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Comparative computational analysis of the selection of battery energy storage for civil objects and parking with photovoltaic plants

Zinkevych Petro, Baliuta Serhii, Kuievda Iuliia

Journal of New Technologies in Environmental Science

2023

Vol. 7, nr 1

16--23

One of the disadvantages of solar power plants is that they do not produce electricity at night, so they cannot support the load of consumers. One of the reliable methods of increasing the efficiency of the use of photovoltaic power station (PPS) for consumers is the installation of energy storage. This study aims to investigate the efficiency of using a battery energy storage system (BESS) that is designed to power a civil facility and a parking lot. This study presents a feasibility analysis of BESS using System Advisor Model (SAM) software. The following objects were chosen as objects of research: a cottage; 19-story residential building with built-in non-residential premises (BNP); 9th floor parking lot for 979 cars. These facilities have solar power plants installed on the roof. BESS is planned to be used for power supply of the entire facility and power consumers. For the existing PPS, taking into account the peak load, the selection of the storage energy and modeling of the system operation modes was performed. The modes of use of the usage accumulator have been studied. The most effective mode of operation is mode 1, which involves charging the electricity storage during the day, and feeding the load in the evening. It is advisable to use this mode throughout the year. Mode 2 should be used to cover the load only during the spring-winter-autumn period, when the electricity generation from the FES is not sufficient. The simulation results showed that BESS has the highest economic efficiency for the electricity supply of BZB with a payback period of 10.5 years with a battery utilization efficiency of 96.49%.

Forecasting the electricity generation of photovoltaic plants

Kuievda Iuliia, Baliuta Serhii, Zinkevich Petro, Stoliarov Oleksandr

Journal of New Technologies in Environmental Science

2021

Vol. 5, nr 1

40--45

Due to the need in accordance with Ukrainian legislation to submit a day-ahead hourly forecast of electricity generation of solar power plants, the problem of forecasting model quality becomes very important. In the study it is proposed a method of choosing the optimal structure and sensitivity assessment of ANFIS-based forecasting model. In the model the input is solar irradiance, the output is solar panel generation power. The method is based on computational procedures using MATLAB software. For the data set, used in the study, the results, optimal for normalized mean absolute error (NMAE), were achieved on 5 triangular input member functions (trimf), while the error varied within 0.23% depending on number and shape of input member functions. According to the calculations of input error sensitivity of the forecasting model with 5 input trimf membership functions, the increasing of input error up to 8.19% NMAE leads to the raising of the output error in the testing sample up to 5.78%, NMAE. The rather low sensitivity of the model to the input data error allows us to conclude that forecasted meteorological data with a pre-known fixed forecast error can be used as input data.