently as possible using renewable energy sources and monitoring the battery’s state of charge. The simulation results using MATLAB Simulink demonstrate the performance of the three proposed microgrid stability strategies (PID, artificial neural network, and fuzzy logic). The comparison results confirmed the viability and effectiveness of the proposed technique for energy management in a microgrid which is based on fuzzy logic controllers.

Informational aspects at model of power consumption by main drainage facilities of iron-ore mining enterprises

The work investigates into variable informational approaches to modeling power consumption by main drainage facilities of ore mining enterprises with underground mining method. Methodological recommendations for using the models are also designed. The research deals with general methodological approaches to model formation with both power consumption indices for drainage facilities and corresponding costs. Logistics of model formation is substantiated, namely, combination of classic multifactor regression modeling with modern digital modeling methods – automated control systems used for drainage facilities. Principles of building fuzzy logic controllers and algorithms of their functioning under multichannel control are determined in detail. The improved fuzzy logic-based variant is proposed and combined, with correlation analysis, to provide the basis for developing algorithms of the automated control systems of electric power consumption. There is an example of developing a “road map” for implementing a generalized algorithm for automated control systems power flows for two current cases – a selective tariff with limited daily contract-based power consumption and that with a variable tariff. It is established that application of the two-rate hourly tariff with its conditional distribution (Night/Peak) instead of the three-rate tariff (Night/Half-Peak/Peak) on a single-use basis leads to a thirteen percent increase of daily power costs with a single-channel control of the ore flow and a seven percent increase with two-channel control (ore flow and drainage simultaneously). The use of fuzzy logic controllers enables minimizing these losses.

Performance of Trainers kits for Industrial Automation Based on Programmable Logic Controllers

The objectives of this study include: (1) get results; and (2) know the performance of trainer kits for industrial automation based on Programmable Logic Controllers (PLC). The type of research is research and development that refers to the ADDIE model according to Robert Maribe Branch. Research steps include: Analyze, Design, Develop, Implement, and Evaluate. Data obtained through observation, interviews, and questionnaires, using instruments in the form of observation sheets, interview guidelines, and questionnaires. Data were analysed descriptively. The results showed that: (1) A PLC-based industrial automation trainer kit has been developed in the form of simulation of drilling objects, spraying paint on objects, applying stamps, and moving objects manually and automatically; and (2) PLC-based industrial automation trainer kit products have good performance, which is shown that 100% of the important components can work properly, and all job descriptions (100%) of the trainer kits can work as their function.

Closed Loop V/f Speed Control of Multilevel Inverter Fed Induction Motors Using PID and Fuzzy Logic Controllers

The Volts per Hertz (V/f) speed control method makes induction motors available to be used in variable speed applications. However, the great harmonic distortion in supply voltage is a major issue of this method. Therefore, this study focuses on decreasing the harmonic distortion in the supply to induction motors. For that, the use of thirty-one-level multilevel inverters (MLIs) is investigated. Another drawback of the V/f speed control method is the use of proportional-integral-derivative (PID) controllers as speed controllers, which are difficult to be tuned precisely. To overcome this, the use of fuzzy logic controllers is investigated. The whole model is developed and simulated in MATLAB/SIMULINK by varying two variables, i.e., reference speed and load torque, one at a time using each controller. The observations for the changes in speed, torque, stator current, and supply voltage to the induction motors are made. The system’s performance using fuzzy logic controllers is found superior.

PLCrypto: A Symmetric Cryptographic Library for Programmable Logic Controllers

Programmable Logic Controllers (PLCs) are control devices widely used in industrial automation. They can be found in critical infrastructures like power grids, water systems, nuclear plants, manufacturing systems, etc. This paper introduces PLCrypto, a software cryptographic library that implements lightweight symmetric cryptographic algorithms for PLCs using a standard PLC programming language called structured text (ST). To the best of our knowledge, PLCrypto is the first ST-based cryptographic library that is executable on commercial off-the-shelf PLCs. PLCrypto includes a wide range of commonly used algorithms, totaling ten algorithms, including one-way functions, message authentication codes, hash functions, block ciphers, and pseudo-random functions/generators. PLCrypto can be used to protect the confidentiality and integrity of data on PLCs without additional hardware or firmware modification. This paper also presents general optimization methodologies and techniques used in PLCrypto for implementing primitive operations like bit-shifting/rotation, substitution, and permutation. The optimization tricks we distilled from our practice can also guide future implementation of other computationheavy programs on PLCs. To demonstrate a use case of PLCrypto in practice, we further realize a cryptographic protocol called proof of aliveness as a case study. We benchmarked the algorithms and protocols in PLCrypto on a commercial PLC, Allen Bradley ControlLogix 5571, which is widely used in the real world. Also, we make our source codes publicly available, so plant operators can freely deploy our library in practice.