Abstract

In recent years, floating photovoltaic (FPV) systems have emerged as a promising technology for generating renewable energy using the surface of water bodies such as reservoirs, lakes, and oceans. FPV systems offer several advantages over traditional land-based solar arrays, including increased land-use efficiency, reduced water evaporation, and improved cooling and maintenance. However, like all solar power systems, FPVs are subject to variability and intermittency due to changes in weather, seasons, and time of day. The environmental impact is discussed along with the deployment consideration and the feasibility for a better understanding of the system. Challenges associated with this are addressed by progressed research suggesting the integration of FPVs with various energy storage and hybrid systems. The most promising areas researched in this paper look at hybrid FPV hydropower plants (HPP), in parts of the world experiencing droughts HPP is not working to its optimum capacity. A review of available literature has been conducted on the topic of offshore and onshore floating solar electricity generation using floating solar photovoltaics to identify the challenges and opportunities presented. This work looks at a variety of other hybrid FPV energy sources with varying technology readiness levels. This paper concludes with the possibility of integrating different renewable technologies with existing FPVs and highlights the boons of doing so with some examples. Ultimately, current as well as future perspectives have been provided which consolidate the current research being done and give recommendations for future research work.

Introduction

One of the biggest challenges that is faced by the world is global warming due to which both humans and the planet are suffering as a whole, this is directly linked to the burning of the fossil fuels that we rely on to facilitate our daily life. The Intergovernmental Panel on Climate Change (IPCC) set out the impacts of global warming 1.5 °C above preindustrial levels [1]. We are not currently on course to limit 21st-century global warming to under 1.5 °C or even 2 °C [2]. Another key issue is the lack of clean electrification for a vast population which is hampering the development of the planet in tackling the climate change issue as many rely on the burning of fossil fuel for various daily requirements from generating electricity to cooking. It has been estimated that about 675 million people are still forced to live in the dark most of them belong to sub-Saharan Africa according to 2021 data. Though there has been an increase in the rate of access to electricity from 87% in 2015 to 91% in 2019, this has provided electricity to nearly 800 million people [3]. This is where solar PV can play a substantial role, solar PV has the benefit of being a renewable energy source, producing electricity from solar irradiance without any greenhouse emission [4].

However, there are challenges that must be addressed in order to fully realize the potential of solar energy and traditional photovoltaics [5]. These challenges include land usage, intermittency, storage, and integration into existing energy grids. One promising and upcoming alternative to traditional land-based photovoltaics is Floating Photovoltaics (FPV) or flotavoltaics [6]. The majority of renewable energy sources, such as biomass, solar, and others, take considerable footprint areas to generate electricity on a larger scale, which restricts the use of land for agriculture [[7], [8], [9]]. This sparked the discussion over whether land should be used for food production or energy production [10,11], encouraging research into offshore renewable technologies [12], and led to the creation of the floating photovoltaic (PV) array concept for the production of commercial electricity [13]. FPV technology is a concept in which solar panels are placed on platforms that float on water bodies such as natural lakes, man-made reservoirs, and the seas and oceans [14]. Fig. 1 shows a typical standalone floating photovoltaic system with all the components including an inverter, pontoons, solar panels, and cables connected to the grid.

Conclusion

This review article has examined the current state of research on the integration of floating photovoltaics with different storage and hybrid systems, including batteries, pumped hydro storage, compressed air energy storage, hydrogen storage and mixed energy storage options as well as the hybrid systems of FPV wind, FPV aquaculture, and FPV hydrogen production. The findings suggest that such systems have the potential to significantly increase the efficiency and reliability of renewable energy generation, as well as provide additional flexibility in managing electricity supply and demand.

FPV has many benefits over ground-mounted such as reduced land costs, increased efficiency, reduced soiling, reduced shading, reduced evaporation, and lower visual impact. Hybrid FPV has all of these benefits while being able to reduce its lifetime costs when paired with another technology a reduction in O&M costs, grid infrastructure and cable pooling. Overall, hybrid FPV has all the benefits of FPV plus reduced costs, while enhancing another technology. While FPV is set to rise this will initially be in land first with offshore following, the priority should be covering HPP first due to its complementary nature and benefits for both technologies. Countries, which have HPP reservoirs, should be looking into all the benefits of combining FPV with it. As FPV becomes more common it will be seen moving offshore, as the offshore wind increases it creates the opportunity for FPV to become a hybrid system.

Abstract

     Economic development and the comfort-loving nature of human beings in recent years have resulted in increased energy demand. Since energy resources are scarce and should be preserved for future generations, optimizing energy systems is ideal. Still, due to the complexity of integrated energy systems, such a feat is by no means easy. Here is where computer-aided decision-making can be very game-changing in determining the optimum point for supply and demand. The concept of artificial intelligence (AI) and machine learning (ML) was born in the twentieth century to enable computers to simulate humans’ learning and decision-making capabilities. Since then, data mining and artificial intelligence have become increasingly essential areas in many different research fields. Naturally, the energy section is one area where artificial intelligence and machine learning can be very beneficial. This paper uses the VOSviewer software to investigate and review the usage of artificial intelligence and machine learning in the energy field and proposes promising yet neglected or unexplored areas in which these concepts can be used. To achieve this, the 2000 most recent papers in addition to the 2000 most cited ones in different energy-related keywords were studied and their relationship to AI- and ML-related keywords was visualized. The results revealed different research trends in recent years from the basic to more cutting-edge topics and revealed many promising areas that are yet to be explored. Results also showed that from the commercial aspect, patents submitted for artificial intelligence and machine learning in energy-related areas had a sharp increase.

Introduction

     Economic development and increasing welfare are always entangled with the rising consumption of energy resources. Increasing energy generation as the default answer to how to cope with this additive energy consumption may not be the best answer. From an energy justice perspective, it’s not acceptable to deplete energy reservoirs that belong to the next generations [1]. Although retrofitting existing equipment and minimizing energy usage by combining (or cascading) multiple systems for increased efficiency may be an answer to this challenge, increasing efficiency may not be the ideal solution. It’s valid that efficiency leads to lower consumption, but it should be noted that many of these systems might also be able to be turned off or operate on lower loads. So, a more dynamic approach may be a better solution.

     Artificial intelligence and machine learning are relatively new concepts in energy that can be promising tools to operate systems by implementing past and predicted futures to increase the effectiveness of systems.

Conclusion

     The concept of artificial intelligence (AI) and machine learning (ML) is for computers to simulate humans’ learning and decision-making capabilities. With advances in computing systems, AI and ML have become increasingly important areas in many different branches of science and industry. The energy section is also one of the areas that can benefit from AI and ML. To investigate the current standing point of AI and ML in energy-related areas, we used VOSviewer software to investigate and review the relatively new usage of AI and ML in the energy field and propose promising or neglected areas in which these concepts can be used.

     The results showed that from 2000 AI gains an increasing focus, especially after 2014 when the number of articles in ML skyrocketed. And in 6 years become 10 times more compared to 2014. Although there have been many papers in different fields of energy that introduced new usages of AI and ML in that section, due to the vastness of energy usage and respected fields of it, obviously, in no way the available articles could cover all these areas.

Abstract

Keywords

Introduction

Smart electric pole

Sustainable power unit

Conclusion

Data Availability Statement

Declaration of Competing Interest

References

Abstract

With the effective result of IoT architecture in all research areas, we propose IoT framework based energy efficient smart and intelligent street road lighting system that consist of IoT sensor bases smart electric pole with controller for tuning LED lamps. In our work we replace traditional metal halide lamps with mesophic design LED lamps based on human eye sensitivity and it provides significant saving of energy too. Based on the sensor unit information about traffic flow and presence and absence of occupant smart and intelligent decision making module compute intensity level that generate different width pulse using PWM dimming system which triggers LED power switch via DALI controller mounted inside LED Light Controller. For efficient use of sustainable energy resources we use sustainable power systems that consist of PV solar panel units, Battery storage systems and smart electric power grids. For the charging battery system we use MPPT based dynamic battery charging algorithm. From experiment and simulated result, we observe that proposed energy efficient Smart Street lighting saves considerable amount of energy during peak and off peak hours not only at highway roads but at residential and sub-urban pedestrian areas also.

Introduction

Sustainable energy is the method of utilizing energy in an efficient way and at the same time satisfying the needs of the modern world. Sustainable energy can be used in economic, social and environmental issues. An efficient sustainable energy management system can be achieved by using renewable resources in all the possible ways, using sustainable energy resources, using alternative energy resources, making use of smart systems, implementing IoT systems, implementing green technologies. The smart system is the technique, which is used to embed the modern technology into functions already used by the world. In terms of smart system, the information about utility system and traffic flow of the large cities is extracted with the help of sensor also it analysis the pattern of information for prediction. Then, the ability to transfer data over a network without the help of human-to-computer or human-to-human interaction is called IoT or internet of things system and the green technology is used to explain the functions of science and technology to develop products as environmental friendly. Some of the examples of green technology is water purification, conserve natural resources, clan energy creation and waste recycle management. It is also used in digital and mechanical machines, objects and in correlated computing devices.

Abstract

     The paper studies the performance of Offshore Wind Turbines (OWTs) founded on Suction Bucket Jackets (SBJs) in clay under combined wind and seismic loading. A detailed 3D FE model of the soil–foundation–structure (SFS) system is developed and used as a benchmark to assess the efficiency of an enhanced Winkler-based “Caisson-on-Winkler-Soil” (CWS) model, where the soil is replaced by nonlinear hysteretic elements. The proposed CWS model captures residual deformations and hysteresis and offers physical coupling between vertical and moment loading. It allows excellent prediction of the  failure envelope in the most relevant first quadrant of  space, where the loads act in the same direction. Despite its successful application for the simulation of inertial loading, the CWS model fails to reproduce the dual shearing mechanism that develops at the caisson shaft during shaking, stemming from the combination of kinematic soil shearing due to the vertically propagating shear waves, and shearing due to the superstructure inertial response, thus underpredicting the co-seismic caisson settlements. For the prediction of the latter, the research utilizes spectrum compatible input motions and 3D FE models of varying geometric and material properties to derive linear regression equations that correlate the co-seismic dimensionless settlement of caissons ) with characteristic dimensional variables of the problem under investigation and the Arias Intensity  of the surface ground motion. As a final step, the paper proposes a hybrid method for performance-based assessment of SBJ OWTs. The proposed method employs the simplified CWS model to calculate the VHM loads and approximately estimate horizontal displacements and rotations at the jacket legs, followed by a preliminary assessment of caisson settlements using the correlations of  with  on the basis of spectrum-compatible input motions.

Introduction

     Following the ambitious energy targets set by countries worldwide, the offshore wind sector has seen impressive growth over the last decade, transforming from niche technology to a global industry. As of 2019, Europe alone has 22 GW of installed offshore wind capacity – enough to cover 2.3% of its electricity consumption [1], while similar or even more potent growth is observed in many countries around the world, such as China, the USA, and India. Part of this energy transition is led by technology-driven innovation, with offshore wind turbines reaching new heights and larger capacities, while wind farms are moving deeper into the sea to harness the increased energy potential. Giventhis new “deep-water” environment, traditional OWT support structures are gradually being replaced by more cost-effective and agile foundation systems in a quest for reduction of investment costs.

Conclusions

     The paper has developed a simplified performance-based assessment technique for SBJ OWTs founded in clay under the combined action of wind () and earthquake () loading. Using an example of an 8 MW jacket-supported OWT, installed at 60 m depth in the Adriatic Sea, system performance was assessed employing a detailed 3D FE model of the soil–foundation–structure (SFS) system (global 3D FE model). After deriving insights on system performance, the global 3D FE model was used as a benchmark to assess the efficiency of an enhanced Winkler-based “Caisson-on-Winkler-Soil” (CWS) model. Soil–suction caisson interaction is represented by nonlinear hysteretic elements, capturing residual deformations and hysteresis. The proposed CWS model offers physical coupling between vertical and moment loading by introducing distributed vertical hysteretic elements along the caisson shaft, simultaneously contributing to vertical and moment shaft resistance.

Abstract

1. Introduction

2. PV cell model and design parameters

3. Fuzzy Distribution of PV cell parameters

4. Global sensitivity analysis of PV cell parameters

5. Analysis and discussion

6. Conclusion

CRediT authorship contribution statement

Declaration of competing interest

Acknowledgments

References

Abstract

     Photovoltaic cells can directly convert solar energy into electrical energy, which is environmentally friendly and has a wide range of applications. In practical engineering, the uncertainty of photovoltaic cell parameters has an important impact on cell performance. In order to study the influence of parameter uncertainty on the output performance of photovoltaic cells, a photovoltaic cell model is established and five parameters are selected: irradiation intensity, photovoltaic cell surface temperature, temperature coefficient, equivalent series resistance and equivalent parallel resistance. The influence of these parameters on the output power and conversion efficiency of photovoltaic cells is studied by using the global sensitivity analysis method based on fuzzy theory. The principal and total global sensitivity indexes describing the influence of each parameter on the output performance were therefore calculated and ranked. The key parameters influencing the performance of photovoltaic cells were determined to be related to cell surface temperature and equivalent parallel resistance. In actual production and life, the output performance of photovoltaic cells can be improved by controlling these two factors. The results of this study can help to guide the performance analysis and parameter optimization of photovoltaic cells, accelerating the development and improving the adoption of photovoltaic systems.

Introduction

     With the aggravation of the global energy crisis and increasing environmental pollution, the development of solar energy occupies a critical position in the energy structure (Wang et al., 2021b, Xiong et al., 2022). As photovoltaic (PV) cells directly convert solar energy into electric energy, they represent an increasingly popular source of renewable energy. The number of deployed PV power generation systems has significantly increased worldwide (Wang et al., 2021a, Wu et al., 2022), and many countries have introduced grid pricing policies to accelerate investment in PV power generation. Therefore, research into the performance of PV cells is of great significance for ensuring their continued adoption (Sharma et al., 2021, Sadan and Dwivedi, 2020). To date, many experts and scholars have studied the parameters of PV cells (Chehreh Ghadikolaei, 2021, Chen et al., 2020, Chandran et al., 2021, Ganesh Pardhu and Kota, 2021, Ji et al., 2021). For example, Chen et al. (2020) used variables reduction and improved shark optimization technique to extract photovoltaic cells parameters, Chandran et al. (2021) proposed an improved distribution estimation algorithm to estimate the optimal parameters of fuel cells and solar cells, and Ganesh Pardhu and Kota (2021) proposed a new random radial shift optimization algorithm based on a group algorithm to extract the unknown parameters of solar PV cells. The confirmation and extraction of parameters of photovoltaic cells and their components is of great significance for evaluating the performance of photovoltaic cell systems and preventing aging and failure of systems and components.

Conclusion

     To address the instability of PV cell output performance according to the inherent fluctuation of design parameters, this study applied the global sensitivity index based on fuzzy theory to measure the influence of inherent design parameter fluctuation on the stability of PV cell output power  and conversion efficiency . The Monte Carlo method was used to calculate the principal and global sensitivity indexes of the design variables based on the credibility variance. The results show that compared with the cell surface temperature  and equivalent parallel resistance , the total global sensitivity index values of the short-circuit current temperature coefficient , irradiation intensity , and equivalent series resistance  are minimal for both the output power  and conversion efficiency , and the effects of their variation can therefore be ignored. Therefore, the key design parameters of PV cells are related to the working environment () and material (). In actual production and application, the output performance of PV cells can therefore be improved by controlling material selection(ensure a consistent equivalent parallel resistance ) and expected working environment temperature . The results of this study can provide guidance for the design and optimization of future PV cells, and further improve their application and utility to increase adoption.

Abstract

1. Introduction

2. Methods

3. Results

4. Conclusions

Code availability

CRediT authorship contribution statement

Declaration of competing interest

Acknowledgements

References

Abstract

     Urban sustainability is a significant factor in combating climate change. Replacing polluting by renewable energies is fundamental to reduce the emission of greenhouse gases. Photovoltaic (PV) facilities harnessing solar energy, and particularly self-consumption PV facilities, can be widely used in cities throughout most countries. Therefore, locating spaces where photovoltaic installations can be integrated into urban areas is essential to reduce climate change and improve urban sustainability. An open-source software (URSUS-PV) to aid decision-making regarding possible optimal locations for photovoltaic panel installations in cities is presented in this paper. URSUS-PV is the result of a data mining process, and it can extract the characteristics of the roofs (orientation, inclination, latitude, longitude, area) in the urban areas of interest. By combining this information with meteorological data and characteristics of the photovoltaic systems, the system can predict both the next-day hourly photovoltaic energy production and the long-term photovoltaic daily average energy production.

Introduction

     Cities have become a determining factor in climate change, as they are the place where much energy is consumed (64% of global primary energy use) and high levels of greenhouse gases emitted (70% of the global total), due to the use of fossil fuels as energy sources (International Energy Agency, 2016). There is a great opportunity for citizens to reduce these emissions. Replacing polluting energy sources by renewable energies that respect the environment and do not compromise future generations is one of the essential requirements to achieve energy-sustainable cities and favour the fight against climate change. Additionally, switching to renewable energy sources as a detriment to polluting energies could improve health and quality of life. Precisely, one of the goals proposed in the 2030 Agenda for Sustainable Development by UN is making cities inclusive, safe, resilient and sustainable (United Nations, 2015).

     Solar energy has seen a large increase among renewable energies. According to the International Energy Agency (IEA), there was a 22% growth up to 720 TWh (representing 3% of global electricity generation) in 2019 (International Energy Agency, 2020). Although large photovoltaic infrastructures are away from cities, there has been an exponential rise in distributed installations in buildings, industry and houses in Europe, the United States and Japan (International Energy Agency, 2020). This is very important since local production reduces transportation losses and enhance citizen’s responsibility because of inspiration for searching for energy self-sufficiency. In recent years, a new type of building, based on that type of installation, has been proposed as an evolution of Zero Energy Building (ZEB): the Positive Energy Building (PEB) (Magrini et al., 2020).

Conclusions

     An open-source tool, URSUS-PV, has been built to estimate potential electricity that can be generated in photovoltaic (PV) facilities in the short-term (one-day-ahead) and in the long-term (daily average) in an urban area of interest (neighbourhoods, streets, complex buildings). It could be potentially useful for multiple types of users, including municipalities, public administrations, companies in the photovoltaic sector, cooperatives or neighbourhood communities.

     One of the tools’ most significant benefits is the automation of the complex process. It initially had to be performed manually to obtain global results in urban areas of interest to produce short-term or long-term photovoltaic energy estimations. After conducting a data mining process, such manual processing has now been computerized. CRISP-DM methodology has supported the process. We have executed all the steps from the business understanding to the final deployment, which includes models discovered in intermediate phases. Therefore, following such methodology, once the data sources (meteorological and geographical data) have been identified, its acquisition and integration are automated. Transformations done in the preprocessing stage are also programmed, meaning that segmentation of the roofs available in urban areas of interest and extraction of their features can be easily computed. The calculating photovoltaic energy potential phase has also been fully automated using meteorological data of the city and the configuration of PV facility that could be integrated into each roof.

Abstract

     The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria Decision Making (MCDM) methods have been used successfully in various renewable energy technology selection problems, the decision process becomes more challenging when preferential judgements are made on the basis of non-homogenous and imprecise input data, and when there is uncertainty due to disparities among decision makers. This paper presents a hybrid MCDM method capable of overcoming these problems by taking into account quantitative and qualitative data under a probabilistic environment in the context of group decision making. In this method, qualitative data is fuzzified and used along with quantitative data to develop a hybrid model. A coefficient factor allows decision makers to vary the weight of each quantitative model so that the resultant criteria weights and overall alternatives’ scores consider both subjective considerations and objective information. An example is presented to showcase the usability of the method developed for ranking and evaluating renewable energy technologies in the mining industry. In addition, the impact of different coefficient factors on the final results was assessed by means of sensitivity analysis. The results indicate that the method developed is able to minimise the loss of valuable objective information, caused by the subjective bias of qualitative weights during the evaluations, by adjusting the coefficient factors of the hybrid model during the calculations.

Introduction

     Energy-generating technologies that depend on non-renewable fossil fuels result in significant environmental challenges, such as increasing greenhouse gas (GHG) emissions, which lead to climate change (Disli et al., 2016, Li et al., 2020). In response to these challenges, it is important to better exploit renewable energy technologies (e.g. wind and solar), which are low-cost, clean and sustainable (Cunden et al., 2020, Dincer, 2000).

     The selection of renewable energy technologies is a complex and multidisciplinary problem that mainly refers to the performance of the technologies concerning multiple criteria such as environmental, social, technical and economic (Wu et al., 2018). In order to evaluate holistically and select the technologies that have a higher performance appropriately, decision makers need to have methodological tools that incorporate both quantitative and qualitative analyses of the multiple criteria. Decision makers should, therefore, make use of the best tools available to evaluate the performance criteria of renewable energy technologies. Choosing the best renewable energy technology to use among various alternatives considering conflicting criteria is thus considered a Multiple Criteria Decision Making (MCDM) problem (Büyüközkan & Güleryüz, 2017).

Conclusions

     A hybrid MCDM method was proposed and was applied to the selection of renewable energy technologies in the mining industry, which faces an increase in energy demand as high grade ores are depleted and the demand for metals and minerals, including those required for renewable energy technologies, increases. The large scale of mining operations makes it very important to consider renewable energy options in order to contribute to the sustainability of the operations.

     Three renewable technology alternatives, namely onshore wind, concentrated solar power, and solar photovoltaic, were assessed taking into account both subjective considerations and objective information with respect to five sustainability criteria. The selected criteria were potential total power generation, GHG emissions, area requirement, levelised energy cost, and prospective jobs creation. An objective weight was obtained using data compiled from the literature, whereas a subjective weight was obtained from the judgements and preferences of four experts. The proposed method was then employed to compute the criteria weights and the alternatives’ scores.

Abstract

     An increasing number of offshore wind farms are being constructed in seismic regions over liquefaction susceptible soils. This paper presents a methodology for the analysis and design of monopiles in seismically liquefiable soils by extending the established “10-step methodology” with an additional 7 steps. These additional steps include assimilation of seismic data, site response analysis, stability check of the structure (ULS check through the concept of load-utilization ratio), input motion selection, prediction of permanent tilt/rotation, and ground settlement post liquefaction. A flow chart, which shows the interdependence of the different disciplines, is presented and can be extended to routine design. This proposed method is validated using the observed performance of an offshore and nearshore turbine from the Kamisu wind farm during the 2011 Great East Japan earthquake. Predicted results based on the proposed methodology compare well with the field observation and demarcate the (i) good overall performance of the offshore turbines and (ii) limit state exceedance of the nearshore turbine. It is envisaged that the proposed method will be useful towards the design of monopiles-supported wind turbines in seismic areas.

Introduction

     Towards the end of 2020, the global wind energy generation capacity amounted to 733 GW, with new installations accounting for 111 GW, almost doubling that of 2019 [1]. Due to higher efficiencies and more stable wind conditions offshore than onshore sites, an increasing proportion of wind power is produced through large offshore wind farms. This demand for cost-efficient wind energy production has facilitated the industry to develop larger turbines with higher capacities. Fig. 1 presents the evolution of turbine capacity over the last 16 years, color-coded with rotor diameter. However, due to the high capital investments involved, profitability of these wind farms requires continuous operation and immediate functionality post-natural hazards. Therefore, the seismic resilience of OWTs is an important consideration in their engineering design and is, therefore, an area of active research. Readers are referred to recent publications [[2], [3], [4], [5], [6], [7], [8], [9]] on various aspects of seismic design.

Discussion and conclusions

     An existing framework for the foundation design of monopile-supported wind turbines was extended to include seismic load considerations in liquefiable and non-liquefiable soil. The framework was validated using a case study from Wind Power Kamisu, a near-shore farm that performed well during the 2011 Tohoku earthquake and subsequent tsunami.

The discussion and conclusions are presented succinctly below:

     1. A quantitative appraisal of appropriate damping, as recommended by Lombardi and Bhattacharya [58] and Adhikari and Bhattacharya [57], could vary the structural demands and therefore needs proper consideration. Back analysis of a case study from the Kamisu wind farm further indicated that structural demands could vary if suitable damping models are not selected.

      2. Definition of mechanism-specific p-y spring models for liquefiable and non-liquefiable soil is necessary as their selection could underpredict or overpredict structural response (deformation, tilt, RNA acceleration). As near-level ground conditions prevailed in this study, the authors employed hyperelastic (strain hardening) p-y curves for liquefiable soil to account for the increased resistance attributed to shear strain-induced soil dilation. During shear strain excursions, such dilative tendencies can transfer high acceleration pulses to the RNA and therefore need to be accounted for in the design stage.

Abstract

     Energy efficiency is one of the most important issues of today. The limited reserves of fossil fuels make the use of renewable energy sources more attractive. Photovoltaic panels are one of the ways to utilize solar energy, which is one of the renewable energy sources.

     The instantaneous efficiency of photovoltaic panels is related to the cell temperature of the panels. In the current studies in the literature, there are empirical expressions that give the photovoltaic panel cell temperature, but the results obtained from these expressions do not overlap with each other. In order to obtain the instantaneous efficiencies of photovoltaic panels and, accordingly, the production values theoretically, there is a need for a global expression that gives the photovoltaic panel cell temperature. In this study, a global expression was developed that gives the photovoltaic panel cell temperature depending on the ambient temperature, solar radiation and wind speed. In addition, using the meteorological data of Kütahya for many years, expressions giving ambient temperature, solar radiation and wind speed were created.

Introduction

     The limited reserves of fossil fuels make renewable energy sources more attractive day by day. While the world primary energy consumption was 581.51 exajoules in 2019, this value was 557.1 exajoules in 2020 (BP, 2021). The amount of renewable energy sources in primary energy consumption in 2019 was 28.82 exajoules (5 %), and in 2020, primary energy consumption from renewable energy sources was 31.71 exajoules (5.7 %) (BP, 2021). From renewable energy sources, 2,789.2 TWh of electricity was produced in 2019 and 3,147.0 TWh in 2020 in the world. While total solar energy production was 707.9 TWh (25.4 %) in 2019, total solar energy production was 855.7 TWh (27.2 %) in 2020 (BP, 2021).

     Table 1 and Table 2 show the solar energy installed power and solar energy production values for 10 years between 2011 and 2020 (BP, 2021). When the tables are examined; It is seen that the installed PV power in the world has increased by 882 % in 10 years. Likewise, electrical energy production from PV systems has increased by 1,212 % over the 10-year period.

     Fig. 1 shows Turkey’s solar energy situation. While the total installed power was 7 MW as of the end of 2011, this value increased by 95,143 % and reached 6,667 MW at the end of 2020. Likewise, while electricity generation from solar energy was 2.86 GWh in 2011, this value increased by 378,732 % in 10 years and reached 10,834.6 GWh (BP, 2021).

Evaluations and suggestions

     In the current studies in the literature, there are empirical expressions that give the photovoltaic panel cell temperature, but the results obtained from these expressions do not overlap with each other. In order to obtain the instantaneous efficiencies of photovoltaic panels and, accordingly, the production values theoretically, there is a need for a global expression that gives the photovoltaic panel cell temperature.

     The instantaneous efficiency of the photovoltaic panel and the generation of electrical energy depending on the efficiency are related to the cell temperature of the photovoltaic panel. Within the scope of this study, a global expression that gives the photovoltaic panel cell temperature was created by using real photovoltaic plant data with the 7 most popular expressions in the literature that give the photovoltaic panel cell temperature. With the obtained expression, instantaneous photovoltaic panel temperature can be obtained depending on the ambient temperature, solar radiation and wind speed.

Building energy use is expected to grow by more than 40% in the next 20 years. Electricity remains the largest energy source consumed by buildings, and that demand is growing. To mitigate the impact of the growing demand, strategies are needed to improve buildings’ energy efficiency. In residential buildings home appliances, water, and space heating are answerable for the increase of energy use, while space heating and other miscellaneous equipment are behind the increase of energy utilization in non-residential buildings. Building energy management systems support building managers and proprietors to increase energy efficiency in modern and existing buildings, non-residential and residential buildings can benefit from building energy management system to decrease energy use. Base on the type of building, different management strategies can be used to achieve energy savings. This paper presents a review of management strategies for building energy management systems for improving energy efficiency. Different management strategies are investigated in non-residential and residential buildings. Following this, the reviewed researches are discussed in terms of the type of buildings, building systems, and management strategies. Lastly, the paper discusses future challenges for the increase of energy efficiency in building energy management system.

1. Introduction

Buildings such as residential, education, office, healthcare, and industrial are emerging as critical consumers in energy consumption. Energy consumption for buildings represents 30–45% of global energy use [1–3], with a larger part of the energy used by the building subsystems, which consist of cooling and heating systems; safety, water, lighting, and similarly combined subsystems. In this context, efforts at this time are focused on the fulfillment of the requirements for energy-efficient in buildings, by guaranteeing the operative needs with the base conceivable energy cost and environmentally friendly [4]. In many developing and developed countries, energy efficiency is viewed as the best mechanism to address and defeat ever-rising energy needs [5]. In any case, advancing the energy efficiency of these subsystems is very testing since they typically have to comply with complex working requirements, dynamic energy necessity, and comfort needs [6].

Abstract

For reducing the energy use of buildings, the application of insulation materials can be a possible solution to improve energy efficiency. However, with the continuously tightening regulations, thicker and thicker insulations should be used (e.g., up to 20–25 cm in Hungary and about 40–50 cm in the Nordic countries) to fulfil the directives. In the past decades, developmental research started to focus on both decreasing the thickness and decreasing the thermal conductivity of materials parallels. With this research direction, the investigations of the new type of insulation materials took place. The use of materials having thermal conductivity with less than 0.020 W/mK spread over. These materials are the so-called super insulation materials. Besides Vacuum Insulation Panels (VIPs), aerogel-based materials belong to this group, too. This paper will present laboratory tests executed on two altered types of protected Vacuum Insulation Panels: a one side and a 2 side protected VIP, also called Vacuum Insulation Sandwich (VIS). The first one, type “A” contains 20 mm thick laminated fumed silica, covered with 10 mm thick expanded polystyrene on one side, while type “B” was the one where the 10 mm thick laminated fumed silica core was packed between two 10 mm thick EPS slabs. Firstly, thermal insulation performance was investigated by the so-called guarded hot-box method for U-value, where the samples were placed on a solid brick wall. Furthermore, the thermal insulation performance of protected VIPs was also tested with Hukseflux heat flux plates. To reveal the applicability limits caused by the thermal bridges infrared thermography images (IR) were taken, too. From the images and the measurement results, a theory was formed regarding the heat flow directions inside the encapsulated panels. The current article emphasizes the equivalent thermal conductivity for the assessment of the thermal protection performance of vacuum insulation panels. The paper states that by using VIPs at least, 70% reduction can be reached in the U-value compared to the value of the solid brick wall. Moreover, the paper points out that the use of EPS protection layer on both sides of the VIP has a promising effect by reducing the thermal bridges. Furthermore, the VIP protected with EPS slabs on both sides results in less equivalent thermal conductivity.

1. Introduction

Nowadays, reducing significantly the energy consumption is an important issue for the building sector, but the reduction of energy use cannot neglect the thermal comfort requirements. Heating and cooling account for at least 40% of the final energy use of the European Union. Moreover, it was predicted by the International Energy Agency (IEA) by the energy use of the countries all over the world could reach up the unwanted 50% until the year 2030 [1–3]. That is why the application of thermal insulation materials in the buildings is very significant. Several types of insulation materials are available [4], but nowadays the use of super insulation materials (SIM) is also widespread, resulted in the development of the industry sector [5]. In cases where greater thickness (15 ~ 20 cm) cannot be used, materials with less thermal conductivity must be applied. It is mentionable that there is no exact definition of SIMs but the IEA EBC Annex 65 ‘‘SIM” Subtask 1 [6] defines the elements of these groups. According to this Annex, these materials are said to be the part of this group: (a) Vacuum Insulation Panels (VIP); (b) Advanced Porous Materials (APM), for example, different types of aerogels (monoliths or fibrous ones). Their most important property is the thermal conductivity, possibly less than 0.022 W/ mK [7]. These insulation materials are also called nanostructured materials, due to their nano-sized pore structure [6]. The application limits of these mentioned materials are written in [8,9] but now the vacuum insulation panels will be in focus.