Wind Farm Development Research Articles

Barriers and Prospects for the Development of Renewable Energy Sources in Poland during the Energy Crisis

Europe is currently facing the potentially biggest energy crisis in history. There are many reasons for this, and the current geopolitical situation makes it clear that we are being forced to take immediate action to ensure sufficient energy supplies to consumers. Until recently, the European Union was dependent on Russian energy resources (mainly oil and gas). For many years, the EU countries had been shutting down their own production and importing much cheaper raw material from Russia. The threat of a blackout is becoming increasingly possible. European governments are preparing businesses and households for the energy crisis in various ways, but there is also a great deal of mobilization to accelerate the development of renewable energy sources (RES). The aim of this study was to identify the barriers and prospects for RES development in Poland in the current geopolitical conditions. The reasons for insufficient grid HC were analyzed. Additionally, the article aimed to assess the prospects for solar energy development in Poland. Wind power was discussed only in general terms because the development of wind farms is inhibited by the regulatory framework. Particular attention was paid to hosting capacity (HC) and the condition of the power infrastructure as the main determinants of RES development in Poland. Numerous documents developed by power companies and government agencies responsible for implementing and managing energy in Poland were analyzed. Special attention was paid to legal regulations and the need for legislative changes. As a country, Poland has one of the highest growth rates in photovoltaic (PV) installations. The forecasts for increasing HC, as a prerequisite for RES development in Poland, are not promising.

An integrated conceptual model to characterize the effects of offshore wind farms on ecosystem services

Offshore wind farm development has become a key measure of energy transition in recent years. Coastal territories are particularly favorable to the development of offshore wind farms due to their high energy potential. However, these areas are also hotspots of biodiversity, provide attractive landscapes and are under strong anthropogenic pressures. Preserving and sharing the natural and cultural resources of coastal territories while intensifying renewable marine energies, represents one of the most important challenges for future management of coastal environments. Consequently, systemic models that consider all the effects of offshore wind farms on ecosystems and society are essential. Here, we propose a conceptual model for studying these effects, by mobilizing the concept of ecosystem service in a systemic and integrated assessment approach. To that aim, we reviewed the literature and compiled experts’ knowledge in order to characterize the effects of offshore wind farms on food webs during the construction and operation phases. Then, we analyzed the contribution of trophic compartments on ecosystem functions, ecosystem services and beneficiaries, and how offshore wind farms modify the relationships between these compartments of the marine coastal social-ecological systems. Our approach helps identify the causal chains that generate the most important modifications in this system. This information could then be used to predict impacts of offshore wind farms on ecosystem services, and to suggest management trade-offs. This study reveals the need for further studies relating marine biodiversity to ecosystem services, and developing systemic approaches at different scales. The analysis of the effects of offshore wind farms on ecosystem services is crucial since it is linked to strong ecological, socio-economic and political issues.

Techniques to establish accurate background noise levels in areas affected by operational wind turbine noise

During the planning process for an onshore wind farm, the establishment of accurate background noise levels at nearby noise sensitive receptors is vital in determining the allowable noise limits at these locations. This is typically achieved through background noise monitoring at a selection of representative noise sensitive receptors. As onshore windfarms have become more prevalent, areas suitable for wind farm development are increasingly within the vicinity of operational wind farms. The result of this is background noise monitoring at receptors is now often influenced by nearby operational wind farms and is not a true representation of the unaffected noise levels at these locations. Current good UK practice (as set out in the Institute of Acoustics document 'A good practice guide to the application of ETSU-R-97 for the assessment and rating of wind turbine noise') proposes a number of solutions to account for this additional wind farm noise. One solution is to consider directional filtering or the subtraction of the predicted noise levels from the measured baseline data. Whilst both approaches are valid, it can often be unclear which approach is most appropriate for a particular scenario. Within this paper, the limitations of current good practice are discussed, and an alternative methodology is proposed which combines both approaches to establish the unaffected background noise levels. Specific examples of where this alternative approach has been used are presented within the paper as validation.

Numerical modelling of laterally loaded piles driven in low-to-medium density fractured chalk

Chalk’s sensitive, variable nature poses difficulties for foundation designers. It can present as weak rock and yet be de-structured to very weak putty by dynamic or high-pressure loading. The development of multiple offshore wind farms at north European chalk sites led to the recent ALPACA Joint Industry Programme, which undertook intensive material characterisation and large-scale field testing at St Nicholas at Wade (SNW), Kent, UK to capture and better understand the behaviour of piles driven in fractured low-to-medium density chalk. Noting that lateral loading response is a vital design concern for monopile and jacket supported structures, this paper focuses on 3D Finite Element (FE) modelling of ALPACA’s monotonic lateral loading field tests on open-ended driven tubular steel piles. The brittle chalk is modelled with a strain-softening Mohr-Coulomb model combined with nonlocal regularisation, calibrated meticulously against the ALPACA characterisation dataset. A second, simpler modelling approach, adopting a perfectly-plastic Mohr-Coulomb model, is also explored as a simplified practical alternative. Both approaches can match field lateral capacity and bending moment distributions, after taking due account of pile installation and chalk fracturing effects. The analyses indicate how robust, accurate and cost-effective lateral loading design may be approached for low-to-medium density fractured chalks.

Simulating offshore wind contract for difference auctions to prepare bid strategies

This paper presents a novel agent-based, stochastic model, which uses game-theoretic principles to simulate Contract for Difference (CfD) auctions. The framework has use cases and implications for policymakers and renewable generators alike, and can be used by developers to prepare bidding strategy and for policymakers to empirically test auction design. The model is demonstrated through replication of the offshore wind CfD Allocation Round 3 (AR3) pot, and utilises high-level cost modelling distribution data to estimate bid prices for the competing projects. The model produces a distribution of most likely results which better categorises uncertainty, and through comparison of AR3 and simulation results, demonstrates how outcomes can be predicted with reasonable confidence by developers. Analysis show that the transmission network and grid connection charges are a significant barrier for projects in some geographical regions to be awarded a CfD contract, potentially hindering renewable deployment in those areas. Moreover, this paper demonstrates how players can use probability theory to select an optimum bidding strategy which maximises expected profit while factoring the uncertainty inherent in CfD auctions. Results show that a 1200 MW wind farm development can increase potential profits by £135 million over the CfD contract length in exchange for a 25 p.p. chance reduction in being awarded a subsidy.

Installation planning for an offshore wind farm: a hybrid modelling framework of integrating simulation and optimisation with a Markov Chain

ABSTRACT Offshore wind energy has been rapidly gaining traction more recently and the development of offshore wind farms continues to rise on a global scale in search of a sustainable future energy source. In the meantime, the capital-intensive project of installing wind turbines offshore involves a multitude of logistics activities and maritime operations. The high-risk installation process becomes more complex, in particular, under the uncertain weather conditions at sea such as wind speed and wave height. We present in this paper a hybrid modelling framework that minimises the overall installation time required to build an offshore wind farm, and develop a mixed-integer linear program submodule embedded on the discrete event simulation model. In addition, to take stochastic weather states into consideration, a Markov-Chain Monte Carlo method is used to generate weather instances with uncertainty. The weather occurrence serves as an integrated look-ahead viewpoint in making turbine component installation decisions. Further, the experiments of sensitivity analysis are designed to draw insights regarding the effects that the number of turbines, the number of vessels, and the seasonality have on the total project timespan. The computational results demonstrate the efficacy of our proposed hybrid solution approach, tested on the case of Southwest Offshore Wind Farm in South Korea.

Effects of Wind Power Development on Reindeer: Global Positioning System Monitoring and Herders’ Experience

Testing and documenting effects of wind farm (WF) infrastructure on wildlife are crucial considering increasing development throughout Scandinavia, especially for reindeer, which require large areas for grazing and are vulnerable to disturbances. We present results from 2011 to 2019 for semidomesticated reindeer tracked with Global Positioning System (GPS) transmitters, along with herders’ knowledge about reindeers’ habitat use and changes following WF development within the Raggonjarga reindeer district summer range in Finnmark, Norway. We tracked up to 36 females (ranging from 19 to 36 individuals per year), from their arrival in the study area in April to their departure in the end of October. We evaluated habitat use before, during, and after WF development at the home range and landscape scales. We also evaluated reindeer habitat use qualitatively based on semistructured interviews with local herders. The herders’ reported negative effects of the WF on reindeer, both on general habitat use and intrarange movements, resulting in less use of grazing areas surrounding the WF and increased workload for the herders. The GPS results partly support the herders’ experiences. We found negative effects of the WF at the landscape scale, except during summer, where the effect was positive. Results at the home range scale showed negative effects of the WF in spring and summer, but not autumn. Different results at different scales make identifying causality challenging, especially as yearly variation was also large. Different results for summer and autumn may relate to changes in herding activities and larger movement patterns, respectively. Similar and contrasting results from the two methods suggest a need for both sources of data in combination to understand and improve land management. Including herders’ knowledge to understand results from GPS data is thus crucial. We also suggest future studies focus on mechanisms behind behavioral changes to better understand cause-and-effect relationships and how effects can be mitigated.

An ecological risk assessment for the impacts of offshore wind farms on birds in Australia

AbstractAn ecological risk assessment, based on life‐history and behavioural attributes of 273 bird taxa, was used to identify which of those taxa are at high risk from negative interactions with offshore wind farms in Australia. The marine area of Australia was divided by state/territory boundaries perpendicular to the coast into eight regions, with Western Australia further divided into north and south, and a Bass Strait region bounded by the Victoria coast and the north coast of Tasmania. These regions were subdivided into coastal, inshore and offshore sub‐regions and a risk summary for all bird taxa occurring in each of these sub‐regions produced. In coastal and inshore sub‐regions of Bass Strait, South Australia and Tasmania, the species with the highest risk scores were Orange‐bellied Parrot Neophema chrysogaster, Furneaux White‐fronted Tern Sterna striata incerta, Swift Parrot Lathamus discolor, Shy Albatross Thalassarche cauta, Far Eastern Curlew Numenius madagascariensis and Anadyr Bar‐tailed Godwit Limosa lapponica anadyrensis. In offshore sub‐regions in southern Australia, the highest risk species were all albatrosses, comprising Northern Royal Diomedea sanfordi, Eastern Antipodean D. antipodensis antipodensis, Gibson's D. antipodensis gibsoni, Wandering D. exulans, Amsterdam D. amsterdamensis and Grey‐headed Albatross T. chrysostoma. Compared to onshore installations, there are logistical challenges to quantifying the potential and realized impacts of offshore wind farms that require different approaches to data collection and analyses. The extensive development of offshore wind farms in the Northern Hemisphere provides examples of best and emerging approaches to quantify and mitigate negative impacts of offshore wind farms that can be applied in an Australian context. Despite differences in the species involved, the same approaches to identifying high‐risk species and to the monitoring and mitigation of negative impacts should be applied in a coordinated, regional‐scale approach to the development of offshore wind farms in Australia.

High resolution wind resource assessment method based on mesoscale atmospheric model and CFD technology

The evaluation results of wind energy resources directly affect the economic benefits and healthy development of wind farms. Therefore, a high-resolution wind resource assessment method for wind farms based on mesoscale atmospheric model and CFD technology is studied to accurately simulate relevant data of wind resources and improve the assessment effect. The mesoscale WRF numerical model is used to solve the regional data of wind farms and obtain the mesoscale meteorological analysis data. According to the solution results of the mesoscale atmospheric model, the wind speed profile is established, the boundary conditions and initial conditions are extracted, and the CFD micro scale model is input to obtain the wind speed and wind speed frequency at the height of the fan impeller. In order to improve the accuracy of numerical simulation of micro scale CFD model, the large eddy simulation method is used to simulate the operation of wind farms. Complete theoretical power generation evaluation based on wind speed, wind speed frequency and generator power. The experimental results show that this method can accurately simulate wind resources and accurately evaluate the theoretical power generation of wind farms. The wind farm is rated as Level 3, and the wind frequency is mainly between 4 and 10 m/s. This method can ensure that the wind farm can generate electricity all year round without damaging the wind speed.

Geological and geotechnical characterisation of soft Holocene marine sediments: A case study from the north Irish Sea

The seabed of the Western Irish Sea Mud Belt (north Irish Sea) comprises a thick sequence of fine-grained Holocene marine sediments that overlay complex glacial deposits. The Holocene sequence preserves a record of environmental change in the area. Part of this area is earmarked for a number of offshore wind farm developments. The area poses a number of geotechnical challenges to such developments, including soft marine silts and clays as well as shallow gas. This paper characterises the soil conditions in the area in the context of offshore renewable energy development using various geophysical techniques, geotechnical data and shallow (3 m) sediment samples obtained across multiple research surveys between 2009 and 2020. The purpose is to assess the use of such techniques, including multichannel sparker seismic and underwater multichannel analysis of surface waves (UMASW), in characterising these kinds of sediments. It is also intended to build on previous research and provide a reference dataset and case study for further work in developing offshore wind in the area. UMASW and in-situ cone penetration testing with pore pressure measurement (CPTu) results showed good agreement in characterising these Holocene sediments, with multichannel sparker delineating shallow gas from surrounding sediments. Core profiles show distinct lithological variation in the upper 3 m, which can be related to CPTu parameters, but is not resolvable by UMASW profiles. Paleoenvironmental reconstruction for this upper 3 m suggests changes in depositional setting over the past ca. 7000 years, which could influence sedimentary structure. These parameters have implications for cable installation design.

Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic

Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.

Blowing in the Wind: Revenue Windfalls and Local Responses from Wind Farm Development

Blowing in the Wind: Revenue Windfalls and Local Responses from Wind Farm Development

Offshore wind power prediction method considering typhoon, cold wave and other meteorological features under transitory weather

With the large-scale development of offshore wind farms, China's offshore wind power process is becoming more and more perfect. How to accurately forecast offshore wind power, especially under the influence of transitional weather, is a difficult problem to be solved. Therefore, in order to accurately forecast offshore wind power in the extreme small sample event, this paper proposes a method for predicting wind power before the turning weather based on meteorological element selection and small sample learning and expansion. The method improves the prediction accuracy of offshore wind power under typhoons and cold waves by constructing meteorological features in transitional weather such as typhoons and cold waves, expanding the small sample using time series, and modelling the relationship between the expanded meteorological factors and wind power.

Projected Wind Energy Maximum Potential in Lithuania

Harnessing wind energy in Lithuania is one of the most important ways to implement climate mitigation measures. This study aims to assess whether it is feasible to implement an energy greening plan in Lithuania in the 21st century, hypothetically by using only wind farms, where the entire permitted area is developed with them. The wind turbine chosen for the study is a 3 MW wind turbine, installed at a height of 100 m. Wind speeds were estimated using the most up-to-date generation of shared socioeconomic pathway (SSP) climate scenario projections. The most likely climate model, SSP2-4.5, shows that the wind speed in Lithuania is more likely to decrease slightly over the 21st century. The decrease could be as high as 3% in the coastal region, while in the eastern part of the country, which is the furthest from the sea, the decrease will likely be around 1.5%. Analysis of the projected data shows that the number of days with wind speeds below the cut-in speed is decreasing, while the number of days with wind speeds higher than the cut-off speed is increasing slightly. However, the number of days on which the operating conditions of the wind farm are met has changed only slightly. The results show that the potential maximum wind power generation exceeds Lithuania’s renewable energy needs by at least three times, suggesting that the development of onshore wind farms in Lithuania can help to achieve the energy greening plans.

A comparative study to analyze wind potential of different wind corridors

The rollout of China Pakistan Economic Corridor (CPEC) has benefited Pakistan in getting a faster pace in terms of economic and financial stability. Pakistan has a significant geographical location in the Asian continent. It possesses an enormous renewable energy sources (RES) potential, primarily wind, in its Sindh, Balochistan, and Khyber Pakhtun-Khuwa (KPK) provinces. This study concentrates on the availability of wind power potential at the selected twelve sites located in three different provinces of the country, using the Weibull probability distribution (WPD) technique. Five parametric estimation techniques were simulated on the data sets of the selected wind sites to find the optimal results. The obtained results showed that the annual wind energy density was found to be 3668.28 kWh/m2 at Lucky Energy, 3297.21 kWh/m2 at Sujawal, 3180.03 kWh/m2 at Tando Ghulam Ali, 2836.76 kWh/m2 at Sanghar, 2821.09 kWh/m2 at Baburband, 2684.32 kWh/m2 at Ketibandar, 2618.78 kWh/m2 at Umerkot, 1759.2 kWh/m2 Hawksby, 1253.76 kWh/m2 at Gwadar, 896.41 kWh/m2 at Quetta, 558.59 kWh/m2 at Haripur and 376.07 kWh/m2 at Peshawar respectively. From the results, it is found that sites present in Sindh province are suitable for commercial-scale wind farm development and the selected wind sites of Balochistan are appropriate for utility-scale wind power development. In contrast, the selected wind sites of Khyber Pakhtunkhwa province are unsuitable for commercial scale due to low wind speeds around the year.

GIS-based weighted overlay model for wind and solar farm locating in Sri Lanka.

With regard to wind and solar energy, research has shown a clear discrepancy between the amount of energy currently being used with the existing potential. The present research has attempted to develop a geographic information systems (GIS) based weighted overlay model to identify potential locations for the development of wind and solar farms in Sri Lanka, which are rapidly advancing renewable energy resources globally. Four major land-use types were considered for the model development as least productive land areas to establish wind and solar farms, namely, barren lands, sand areas, open forests, and scrublands. Nine and seven criteria were identified for the wind and solar farm siting respectively, and the relative weights for each criterion were obtained through focused group discussions. The weighted overlay model was used to locate suitable areas and higher the values generally indicate that a location is more suitable. The outcome of the weighted overlay model shows that for the wind farm locating, 141km2 of highly suitable lands available accounts for 3% of the total land area of Sri Lanka. Furthermore, the model results indicated a total area of 99km2 as highly suitable for solar power generation. Central, Sabaragamuwa, Uva, and Northern provinces were found to be the most suitable for wind farm locating and Eastern, Southern, and Northern provinces we identified as highly suitable for the solar farm locating. The model validation performed by overlaying the results with the existing solar and wind farm map of Sri Lanka indicated that the highly suitable, moderately suitable, and marginally suitable lands identified by the weighted overlay lied within 1km radius of the existing wind and solar power plants. Thus, it can be concluded that GIS-based weighted overlay model can serve as a primary screening tool to shortlist the optimum land areas to locate future solar and wind farms in any selected geographical location.

Development of a computable general equilibrium model based on integrated macroeconomic framework for ocean multi-use between offshore wind farms and fishing activities in Scotland

The rapid development of offshore wind farms (OWFs) has raised concerns about the increasing conflicts and synergies with existing marine activities, especially the traditional fishery industry, from socioeconomic and environmental perspectives. Quantifying the conflicts and synergies require frameworks that can consider environment and economic systems simultaneously. This study builds on and extends a well-established computable general equilibrium (CGE) model to incorporate a natural capital and ecosystem service into the modelling framework, enabling a comprehensive analysis of the two-way interactions between the economy and natural environment. Our results suggest that expansion of OWFs has significant negative impacts on the seafood sectors, whereas fish stocks benefit slightly as fewer fish are harvested. Moreover, the increase in fish stocks due to the closed areas and artificial reef effect could bring benefits to the fishing sector, and pass onto the wider economy. The combined impacts of expansion of OWFs and increased fish stock demonstrate the potential benefits of multi-use of marine spaces by the OWFs and fishing activities. This modelling approach provides an illustration of the potential and importance of incorporating natural capital into CGE models in practice, which could be used for policy making regarding marine renewable energy and sustainable development planning in the marine environment.

Assessment of Offshore Wind Resources, Based on Improved Particle Swarm Optimization

It is crucial to understand the characteristics of wind resources and optimize wind resources in the area that is being considered for offshore wind farm development. Based on the improved particle swarm optimization (IPSO) and the back propagation neural network (BPNN), the IPSO-BP hybrid intelligent algorithm model was established. The assessment of wind resource characteristics in the eastern waters of China, including average wind speed, extreme wind speed, wind power density, effective wind energy hours and wind direction distribution were all calculated. Additionally, the wind speed throughout the different years in Luchao Port, a famous seaport in China, was predicted. The results revealed that the wind power density is approximately 300 W/m2 all year round and that the effective wind energy hours take up about 92% per hour. It was also identified that the wind direction distribution is stable in Luchao Port, implying that there are better wind energy resource reserves in this region. The IPSO-BP model has a strong tracking performance for wind speed changes, and can accurately predict the wind speed change in a short period. In addition, the prediction error of the IPSO-BP model is smaller when the time of training data is closer to the target one, and it can be controlled within a 5% range.

Empowering onshore wind energy: A national choice experiment on financial benefits and citizen participation

This paper examines a representative choice experiment for Ireland (n = 1014) to understand the trade-offs citizens are willing to make between the distribution of financial benefits from a nearby wind farm and procedural measures for citizen participation in decision-making. Both participatory processes and outcomes which recognise local impacts are necessary for the acceptance of onshore wind farms. This paper distinguishes between shared community benefit funds, near-neighbour compensation, and citizen investment relative to issues of ownership, modes of engagement and the management of financial benefits during siting, construction, and operation of a wind farm respectively. Citizens willing to accept place greater importance on factors associated with distributive and procedural justice, while proximity and related visual impacts have comparatively more importance for citizens unwilling to accept. Willingness to accept is associated with early, in-person, engagement with a community liaison officer during siting and citizen participation in the governance and distribution of financial benefits during operation. However, citizens who show conditional support for wind farm developments prefer compensation of near-neighbour households, semi-state developers, and town hall engagement meetings. Strong supporters are more influenced by financial benefits for the wider community and local (co-)ownership of wind farms, particularly joint ventures between the developer and community.

Analysis of sea waves energy resources in the Baltic Sea and technical possibilities of their usage for energy generation in Poland

Due to the current ecological situation in the world, the demand for renewable energy is growing. Its use does not burden the environment because resources are renewed in a short time, unlike traditional fuels - coal or oil. It can be concluded that the main task of humanity is to choose the appropriate technology for obtaining renewable energy and adapt it to local conditions. The aim of the work is to present the technical, economic and environmental potential of using the wave energy of the Baltic Sea and the possibility of converting this energy into electricity. The theoretical and technical potential of sea wave energy that Poland could use was estimated. The most advanced methods of converting wave energy into electricity were presented, and the most promising technical solutions were selected for use in the Polish Exclusive Economic Zone and off the coast of our country. The selection of the most promising technologies - single and combined wave energy converters was based on reports on the operation of the first experimental wave power plants and wave converters operating in other waters. In terms of technology and economics, obtaining energy from sea waves is much more difficult than using solar or wind energy. However, along with the development of offshore wind farms and access to the infrastructure of the National Power System and the need to give up traditional, emission-related energy sources, wave power plants may have a chance for development in the Polish energy sector. It is an untapped source of renewable energy with great energy potential.