Energy Cost Research Articles

Daylight Considerations for Offshore Wind Operations and Maintenance

Abstract The cost associated with operations and maintenance (O&M) for offshore wind is a cost that developers and operators are striving to reduce in order to reduce the overall Levelised Cost of Energy. Improving accessibility and increasing time based availability of wind turbines can guarantee these reductions. To increase time based availability , some wind farms utilise night shift work to reduce downtime for turbines. Previous studies revealed cost reductions using this method but are strictly based on North Sea wind farms. This paper investigates the impact daylight hours have on the O&M costs for an offshore wind farm depending on location. Using an O&M model, three maintenance strategies are simulated and their associated O&M costs are found: ‘Daylight Limited’, ‘Daylight Not Limited’ and ‘Night Shift’. Three case studies are chosen: North Sea, USA and Australia. The operational costs for the North Sea were reduced by £32.74/MWhr with the introduction of the night shift. With increased daylight, the US site saw a smaller reduction in operational costs of £3.48/MWhr using the night shift. However, the Australian site was negatively impacted when adopting a night shift strategy as operational costs increased by £3.19/MWhr. The study considers, if there are reductions in cost through night shift, is it worth the trade-of the industry makes for health and safety of technicians who work at night.

Experimental Investigation of Towing of a Semi-submersible Floating Offshore Wind Turbine

Abstract The offshore floating wind energy sector is poised for exponential growth in the coming decades. A pivotal challenge within this context is the imperative to substantially decrease the levelized cost of energy (LCOE) to enhance competitiveness. A significant proportion of these LCOE costs are attributable to the towing operations entailed in both the installation of assembled floating wind turbines and the maintenance of major components. Semi-submersibles, characterized by multiple columns and pontoons, represent the prevailing conceptual approach in the industry due to their versatility across varying water depths and their cost-effectiveness in terms of mooring and transportation. Towing model tests for the semi-submersible INO WINDMOOR floating wind turbine have been conducted in the Ocean Basin at SINTEF Ocean. The primary objective of these tests is to investigate critical aspects such as towing resistance and dynamic responses, including vortex-induced motion (VIM) and galloping. This paper presents the experimental set-up and initial findings from the model tests. Through comparative data analysis of selected cases, an enhanced and insightful understanding of the intricate fuid-structure interactions is expected to be achieved. Additionally, it highlights the identification of knowledge gaps and research imperatives aimed at expanding the towing operational criteria, with the ultimate goal of reduction of installation and maintenance costs.

Floating wave energy farms: How energy calculations shape economic feasibility?

The aim of this study is to use two different methodologies for calculating the energy produced by a total wave energy farm in the Cantabrian Sea (North of Spain). First method studies the energy produced by the farm taking into account the wave energy converter power matrix and the probability matrix of sea conditions for a particular location. On the other hand, second method is a more simplified methodology in which the wave energy converter power matrix is not taken into account, but it considers the density of the water, gravity, period and height of the wave, as well as the percentage of efficiency, among others. Finally, the energy generated by the farm and the economic parameters that allow calculating its economic feasibility are studied, such as Levelized Cost of Energy, Net Present Value and Internal Rate of Return. Results indicate the importance of using a particular method for calculating the energy produced by a wave energy farm in terms of the variation of its economic feasibility. In this sense, it is shown that despite the fact that the first method is more detailed, the variations between both methods are very small, therefore the simplest model can be used in the future studies, reducing the calculation process in the future.

Modelled Cost Reductions for the X-Rotor Offshore Wind Turbine

Abstract The XROTOR project is developing an innovative turbine (X-Rotor Concept - XRC) that is a Vertical Axis Wind Turbine (VAWT)/Horizontal Axis Wind Turbine (HAWT) hybrid. The objective of this paper is to assess the XRC Levelised Cost of Energy (LCoE), applying different sensitivity analysis to determine a realistic LCoE range. This will then be compared with LCoE estimates for three traditional HAWT drivetrain configurations to evaluate the potential cost savings for the XRC. The paper considers a hypothetical farm of 100x5MW XRCs on generic monopiles, 100km from shore and commissioned in 2030 with a 30-year project. Analysis uses the University of Strathclyde Operation and Maintenance (O&M) model and an LCoE tool developed by University College Cork to calculate results. Sensitivity analysis varies key cost driving elements and uncertain inputs including the O&M strategy, distance from shore and the financial assumptions to determine an optimised LCoE estimated range. Results for the XRC are then compared with estimates derived using the same methodology for the HAWT configurations. Analysis indicates that the novel design may facilitate cost reductions, reducing OPEX by removing heavy components that would require costly heavy lift vessels to maintain. It also removes the failure modes around the gearbox, multi-pole generator and yaw system. The XRC could also reduce the capital cost of drivetrains through a power take-off approach that does not require a gearbox or a multi-pole generation but achieves comparable levels of power conversion. Ultimately the XRC could achieve LCoE cost reductions of 10-19%, compared with the traditional HAWTs. Further savings are considered possible but require additional design and analysis that are outside the scope of this paper.

A novel PEMFC-GT-ST power generation system employing supercritical water gasification of coal for enhanced hydrogen production

This study presents an innovative coal-fired power generation system that integrates a Proton Exchange Membrane Fuel Cell (PEMFC), Gas Turbine (GT), and Steam Turbine (ST) with a supercritical water gasification (SCWG) process designed to efficiently convert coal into hydrogen. A pivotal feature of this system is the first-time integration of advanced two-step SCWG technology with PEMFC, which significantly boosts hydrogen yield, thereby elevating overall efficiency. By effectively addressing the thermodynamic limitations of the Carnot cycle, the proposed system achieves an impressive coal-to-electricity conversion efficiency of 51.61%. Economic viability is demonstrated through a competitive levelized cost of energy (LCOE) of $0.052 per kWh and a rapid payback period of approximately 2.87 years. Furthermore, the study analyzes the impact of various operational parameters—such as coal feed capacity, water-to-coal ratio, operating temperatures of the PEMFC, fuel utilization rates, airflow, and hydrogen bypass flow—on system performance. The findings not only advance the efficiency of coal-to-electricity conversion but also contribute valuable insights to the evolution of sustainable coal-fueled power generation technologies.

Performance analysis of hybrid off-grid renewable energy systems for sustainable rural electrification

Delivering sustainable power to rural communities in sub-Saharan Africa, particularly in Somalia, where many areas are far from the electrical grid and suffer from energy shortages, necessitates the deployment of appropriate technologies. This study evaluates the techno-economic and environmental viability of a hybrid renewable energy system (HRES) comprising a 15 kWp photovoltaic (PV) generator, 10 kW wind turbine (WT), 25 kW diesel generator (DG), and a 72-kWh battery energy storage system (BESS). The HRES is proposed to supply sustainable power to a rural community in Somalia. The techno-economic assessment of the proposed HRES and a comparative analysis of other configurations—namely the PV/WT/BESS and PV/DG/BESS systems is conducted using HOMER and MATLAB software. The results indicate that the proposed PV/WT/DG/BESS HRES demonstrates superior techno-economic performance compared to the other configurations. The lowest net present cost of $96,899.16 and the levelized cost of energy (LCOE) of $0.090/kWh were achieved. This system attains 25 % excess electricity, maintains a 0 % unmet electric load, and demonstrates robust environmental performance with a renewable penetration rate of 91.8 %. Approximately 53.34 % of greenhouse gas emissions are reduced compared to the PV/DG/BESS configuration. The study confirmed the significant impacts of all sensitivity parameters on operational costs, LCOE, fuel prices, fuel intake, and renewable fraction. The overall results indicate superior performance in the optimal system case, offering a feasible and suitable choice for the sustainable electrification of rural communities.

Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification

Developing hybrid renewable energy systems (HRES) is crucial for ensuring affordable, sustainable, and reliable energy access in remote rural and island regions. Rich and detailed data play a pivotal role in the optimal design of HRES. However, remote areas often face data limitations due to inadequate metering infrastructure, which further increases uncertainties in HRES design. This paper proposes a planning optimization method that quantifies multiple uncertainties, requiring only limited information for the optimal HRES design. First, uncertainties in HRES planning are classified into different types based on intrinsic randomness, data availability, and impact level. Then, by integrating uncertainty quantification with credibility theory, knowledge-based scenario generation models are developed to leverage limited available information to generate extreme and typical operating conditions for a tailored HRES design. Finally, a fuzzy credibility-constrained stochastic-robust optimization model is proposed to optimize the design of HRES. A practical case facing significant data scarcity and gaps is used to validate the effectiveness of the proposed method. The proposed approach reduces the loss of load probability for HRES to 0.02% and lowers the levelized cost of energy to $0.16/kWh—33% lower than that of the deterministic method and 79% lower than that of the traditional stochastic method.

An agent-based modeling approach for simulating solar PV adoption: A case study of Irish dairy farms

The agricultural sector faces increasing pressure to enhance energy efficiency in light of escalating electricity costs. This study aims to simulate the adoption of photovoltaic (PV) systems in Ireland’s dairy sector using an agent-based modeling (ABM) approach to facilitate PV uptake among dairy farmers. The model incorporates factors such as grid energy costs, annual electricity consumption, annual solar generation, PV cost, and maintenance expenses to predict PV adoption likelihood. Findings reveal that by 2022, about 2.41% of Irish dairy farmers had adopted PV systems, a figure only 0.41 pp higher than the actual observed rate, validating the ABM’s accuracy. Additionally, the research forecasts future adoption rates of PV systems among dairy farmers, demonstrating the efficacy of ABM in understanding and predicting renewable energy uptake in the dairy sector. These insights can inform policy suggestions to promote renewable energy adoption, ultimately enhancing energy efficiency and sustainability in dairy sector.

Influence of melatonin on the development of obesity

In recent years, increasing attention of researchers has been paid to the role of melatonin in the regulation of body weight. When analyzing literature data, the problem of the mechanism of action of melatonin on the body and its use in the correction of metabolic disorders is considered. Disruption of circadian rhythms caused by the use of artificial light at night leads to decreased melatonin secretion. This helps increase appetite and reduce energy costs. In addition, melatonin plays a major role in modulating the secretion of adipokines by influencing lipid metabolism. Decreased melatonin production causes insulin resistance and metabolic circadian disorganization, leading to obesity. Assessing the role of melatonin in the development of obesity and its accompanying pathologies is a promising area of scientific research in the field of diagnosis, prevention and treatment of endocrine and cardiovascular pathologies.

Robotic feet modeled after ungulates improve locomotion on soft wet grounds

Locomotion on soft yielding grounds is more complicated and energetically demanding than on hard ground. Wet soft ground (such as mud or snow) is a particularly difficult substance because it dissipates energy when stepping and resists extrusion of the foot. Sinkage in mud forces walkers to make higher steps, thus, to spend more energy. Yet wet yielding terrains are part of the habitat of numerous even-toed ungulates (large mammals with split hooves). We hypothesized that split hooves provide an advantage on wet grounds and investigated the behavior of moose legs on a test rig. We found that split hooves of a moose reduce suction force at extrusion but could not find conclusive evidence that the hoof reduces sinkage. We then continued by designing artificial feet equipped with split-hoof-inspired protuberances and testing them under different conditions. These bio-inspired feet demonstrate an anisotropic behavior enabling reduction of sinkage depth up to 46.3%, suction force by 47.6%, and energy cost of stepping on mud by up to 70.4%. Finally, we mounted these artificial feet on a Go1 quadruped robot moving in mud and observed 38.7% reduction of the mechanical cost of transport and 55.0% increase of speed. Those results help us understand the physics of mud locomotion of animals and design better robots moving on wet terrains. We did not find any disadvantages of the split-hooves-inspired design on hard ground, which suggests that redesigning the feet of quadruped robots improves their overall versatility and efficiency on natural terrains.

Coordinated control of single-point moored floating multi-wind turbines under fault events and shutdowns

Abstract The emergence of novel concepts aimed at the reduction of floating offshore wind energy cost is increasingly demanding new control approaches. This is the case of floating offshore multi-wind turbine assets (FOMWT), with two or more full wind turbines placed on the same floating platform. The strong dynamic interaction among the sub-components of such systems requires appropriate coordination of the commands driven by the individual wind turbine controllers. The impact of such coupling may increase depending on the asset confguration, as is the case of single-point distribution of mooring lines, commonly applied to FOMWTs. Among the most demanding situations are those under fault events and shutdowns, which may cause large uncontrolled platform rotation and put the system integrity at risk. To address this, a new coordinated control level, mastering the individual turbine controllers hierarchically, is proposed to govern the whole asset. The control concept proves to be effective under a reduced set of extreme load cases in accordance with standards for a two-wind turbine FOMWT. The simulations are performed with the multi-wind turbine simulation tool MUST, which accounts not only for the interaction among the two turbines and the platform, but also for the communication of the coordinated control and the individual turbine control levels.

Self-catalytic enhancement of Cu-EDTA decomplexation and simultaneous Cu recovery via a dual-cathode electrochemical process

Heavy metals that are readily chelated with coexisting organic ligands in industrial wastewaters impose threats to environment and human health but are also valuable metal resources. Traditional treatment methods generally require additional chemicals and generate secondary contaminants. Here, a reagent-free dual-cathode electrochemical system was proposed for the efficient destruction of Cu-organic complexes and synchronous cathodic recovery of Cu, whereby in situ production of H2O2 at carbon aerogel (CA) cathode was coupled with the reduction of Cu(II) to Cu(I) and finally to Cu(0) at Ti cathode. The intermediate Cu(II) complexes enabled the self-reinforced degradation owing to their higher activities toward •OH generation by activating H2O2 in contrast to initial Cu-ethylenediaminetetraacetic acid (Cu-EDTA). The enhanced production of Cu(I) by Ti cathode facilitated both •OH and Cu(III) formation, and the copper redox cycle was realized in the self-reinforced system, maintaining its sustainable catalytic activity. The energy cost of the dual-cathode system is 0.011 kWh/g for decomplexation and 0.057 kWh/g for Cu recovery, which is much lower than single Ti or CA cathode system. This established process provides a prospective approach for cost-effective destruction of chelating metal complexes and metal resources recovery from heavy metal wastewaters.

Design of a hybrid solar and biomass-based energy system integrated with near-zero energy building: Techno-environment investigation and multicriteria optimization

The current research aims to meet the energy needs of a group of residential buildings in Norway with the least amount of carbon dioxide emission and the greatest amount of renewable energy. The supply side based on the renewable renewable-based energy system is planned and scaled using the real-time data use of domestic hot water (DHW), heating and electricity necessary for the buildings. PVT panels are used in the hybrid solar and biomass-based energy systems to produce both the DHW requirements and the electricity production. The digester is used with the heat pump, which generates heat. A double-effect absorption refrigeration system is also utilized to provide the necessary cooling requirements. On the supply side, the management of the heat streams and the redirection of flows are done using a rule-based regulating system. The whole plant's size is supplied, and the dynamic energy simulation is run. The primary deciding criteria for heating the buildings are the costs of electricity and biomass. The whole system is then optimized depending on operating circumstances, and the outcomes are compared to the design point. PVT may be used to create more than 80% of the yearly DHW. Furthermore, summertime radiation accounts for 64.8% of cooling output since it is more intense and may be converted into cooling energy. Digester/CC also contributes 66.55% of the building's heating, showing that the designers should rely on biomass as wintertime energy costs are higher. The parametric study demonstrates that increasing PVT time and tank capacity has varied effects on efficiency and emissions. Also, On winter days, there was a significant drop in renewable energy generation from summer to autumn, from 82.7 MWh to 28.52 MWh. The optimization results show that at the TOPSIS point, the total cost, efficiency, and emission index are 9.73 $/hr, 36.8%, and 7.75kg/MWh, respectively.

Comparison of Controlled-Z operation and beam-splitter transformation for generation of squeezed Fock states by measurement

In the present paper, we investigate the protocol for the generation of squeezed Fock states by measuring the number of particles from a two-mode entangled Gaussian state using a beam splitter and a controlled-Z operation. From two different perspectives, we analyzed two entanglement transformations in the protocol. We evaluated the energy costs and resource requirements of the analyzed schemes. Furthermore, we studied the impact of experimental imperfections on the non-Gaussian states generated by measuring the number of particles. We explored the effects of photon loss and imperfect detectors on the squeezed Fock state generation protocol.

Optimization of PV benefits for Electric Vehicles Charging Station Using a Deterministic Method and Fuzzy Inference System Method

Utilizing renewable energy, specifically Photovoltaic (PV), for Electric Vehicle (EV) charging presents diverse technical and economic opportunities, reflecting a recent trend in innovation and research to address global transportation challenges while highlighting the value of renewable sources. In this context, this paper aims to devise an optimal power management strategy for an EV charging station powered by a PV-based microgrid (MG). The main purpose is to improve the benefits of PV production in recharging EVs to increase self-consumption, decrease dependency on the power grid, and reduce energy costs. Production data from a real-scale MG at the Catholic University in France were used as a case study. This MG comprises a heterogeneous fleet of EVs, PV sources, stationary storage, EV charging stations, and a connection to the power grid. The optimization of PV benefits relies on leveraging the knowledge of EV characteristics to modulate their charge profile. In this context, two methods are used and compared for the modulation of the EVs' charging profile: a deterministic method and a Fuzzy Inference System (FIS)-based method. For each method, different scenarios emerge based on the knowledge or lack thereof of the EVs' characteristics. This methodology permits the optimal distribution of energy among multiple EVs and regulates the necessary power to achieve the desired charge level upon departure. It encourages charging through PV production, resulting in reduced energy costs. The comparison of total costs reveals notable differences between the deterministic and FIS approaches for both slow and fast charging modes. In the case of slow charging, the deterministic approach achieves savings of -863.4 c€/day, whereas the FIS method delivers greater savings of -898.7 c€/day. For fast charging, the deterministic approach yields savings of -524.6 c€/day, while the FIS method results in even higher savings of -540.7 c€/day. These results highlight that the FIS approach enables better cost management, primarily due to more efficient utilization of PV energy. Additionally, simulation results from MATLAB/Simulink confirm the effectiveness of the FIS-based method, which improves PV energy utilization to 98.20%, compared to 81.60% with the deterministic approach. This highlights the superior efficiency of the proposed FIS.

Efficient Thermal Integration Model based on a Biogas-fired Gas Turbine Cycle (GTC) for Electricity and Desalination Applications; Thermo-Economic and GA-based Optimization

As the global energy demand continues to rise, there is an urgent need to improve the efficiency and sustainability of power generation systems. This study integrated a modified supercritical carbon dioxide (S-CO2) and multi-effect desalination (MED) units to recover residual heat from a gas turbine cycle (GTC) in two stages, significantly enhancing electricity production while reducing the environmental footprint of the GTC. The significance of this study lies in its comprehensive approach, combining thermodynamic, environmental, and thermoeconomic analyses alongside thorough sensitivity evaluations. A triple optimization framework was implemented to optimize the system's performance, focusing on key metrics such as exergy efficiency, CO2 reduction rates, and levelized energy cost, utilizing the NSGA-II and the TOPSIS decision-making method in MATLAB software. Economic viability was assessed through a net present value (NPV) analysis, demonstrating substantial profitability. Finally, a comparison study of the devised system CO2 emissions rate was performed for different renewable energy sources. A specific application of the devised system is its capacity to generate 1.415 m³/h of distilled water while generating 1441 kW of electricity. Sensitivity analysis identified the combustion chamber temperature as the most critical design parameter, with a sensitivity index of 0.328. The optimum economic indicators showed marked improvement, with the NPV increasing from 2.371 M$ to 10.75 M$ and the payback period decreasing from 13.28 years to 7.18 years.

The Sharing Energy Storage Mechanism for Demand Side Energy Communities

Energy storage (ES) units are vital for the reliable and economical operation of the power system with a high penetration of renewable distributed generators (DGs). Due to ES’s high investment costs and long payback period, energy management with shared ESs becomes a suitable choice for the demand side. This work investigates the sharing mechanism of ES units for low-voltage (LV) energy prosumer (EP) communities, in which energy interactions of multiple styles among the EPs are enabled, and the aggregated ES dispatch center (AESDC) is established as a special energy service provider to facilitate the scheduling and marketing mechanism. A shared ES operation framework considering multiple EP communities is established, in which both the energy scheduling and cost allocation methods are studied. Then a shared ES model and energy marketing scheme for multiple communities based on the leader–follower game is proposed. The Karush–Kuhn–Tucker (KKT) condition is used to transform the double-layer model into a single-layer model, and then the large M method and PSO-HS algorithm are used to solve it, which improves convergence features in both speed and performance. On this basis, a cost allocation strategy based on the Owen value method is proposed to resolve the issues of benefit distribution fairness and user privacy under current situations. A case study simulation is carried out, and the results show that, with the ES scheduling strategy shared by multiple renewable communities in the leader–follower game, the energy cost is reduced significantly, and all communities acquire benefits from shared ES operators and aggregated ES dispatch centers, which verifies the advantageous and economical features of the proposed framework and strategy. With the cost allocation strategy based on the Owen value method, the distribution results are rational and equitable both for the groups and individuals among the multiple EP communities. Comparing it with other algorithms, the presented PSO-HS algorithm demonstrates better features in computing speed and convergence. Therefore, the proposed mechanism can be implemented in multiple scenarios on the demand side.

The calculated voyage: benchmarking optimal strategies and consumptions in the Japanese eel’s spawning migration

Eels migrate along largely unknown routes to their spawning ground. By coupling Zermelo’s navigation solution and data from the Japan Coastal Ocean Predictability Experiment 2 (JCOPE2M), we simulated a range of seasonal scenarios, swimming speeds, and swimming depths to predict paths that minimize migration duration and energy cost. Our simulations predict a trade-off between migration duration and energy cost. Given that eels do not refuel during their migration, our simulations suggest eels should travel at speeds of 0.4–0.6 body-length per second to retain enough energy reserves for reproduction. For real eels without full information of the ocean currents, they cannot optimize their migration in strong surface currents, thus when swimming at slow swimming speeds, they should swim at depths of 200 m or greater. Eels swimming near the surface are also influenced by seasonal factors, however, migrating at greater depths mitigates these effects. While greater depths present more favorable flow conditions, water temperature may become increasingly unfavorable, dropping near or below 5 °C. Our results serve as a benchmark, demonstrating the complex interplay between swimming speed, depth, seasonal factors, migration time, and energy consumption, to comprehend the migratory behaviors of Japanese eels and other migratory fish.

Design analysis of a sustainable techno-economic hybrid renewable energy system: Application of solar and wind in Sigulu Island, Uganda

Sustainable energy is central to achieving the global Sustainable Development Goals (SDGs), particularly in electrifying underserved communities. This study examines Sigulu Island, which lacks grid electricity and relies on costly, polluting diesel generators. On-site assessments revealed a daily load demand of 1,455.705 kWh. This study designed and analyzed a Sustainable Techno-economic Hybrid Renewable Energy System (STHRES) combining solar photovoltaics and wind turbines, with battery backup, to meet the island's energy needs. The research adopted both qualitative and quantitative methods, gathering atmospheric weather conditions specific to Sigulu Island. Solar panels and wind turbines were identified as the most viable options, with the system incorporating 677 units of 1 kW solar panels and 27 units of 1 kW wind turbines, generating 839.97 kW and 640.08 kW daily, respectively. Additionally, 527 Li-ion batteries were used to store approximately 1480.05 kW of surplus energy demand to manage fluctuations capable of sustaining the island for 8 hours during a total blackout. The initial installation costs are estimated at $90,393.04 for solar PV, $27,729.82 for wind turbines, $159,169.81 for batteries, and $92,407.00 for the inverter. The STHRES is projected to save $56,917.93 annually, covering 15.4 % of the installation costs compared to diesel operations. Moreover, this system will reduce Uganda's carbon footprint by 436,035.6 kgCO₂ annually, equivalent to a 0.01 % reduction in national emissions. The proposed system decreases the Net Present Cost (NPC) from $426,617.60 to $369,699.67 and the Cost of Energy (COE) from $32.12/kWh to $ 27.79/kWh. With a 9 % Internal Rate of Return (IRR) and a 3 % Return on Investment (ROI), STHRES has a payback period of 8.2 years, demonstrating its financial and environmental benefits for Sigulu Island.

Исследование работы термической опреснительной установки с контактным испарителем и компрессией паровоздушной смеси

One of the global issues of our time is the shortage of freshwater resources. Desalination of marine and brackish waters is a promising solution to this problem. The most common desalination technologies are thermal (distillation) and baromembrane (reverse osmosis and nanofiltration) processes. When designing demineralization stations with reverse osmosis units, it is necessary to consider a number of limitations associated with higher requirements for pretreatment of water entering the unit. The use of thermal desalination plants makes it possible to obtain fresh water of higher quality, and less stringent requirements are imposed on the preliminary preparation of water for this type of unit. However, during the operation of desalination plants of this type, scale forms on the heating surfaces, which negatively affects the efficiency of the unit. Scale is formed less intensively in the units with contact vapors, since in this case the evaporation process occurs in volume. Thus, the development of thermal scheme of such unit and the study of their operation is relevant. The tasks have been solved using the methods of experimental studies of heat and mass transfer processes, mathematical processing of experimental data, and balance calculations of power plants. A thermal scheme of a thermal desalination plant with a contact evaporator with compression of a vapor-air mixture has been developed. Thermal and material balance has been compiled, on the basis of which energy costs have been determined to obtain m3 of fresh water. The authors have proved the determining influence of the temperature of desalinated water in the bubbling zone on the productivity of desalination plants with a contact evaporator. An amendment has been obtained that allows the initial salinity of water and brine to be considered when calculating the operating cycle of the unit. As a result of the analysis of the results obtained, it is found that an increase in the water temperature in the bubbling zone allows us to increase the productivity of the unit, and an increase of the drying temperature of the vapor-air mixture leads to a decrease of the energy consumption of the desalination plant. The introduction of an amendment considering the salinity of the source water and brine makes it possible to increase the accuracy of calculating air humidification up to 15 %.