Power Plant Production Research Articles

Proposing a neuro-fuzzy controller to compensate for the effect of disturbances on the MED-TVC desalination system

Due to climate changes and disturbances in the steam production of power plants, multi-effect desalination (MED) plants are facing two possible disturbances: pressure change in motive steam (MS) and temperature change in seawater. Therefore, a controller is needed to compensate for these disturbances. However, the dynamics of these systems are highly nonlinear. Hence, a Takagi-Sugeno-Kang Fuzzy Logic Controller (TSKFLC) is designed for a MED-TVC1 on an industrial scale with four effects, and a condenser. This novel model-free controller is designed by training a neuro-fuzzy network using an input-output dataset extracted from an experimentally validated mathematical model that considers the ejector malfunctions. Hence, the dynamics of the system is fully considered in the controller because it is trained by its own input-output dataset. The controller performance in the first effect brine level regulation as the output of the closed-loop system is investigated in facing changes in the motive steam pressure (MSP) and inlet seawater temperature (SWT) as the main disturbances to prevent the phenomenon of flooding or emptying and possible damages. The behaviors of the open-loop and closed-loop systems in the presence of these disturbances are investigated. Simulation results show that the proposed multi-input-single-output (MISO) controller is so fast in facing disturbances. According to the results, by increasing MSP to 25 bar, it can be seen that the level of brine in the first effect decreased sharply, and the whole space is filled with vapor, which this phenomenon is called emptying. On the other hand, by decreasing the pressure, the level of brine reached 47.65 cm which is fourth times higher than the steady mode, and it brings a new phenomenon called flooding. Moreover, simulation results show that MSP has a higher impact compared to SWT. Also, according to the results, the system needs only 400 s to reach a stable situation showing the fast performance of the neuro-fuzzy controller facing disturbances.

AT-DBN: A Novel Deep Learning Approach for Accurate Flue Gas Pressure Forecasting in Power Plants

Accurately predicting and controlling the flue gas pressure at the induced draft fan inlet is crucial for environmental protection and boiler efficiency. This study designed a model of Attention-enhanced Deep Belief Network (AT-DBN) to predict the flue gas pressure parameters at the induced draft fan inlet, based on key improvements to the Deep Belief Network (DBN). The main improvement involves introducing an attention mechanism to enhance the prediction accuracy of the model for the flue gas pressure parameters at the induced draft fan inlet. The study begins with meticulous preprocessing of historical operational data, including identifying and removing outliers to ensure data quality for subsequent analysis. Next, Pearson correlation analysis is employed to systematically evaluate the correlation between various variables and the flue gas pressure, thereby identifying key variables that significantly affect prediction performance. Finally, an attention mechanism is integrated into the traditional DBN architecture, aiming to enhance the network’s ability to perceive important information within the input features, thereby improving prediction accuracy and model generalization. The results demonstrate that the proposed AT-DBN model can accurately predict the flue gas pressure at the induced draft fan inlet across multiple test sets, providing valuable guidance for power plant production operations.

Effect of Solar Irradiation Inter-Annual Variability on PV and CSP Power Plants Production Capacity: Portugal Case-Study

The sizing of solar energy power plants is usually made using typical meteorological years, which disregards the inter-annual variability of the solar resource. Nevertheless, such variability is crucial for the bankability of these projects because it impacts on the production goals set at the time of the supply agreement. For that reason, this study aims to fill the gap in the existing literature and analyse the impact that solar resource variability has on solar power plant production as applied to the case of Portugal (southern Europe). To that end, 17 years (2003–2019) of meteorological data from a network of 90 ground stations hosted by the Portuguese Meteorological Service is examined. Annual capacity factor regarding photovoltaic (PV) and concentrating solar power (CSP) plants is computed using the System Advisor Model, used here for solar power performance simulations. In terms of results, while a long-term trend for increase in annual irradiation is found for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI), 0.4148 and 3.2711 kWh/m2/year, respectively, consistent with a solar brightening period, no corresponding trend is found for PV or CSP production. The latter is attributed to the long-term upward trend of 0.0231 °C/year in annual average ambient temperature, which contributes to PV and CSP efficiency reduction. Spatial analysis of inter-annual relative variability for GHI and DNI shows a reduction in variability from the north to the south of the country, as well as for the respective power plant productions. Particularly, for PV, inter-annual variability ranges between 2.45% and 12.07% in Faro and Santarém, respectively, while higher values are generally found for CSP, 3.71% in Faro and 16.04% in São Pedro de Moel. These results are a contribution to future instalments of PV and CSP systems in southern Portugal, a region with very favourable conditions for solar energy harvesting, due to the combination of high production capacity and low inter-annual variability.

Predicting Energy Production in Renewable Energy Power Plants Using Deep Learning

It is very important to analyze and forecast energy production for investments in renewable energy resources. In this study, the energy production of wind and solar power plants, which are among the leading renewable energy sources, was estimated using deep learning. For a solar power plant, three different solar power plants with 1MW installed power were examined. Three-year energy production data of power plants were taken. These data were used with the deep learning method long short-term memory (LSTM) and seasonal autoregressive moving average (SARIMA). Results were obtained for each dataset; they were subjected to five different (MSE, RMSE, NMSE, MAE, and MAPE) error performance measurement systems. In the LSTM model, the highest accuracy rate was 81% and the lowest accuracy rate was 59%. In the SARIMA model, the highest accuracy rate was 66% and the lowest accuracy rate was 41%. As for wind energy, wind speeds in two different places were estimated. Wind speed data were taken from meteorological stations. Datasets were tested with MAPE, R2, and RMSE error performance measurement systems. LSTM, GRU, CNN-LSTM, CNN-RNN, LSTM-GRU, and CNN-GRU deep learning methods were used in this study. The CNN-GRU model achieved a maximum accuracy of 99.81% in wind energy forecasting.

Low‐carbon economic schedule of the H2DRI‐EAF steel plant integrated with a power‐to‐hydrogen system driven by blue hydrogen and green hydrogen

AbstractHydrogen direct reduction iron coupled with electronic arc furnace (H2DRI‐EAF) technology, as an important technology for decarbonisation in the iron and steel industry, has the advantages of high electrification and low carbon emissions. However, the large demand for hydrogen in this technology relies significantly on the production of electrolytic hydrogen, leading to a substantial increase in power consumption in the steel production process. Moreover, the use of an unclean power source in electrolytic hydrogen production leads to increases in indirect carbon emissions, reducing the low‐carbon attributes of the technology. This study investigates the integrated flexible operation mode of a steel plant. An illustrating method is utilised for modelling the entire steel production process and power to hydrogen (PtH2) process in detail for the H2DRI‐EAF steel plant, which includes natural gas, photovoltaic, wind power self‐provided power plants, and carbon capture and storage (CCS) systems. A mixed integer linear programming (MILP) model is developed for the comprehensive scheduling of the steel mill. The results of the case studies indicate that by reliably integrating the production of renewable energy and natural gas power plants, the PtH2 system can fully consume the renewable energy output while ensuring the smooth progress of steel production and maximising the reduction of carbon emissions from hydrogen production and the total cost of steel production.

Cause Analysis and Improvement Measures for Superheated Platen Tubes Failure of a 580 t/h CFB Boiler

Superheaters are crucial components of boilers operating under high temperatures and pressures. Understanding potential damages, especially in components like superheaters, is essential for enhancing boiler, turbine, and overall power plant productivity. This paper highlights a study for the failure investigation of platen superheater tube in Unit 2 of a 2x150 MW coal-fired power plant in South Sumatra. Various tests including chemical composition, hardness, tensile, metallography, SEM fracture surface examination, and XRD compound analysis were conducted to assess the failure of the platen superheater tube. The investigation revealed that the failure of platen superheater tube was initiated by the plugging of the tube elbow due to deposits and ashes adhering to the tube's interior. This obstruction prevented saturated steam flow inside the tube, leading to overheating and a subsequent drop in mechanical strength. Overheating was confirmed by the presence of spheroid particles in the ferrite matrix. Prolonged overheating resulted in the formation of microvoids, leading to creep failure and crack formation in the tube. Following improvements made during Unit 2 maintenance outage, which involved adding refractory material inside the furnace on the platen superheater panel, positive results were observed. The platen superheater tubes, which previously exceeded temperature limits, now operate within normal range temperatures. This improvement also reduced spray water consumption and significantly increased boiler efficiency from 83.19% to 83.54%.

Digital model of hydraulic drive for solar tracker rotary control

An important area in the field of solar energy is considered, focusing on the use of a hydraulic drive in high-power solar trackers. In the context of the relevance of environmental problems and the commitment to energy efficiency, the role of solar trackers in increasing the productivity of solar power plants is investigated. An analysis of current trends in the field of hydraulic drive is presented, highlighting the prospects for its application. The analysis of the directions of improvement of the drives of the solar tracker is carried out. The hydraulic drive of the tracker is considered as an object of regulation. Disturbing loads of various types acting in the process of changing the position of the tracker are determined. The main load acting on the tracker drive is positional, caused by the gas–dynamic effect of the wind flow impinging on the tracker plane or the ambiguity of the behavior of the snow and ice cover. It is determined that the inertial load, when turning a high-power tracker, has a significant effect on the friction forces in the attachment points of the hinge support mechanisms. Options for the implementation of new circuit solutions for the tracker hydraulic drive are considered. Using information from sensors of movement of the rods of hydraulic motors of the tracker position drive, the sun position sensor, the control electronic module positions the solar tracker platform by supplying control signals to the electric hydraulic distributors of the drive. The hydromechanical regulators of the pump adjust the characteristics of the system to a random change in external loads on the tracker. A mathematical model of the hydraulic drive of the basic circuit tracker has been developed. The digital model of the tracker drive is designed to optimize the operation of the hydraulic drive, taking into account various factors such as inertia, viscous damping, hydraulic losses, system nonlinearities, thermal losses, elasticity of elements and the impact of external factors. The results obtained emphasize the efficiency and accuracy of the control system, making the hydraulic drive an important element in the development of clean and efficient energy.

Innovative design and field performance evaluation of a desert-adapted PV module for enhanced solar energy harvesting and reliability in harsh arid environments

The aim of this study is to present and evaluate the performance of a novel photovoltaic (PV) module configuration introduced as the “Desert Module,” developed to enhance the production and efficiency of PV power plants operating in harsh desert locations. This innovative module has been constructed by incorporating various technological solutions to address desert climate conditions such as high temperatures, soiling, and intense UV radiation. To assess the performance of the developed “Desert Module,” a comprehensive evaluation was conducted by comparing its performance to that of a conventional module. The study encompasses three main aspects: (i) indoor characterization, including flash and electroluminescence tests; (ii) performance assessment in a hot semi-arid climate over an eight-month period; and (iii) economic analysis to benchmark the costs of electricity produced from the proposed configuration against conventional alternatives. The results indicate that the Desert Module outperforms the conventional module across all performance metrics, enhancing the average efficiency by 0.5%. In addition, the performance ratio for the Desert Module stands at 0.87, surpassing the 0.82 achieved by the conventional module. Throughout the experiment, the average energy yield was enhanced by 5.8% and the conversion efficiency by 1.95%. Notably, during the hottest period (between July and August), the deviations on the energy yield and the conversion efficiency exceed 7% and 3%, respectively, in favor of the Desert Module, highlighting its resilience to the high temperatures characterizing desert locations. Furthermore, the Desert Module demonstrates a 4.44% reduction in the levelized cost of electricity compared to the conventional module, positioning it as a more economically viable option for large-scale energy generation in desert environments.

A flue gas velocimeter based on the hyperbolic chirp modulation method of acoustic source signal

Accurate measurement of flue gas velocity is of great significance for the safe production, energy saving, and emission reduction of coal-fired power plants. In this paper, a method of flue gas velocimetry based on a hyperbolic chirp-modulating acoustic source was proposed, and its superiority was verified by numerical simulations and field experiments. For an acoustic velocimeter, it is crucial to ensure the accuracy of the acoustic Time-of-Flight (TOF), which directly affects the flue gas velocity measurements. The improvement of the accuracy of estimation of the TOF directly determines the accuracy of the flue gas velocity measurement. Simulation on the different types of acoustic sources at different signal-to-noise ratios (SNRs) was conducted, and the results proved that the hyperbolic chirp signal is more accurate in the measurement of TOF. In the strong noise range of − 10 dB to − 20 dB, the average relative root mean square error (RRMSE) obtained using this hyperbolic chirp modulating acoustic source is 0.60 dB and 0.36 dB lower than obtained using the linear and logarithmic modulating modes, respectively. The average relative error (RE) is approximately 0.87 times that of the linear chirp. Power plant flue field experiments show that the measurement error using this hyperbolic modulating mode is about 0.52 times and 0.74 times that of using linear and logarithmic modulating modes, respectively. In harsh measurement environments with strong noise, the proposed acoustic source modulation scheme can significantly improve the measurement SNR and effectively enhance the accuracy and robustness of flue gas velocimetry.

Techno-Economic Assessment for the Best Flexible Operation of the CO2 Removal Section by Potassium Taurate Solvent in a Coal-Fired Power Plant

Alternative solvents based on aqueous solutions of amino acids have been recently developed as possible substitutes for Mono Ethanol Amine (MEA) for CO2 removal from flue gas streams. The potassium taurate solvent has the advantages of degradation resistance, low toxicity and low energy requirements for its regeneration. With any type of solvent, CO2 removal applied to a power production plant decreases the revenues obtained from selling electricity because of the energy requirements. Operating the CO2 removal section in flexible mode avoids significant effects on the profits of the power plant, while accomplishing environmental regulations. This work is the first journal paper focusing on the application in flexible mode of the potassium taurate system for treating a flue gas stream from a 500 MW coal-fired power plant. Techno-economic evaluations are performed to determine the best operating conditions considering the variation in the electricity demand and its price, and different values of carbon tax. In the summer period, with high electricity prices and demands, carbon tax values between 45 EUR/tCO2 and 60 EUR/tCO2 favor CO2 absorption in the flexible mode, without periods of full CO2 emissions during the day.

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

Investigation of Failures during Commissioning and Operation in Photovoltaic Power Systems

Considering global warming and environmental problems, the importance of renewable energy sources is increasing day by day. In particular, the effects of wind and solar power, which are variable renewable power sources, on the power system necessitate their evaluation in terms of the reliability of the power system. Photovoltaic panels, which enable the conversion of solar power into electrical power with semiconductors, have started to take an important place in global energy investments today. Photovoltaic power plants increase the demand for this energy source with continuous energy conversion depending on sunshine duration and radiation intensity. Among the renewable energy sources, the most easily utilized energy source, regardless of geographical conditions, is the sun. To prevent the energy production of PV power plants from being interrupted, it is necessary to address and analyze all kinds of faults that will affect power production in order to increase the reliability of the system. Academic studies in this field are generally grouped under two topics: classification of faults or modeling of electrical faults. Based on this, in this study, the problems that occur during the installation and operation of photovoltaic systems are classified, and the relevant faults are modeled and simulated in MATLAB Simulink version 23.2 (R2023b). Thus, a scientific approach to the problems of photovoltaic power plant operating conditions has been gained, which will be the basis for academic studies.

An Experimental Investigation Use of Fly Ash as Partial Replacement Cement in Concrete

Infrastructural development is at its peak all over the world and is a symbol of growth for any country. The most popular construction material is concrete which involves use of cement which is responsible for 7% of total world’s carbon dioxide emissions. Carbon dioxide is the main threat in causing global warming of the environment. The attempts have been made to reduce CO2 emissions in environment by all possible ways, but cement has not found a suitable replacement for it till date. Fly ash concrete is an effort in reducing cement content of construction. Fly ash concrete has economical and environmental advantages. It also makes concrete sustainable. In India, presently nearly 50% of fly ash produced is consumed. The paper aims at discussing the use of fly ash concrete in construction as a solution to address two environmental problems – one, disposal of huge amounts of fly ash, by production of thermal power plants, causing environmental degradation through large areas of landfills and two, high percentage of carbon dioxide emissions in the atmosphere from the cement industry.

SOLAR TECHNOLOGY: EMPOWERING SERBIA’S RENEWABLE ENERGY FUTURE

This study investigated the solar power potential and performance in Serbia, a country with favorable solar conditions but limited resource utilization. The principal objectives of the investigation were to analyze the performance ratio (PR) and assess the electricity production of simulated solar power plants in different distribution areas. The Photovoltaic System software (PVsyst 7.3) was employed to simulate five grid-connected solar power plants, each with a capacity of 10 MW, in five distribution areas of the Serbian Public Electric Utility Company. The study found that the PR values varied from 81.7 % to 84 %, indicating favorable conditions for harnessing the solar potential. The simulations projected an annual electricity delivery to the grid of 64.41 GWh. According to the study’s estimates, installed solar power plants would be capable of meeting 0.22 % of the electricity needs in Serbia.

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

An integral and flexible wireless power monitoring system

This paper describes the main and fundamental aspects of a power monitoring system, with good adaptation possibilities that ease its use in both PV power production plants and home or building electrical grids. It makes a smart metering solution which integrates several acquisition modules for electrical energy production and consumption monitoring, analysis and control management. The system is flexible in its configuration, easy to install and maintain and allows data transmission to a remote server by Ethernet, Wifi or GPRS/GSM or to a local server through a simple USB cable.

Equivalent Breakeven Installed Cost

Technoeconomic analysis (TEA) is commonly used to determine economic viability of power-generating technologies, including concentrating solar power (CSP) and thermal (CST) production plants. Levelized cost of electricity (LCOE) and analogous measures provide an estimate of long-term costs for operating power plants over their designed lifetimes by accounting for revenues and costs in a time-discounted manner. While these measures are effective when assessing a technology’s total lifecycle costs and productivity under various designs, TEA of candidate incremental technology improvements from the lens of LCOE can be limited when required investment and LCOE impacts are small. In this work, we propose a novel metric for TEA of a plant component technology that recasts relative changes in levelized system costs into component-specific capital cost budgets. This measure, which we refer to as the equivalent breakeven installed cost, is the maximum budget for the technology component that leads to improved levelized costs. We illustrate the usefulness of this metric using the example of candidate heliostat improvements for a CSP tower plant. Here, the results suggest that a reduction in mirror washing costs yield a total plant O&M cost of $37/kWe-yr, which is a breakeven proposition if the average reflectance is reduced from 0.90 to 0.85 as a result of the cost savings.

POTENSI PENGHEMATAN BIAYA TAGIHAN LISTRIK PASCA PEMASANGAN PLTS ATAP GEDUNG RUSUNAWA UNIVERSITAS UDAYANA

The limited availability of natural resources and the impact on the environment that regularly using fossil-based electricity become the basis for the government to develop renewable energy. One of the potential uses of renewable energy in Indonesia is a rooftop solar power plant which in its design does not require a large area of land and space for the placement of solar modules. This research designing rooftop solar power plants with an on-grid system on the Udayana University Rusunawa building with the capacity scenario of 20 kWp, 15 kWp, and 10 kWp using HelioScope. Based on the results of rooftop solar power plants production can be seen the potential cost savings of electricity bills each year. Based on the results of the design for rooftop solar power plants scenario, the number of solar modules obtained is 40 pieces, 30 pieces and 20 pieces with potential savings in electricity bill costs of Rp. 33.391.515, Rp. 28.933.478 and Rp. 23.269.285 per year.

Energy aspects of automobile transport development

Problem. Improving automobile transport means increasing fuel economy and environmental indicators. Fuel, in a broad sense, means energy used to activate the car's power plant. Potential energy is dispersed in the earth’s interior, on its surface, in the atmospheric air, and even in space. Moreover, some of them exist in different substances. On the one hand, the efficiency of an energy product use is assessed by its energy intensity; on the other hand, it is evaluated by the costs of its production (transportation) and the quality of its transformation into a consumer type of energy. Special attention is paid to renewable and unlimited kinds of energy sources. Goal. The purpose of the study is a qualitative analysis of the road transport development direction from the standpoint of the alternative energy sources use, taking into account the factors that comprehensively determine the economic and environmental indicators at the stages of production and processing of fossil raw materials, production of power plants and conversion, transformation, and transportation of energy in the field of transport technologies. Methodology. The first direction consists of the adaptation (conversion) of the design of thermal internal combustion engines for alternative liquid or gaseous fuel types. The advantage of this approach is minimal costs for engine conversion and fuel production. The second approach involves using hybrid power plants, consisting of a main and auxiliary engine, an energy source or accumulator, an energy converter, and a braking recuperation system. The third direction is the use of non-traditional energy sources. Results. The directions of the development of power plants for motor vehicles related to the increase in the energy density of hydrocarbon fuels, the use of hybrid power plants, and the use of alternative energy sources have been determined. A qualitative assessment of the considered approaches is given. Originality. A comprehensive approach to evaluating the effectiveness of using alternative types of energy in road transport is considered in terms of energy, economic, and environmental indicators. Practical value. The obtained results can be regarded as recommendations when drawing up plans for the evolution of industries of fossil extraction and transformation of other energy resources, the development of motor vehicles, and transport infrastructure technologies, taking into account the natural and industrial potential of the country

Assessment of the potential of solar energy to power municipal utilities

The use of alternative energy sources in the housing and utilities sector of Ukraine is a pressing issue today. Powering household consumers or life-support facilities from a photovoltaic power plant allows achieving energy autonomy, reducing electricity costs, and reducing the negative impact on the environment. Over the past ten years, there has been a significant reduction in the cost of solar power plant elements while improving the quality characteristics of the equipment. This affects the speed of transition of various consumer groups, from households to industry, to alternative energy sources or the use of a hybrid energy system. The efficiency and productivity of photovoltaic power plants are affected by the type of technology used and environmental factors. In the process of converting solar energy, losses may occur that are related to the efficiency of solar panels, inverters, and other system components. When designing a photovoltaic power plant, it is necessary to take into account the latitude of the area where it is planned to install it and possible changes in weather conditions that may reduce solar energy production. To increase the reliability of power supply to equipment in the housing and communal sector, it is proposed to equip the pumping station for increasing the pressure in the water supply network of a nine-story residential building with solar panels. The calculation of the amount of energy generated by the solar power plant is based on angle of panel installation, chosen in accordance with the latitude of the region. To calculate the required number of panels, a method was chosen that takes into account the amount of direct and scattered solar radiation received by the solar panel surface. Based on the results of the calculations, the potential amount of hourly generated power during the year and the consumed hourly power were compared. It was found that the potentially high productivity of the station is in the spring-summer and summer-autumn periods, but it is not able to meet the growing demand for electricity in the evening. In the spring and summer, the morning peak in energy consumption can be met by a photovoltaic plant. Under favorable weather conditions, the amount of generated power will be greater than the power consumption, and the excess energy can be accumulated in the battery and used in the evening. The payback period of the investment in the solar station was calculated using the discounted cash flow method and is 1,6 year