This research demonstrates the possibility and expediency of forming local electric energy systems (LEESs) based on renewable sources of energy (RSE) as balancing groups in the electric power system (EPS), which can maintain efficiency and provide power supply to consumers in an autonomous mode. The LEES is a part of the EPS of thermal and nuclear power plants and is considered as a separate balancing group. LEESs are designed in such a way that they can operate autonomously in both normal and extreme conditions in the EPS. The sources of electricity in LEESs are small hydroelectric power plants (SHPPs), photovoltaic power plants (PVPPs), and wind power plants (WPPs), whose electricity generation is unstable due to dependence on natural conditions. Therefore, the structure of a LEES with RSE includes an energy storage system with reserves sufficient to compensate for the unstable generation and balancing of the mode. LEESs can differ significantly in terms of key technical and economic indicators (power supply reliability, power losses, and power quality), and therefore, it is necessary to choose the optimal one. It is not advisable to optimize the quality of power supply in a LEES by individual indicators, as improvement of one indicator may lead to deterioration of another. The functional readiness of a LEES should be assessed by the quality of operation, which depends on reliability, power losses, and power quality. To simplify the task of assessing the quality of operation, which is a vector optimization problem, a method for determining the integral indicator as a number that characterizes the LEES and reflects the compromise between the values of reliability, power losses, and power quality has been developed. The integral indicator of the functioning of complex systems is based on a combination of the theory of Markov processes and the criterion method of similarity theory. The value of the integral indicator of the quality of operation of the LEES allows for comparing different variants of power transmission and distribution systems without determining individual components of technical and economic indicators—reliability, power losses, and power quality. The offered integral indicator of the quality of functioning of a LEES with RSE corresponds to the general requirements for such indicators. It reflects the actual operating conditions; allows for assessing the efficiency, quality, and optimality of power supply systems; and can be easily decomposed into partial indicators.

This paper presents a fiber-optic sensor with intensity demodulation for simultaneous measurement of dynamic transverse force and axial strain. The sensor uses a Sagnac loop filter with a polarization-maintaining photonic crystal fiber (PM-PCF) that is subjected to a dynamic transverse force. The Sagnac loop filter is illuminated by the reflected beam froma uniform fiber-optic Bragg grating (FBG), which is subjected to an axial strain. This way, intensity demodulation is performed in the sensor, enabling it to measure two quantities simultaneously: the dynamic force and the strain. Experimental results show that the sensor achieves a sensitivity to the dynamic transverse force of 38.1 mV/N and a sensitivity to the axial strain of 0.527 mV/με, while the nonlinearity errorsare 4.9% for the dynamic force and 0.9% for the strain. The sensor exhibits low temperature sensitivity due to partial self-compensation of the temperature coefficients of the Sagnac loop filter with the polarization-maintaining photonic crystal fiber and the fiber Bragg grating.

The article discusses the formation of local electric energy systems (LEES) based on renewable energy sources (RSE) as balancing groups in the electric power system (EPS). These systems can function autonomously, providing electricity even in extreme conditions. LEES incorporate small hydroelectric, photovoltaic, and wind power plants, whose output is unstable due to varying natural conditions. To address this, energy storage systems are included to ensure stability and balance. LEES may vary significantly in terms of reliability, power losses, and quality, making it essential to choose the optimal configuration. Optimizing power supply by focusing on individual indicators is discouraged, as it may negatively affect others. To evaluate LEES performance, an integral indicator has been developed, combining the theory of Markov processes and similarity. This indicator compares actual performance with an "ideal" standard, simplifying the assessment of complex systems. It allows comparison of different transmission and distribution options without needing to evaluate all technical and economic details. The proposed integral indicator effectively reflects real operating conditions and assesses the efficiency, quality, and optimality of power supply, while remaining adaptable to partial indicators.

This paper presents a simulation study of the simultaneous reconstruction of the non-smooth strain distribution of an optical fiber Bragg grating and its temperature, which is based on the reflection spectrum of the reflected beam of the grating. The transition matrix method was used to model the reflection spectrum of the grating, and the nonlinear Nelder-Mead optimization method was used to simultaneously reconstruct the strain distribution along the grating and its temperature. The results of simulations of simultaneous reconstruction of the strain profile and temperature indicate good accord with the strain profiles and temperature set. The reconstruction errors of the strain profiles are less than 1.2 percent and the temperature change errors are less than 0.2 percent, with a noise level of 5 percent.