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This study investigates the opportunities and challenges of installing Vestas' V172-7.2 MW wind turbine, standing at 199 m, in Lithuania. As part of the country's commitment to sustainable growth and the European Union's goal of achieving a Net Zero Carbon economy by 2050, Lithuania aims to achieve self-sufficiency in energy production, focusing on wind energy projects. The research addresses two key questions: the optimal geographical location for the wind turbine installation and the anticipated outcomes and impacts of the project. Hence, the turbine's technical requirements are researched to offer a clear picture of the manufacturer's minimal standards, such as cleared site radius, distance to residence, highways, and wind speed range. Following that, Lithuanian regulatory standards are investigated for turbine installation in terms of residential zones, protected natural regions, and locations where any construction is controlled or prohibited. Therefore, the research's data is gathered using a multi-method that relies on secondary data techniques. The deductive approach served as a structured framework for results, leveraging theories to help the identification process of suitable wind turbine locations. Delimitations include a focus on the specific features of the turbine, predefined environmental elements, and a holistic view of potential locations. [ABSTRACT FROM AUTHOR]

During the past few years, hydrogen use has come to be considered as an alternative energy carrier in a future decarbonized world. Many developed nations are undergoing a shift towards low-carbon energy sources, driven by the excessive reliance on fossil fuels and the detrimental effects of climate change. This study aims to investigate the potential for hydrogen deployment in the Greek energy market during the next few decades. In this context, green hydrogen's potential application in the Greek market is being assessed, employing an integrated techno-economic model grounded in worldwide trends and localized expenses. The forthcoming years will see an analysis of both the challenges and opportunities surrounding the integration and implementation of hydrogen in new and existing processes within Greece. Many alternative ways to produce hydrogen in Greece are investigated, contemplating different production paths. We evaluate how fluctuations in hydrogen, oil, and carbon prices affect the economics of green hydrogen adoption in oil refining, as is detailed in the draft of the European Union delegated act published in May 2022. The Levelized Cost of Hydrogen (LCOH) for different scenarios is calculated for the time frame up until 2050. A sensitivity analysis reveals that investment costs, electricity prices, electrolyzer efficiency, and carbon taxes significantly influence the LCOH, ultimately impacting the economic competitiveness of hydrogen production. These findings underscore the importance of aligning public–private partnership agendas in hydrogen production to create optimal conditions for investment attraction and development. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had significant effects on the energy industry, leading to shifts in energy demand and generation patterns worldwide. This has created challenges for the energy sector, including disruptions in energy markets and the need for robust healthcare and electricity infrastructures. The pandemic has also resulted in changes in residential energy consumption, with some communities increasing their energy usage while others saw a decrease. Additionally, the adoption of virtual education during the pandemic has led to energy savings in educational institutions. The pandemic has also impacted electricity systems and grids, requiring ongoing research to address the challenges posed. In other sectors, such as transport and tourism, the pandemic has necessitated innovative measures to ensure passenger safety and has led to a reduction in greenhouse gas emissions in the tourism sector. Overall, the pandemic has brought about a new era for the energy industry, highlighting the need for coherent energy policies and the transition to clean energy. [Extracted from the article]

The operation of the electricity grid can be heavily affected by unexpected meteorological phenomena which generate emergency situations that cause extensive outages. This often has to do with weather-related events. In several places in the world, an electricity network operator is responsible for fairly compensating end-users. In Finland, there are areas where these weather-related impacts are significantly harsher than those in other areas. Based on this and historic data, the applicability and viability of a high-temperature proton-exchange membrane fuel cell (HT-PEMFC) backup power system was studied in order to assess the opportunity for its installation in the affected municipalities and regions. When implemented on a larger scale, from both technoeconomic and social perspectives, such systems have the potential to yield significant benefits. Compared to a diesel generator, the HT-PEMFC produced nearly half of the volume of CO2 and its fuel costs were six times smaller; however, it remains inapplicable to individual detached households. [ABSTRACT FROM AUTHOR]

Growing concerns over environmental issues and sustainable living have resulted in increased interest in renewable energy and energy efficiency. The real estate market is no exception, with homeowners increasingly considering the market value of green and sustainable buildings, which can offer both energy efficiency and potential health benefits. This study investigates the level of interest among homeowners in investing in renewable energy sources and energy efficiency measures for their homes and how it relates to their perception of the market value of green or sustainable buildings in the real estate market. A survey was conducted in the Paphos urban complex in Cyprus, with 180 participants over the age of 18. The participants were selected through a random sampling method and were representative of the general population in terms of gender, age, and income. Data were collected on their attitudes towards renewable energy sources and energy efficiency, as well as their perceptions of the market value of green buildings. The data collected were analyzed using various statistical methods, including Cronbach's α coefficient, the non-parametric Friedman test, descriptive statistics, and factor analysis, with the Statistical Package for the Social Sciences (SPSS) being used for coding and analysis. Results indicate that 64% of the homeowners surveyed were interested in investing in renewable energy sources, and 72% were interested in energy efficiency measures. Additionally, findings suggest a moderate level of interest (58%) among homeowners in investing in renewable energy sources and that this is positively associated with their perception of the market value of green buildings. Furthermore, homeowners with higher income and education levels tend to be more interested in investing in renewable energy sources and energy efficiency measures and perceive green buildings as having higher market value. This study provides insights into the factors that drive homeowners' investment in renewable energy sources and energy efficiency measures, shedding light on the relationship between homeowners' perceptions of the market value of green buildings and their interest in such investments. [ABSTRACT FROM AUTHOR]

This study demonstrates the potential of using low-altitude multispectral imagery data to assess irrigation and fertilization techniques and the relative degree of plant water and nutrient stress. This study aims to create a methodology that can be widely used by vertical farms. Techniques were used for early water and nitrogen stress detection using multispectral reflectance systems in an indoor environment with artificial lighting. The methodology focuses on irrigation and nutrition, that sets schedules, and automatically updates a decision-making system based on crop reflectance data and simplified reflectance indices. The experimental process took place on the premises of CphFarmHouse in Denmark. The results showed that crop reflectance increased due to water and nitrogen deficiencies. The detected reflectance increase was significant on the third day of the experiment when irrigation and fertilization were not applied. It should be noted that during the experimental period, the researchers did not detect water or nitrogen deficiencies visible to the naked eye. More specifically, the Normalized Difference Vegetation Index (NDVI) and the Photochemical Reflectance Index (PRI) showed statistically significant differences between the control treatment and the two stress treatments with limited water and nitrogen. Additionally, based on the reflectance measurements and the measured physiological crop parameters, significant correlations (p < 0.01) were observed mainly between the PRI and the chlorophyll content, the photosynthetic efficiency and the stomatal conductance (r = 0.84/0.90, 0.73/0.66, 0.61/0.66 among the nitrogen and water treatments). The research provides data analysis results on sensors and approaches for crop reflectance measurements as well as spectral indices for remote water and nitrogen detection. Finally, the results provide a feasibility analysis, suggesting that multispectral images could be used as a rapid tool to estimate the physiological status of plants, which is indicative of the spatial variation in the vertical farm. [ABSTRACT FROM AUTHOR]

COVID-19 has affected the entire existence of humans. Despite the mass vaccination programs globally deployed, some governments are still struggling to minimize human losses, high rates of virus transmission, and the socio-economic shock the entire planet has being gone through. COVID-19 has seriously affected all global socio-economic sectors. In this direction, agriculture, food-security and the environment could not be outside of the high-scale negative impacts, especially during the first year of the imposed lockdowns on both national and global scales. The present study provides information on the impact of COVID-19 and the lockdowns imposed, having as its study area the Republic of Cyprus. The study focuses on potato cultivation and production, and on which level entire agricultural procedures were affected during the examined period of the lockdown. A survey methodology study was done with questionnaires distributed to local potato farmers across the country to quantify and identify the link between the pandemic and the potato sector of the island. It was revealed that manpower was limited due to the lockdowns, the distribution of crops to markets disrupted, long delays in transactions in the agricultural sector were experienced, and economic uncertainty, in general, in Cyprus was experienced, among other impacts. Results of the study indicated that—since COVID-19 is not going to be the last disease—a global transition towards a more resilient and spatially localised food network is required. [ABSTRACT FROM AUTHOR]

It has been stated that by 2030, South Korea will have increased their capacity for wind power from 124 MW to 12 GW. According to official statements, offshore wind turbines will provide most of this wind energy. In order to determine the costs for an offshore wind energy production site, an economic analysis was performed in Incheon, South Korea, and the levelized cost of energy (LCoE) value was calculated at 129.97 USD per MWh, and the net present value and the internal rate of return were also calculated. Various scenarios were tested, and it was proven that minimum or no governmental support can lead to economically problematic projects. Is zero subsidy the future of the offshore wind industry? [ABSTRACT FROM AUTHOR]

As California's Renewables Portfolio Standard continues to phase power production from fossil fuels, carbon neutral sources will need to be implemented. This sets small-scale wind production and battery storage in a position to integrate into current grid infrastructure as means of production. This would be an "E Pluribus Unum" approach where many decentralized small production and storage units would act in combination to provide a stable grid. This is often referred to as distributed generation (DG). By distributing the grid's production in this manner and designating predetermined regional hubs for control (in the event of a fractured grid due to natural disaster), the state and its residents will be able to maintain power for critical infrastructure and basic utilities. This work presents, in detail, a sustainable plan for achieving carbon neutral Californian grid by 2045. [ABSTRACT FROM AUTHOR]

The overall energy footprint of a plant factory always comes along with the factory siting. Recognizing the challenges that today's hydroponics industry and tomorrow's plant factories are and will be dealing with requires some strategic thinking. In this category of studies, a wind resource assessment can reveal where the losses due to the wind chill factor [[13]] can mean more on the plant factories' losses and where not. [Extracted from the article]

In recent years both the demand and supply for upgrade solutions and repair services are growing. The majority of the American turbine owners are motivated to be able to operate their various fleets of wind turbines on their own and gain sufficient knowledge to do so in a professional manner. With this goal in mind, the learning curve includes optimizing operation cost, fine-tuning practices, and building a network with suppliers. This work focused on hydraulic pitch system designed for a modern wind turbine, technology overview, and economic loss due to leakage. Furthermore, the work covers the drivers of the customers, performance requirements, and evaluation the current solutions that are available on the market. The possible solutions are listed for each scenario and follow up actions are suggested on how to control future processes. The paper describes how to optimize the long-term running costs and discuss on the changes that could maximize the availability percentage. The findings can be also applied to both other platforms in the product line and even other Original equipment manufacturers' (OEM) turbines to a certain extent. [ABSTRACT FROM AUTHOR]

The possibility of replacing the existing autonomous thermal power plants by Distributed Energy Resources (DER) based on renewable energy sources (RES), along with the appropriate energy storage technologies in order to deal with the major problems that autonomous islands usually face was investigated. A case study of a small Greek island, which is confronted by various energy and water shortages, was studied for assessing the feasibility of DER deployment. The main objectives investigated were cost minimization, CO2 emissions minimization and DER reliability maximization. The DER-CAM (Distributed Energy Resources Customer Adoption Model) decision support tool was used for the multi-objective analysis conducted, which proposes a set of optimal solutions defining the appropriate Distributed Generation (DG) technologies, the capacities of storage and other technologies and the optimal dispatch of the DG system. A mutual beneficial solution, for all stakeholders, was proposed indicating the scope for developing such systems for all islands facing the same problems. [ABSTRACT FROM AUTHOR]

Methane (CH4) is an important greenhouse gas emitted by vehicles. This study provides estimates of emissions of this important and often not well characterized greenhouse gas (GHG) emission related to transportation energy use. It aims to assist urban community planners and policymakers to prioritize and choose implementation strategies for low carbon cities. The paper focuses on emissions of CH4 from vehicles. Unlike emissions of CO2, which are relatively easy to estimate, emissions of CH4 are a function of many complex aspects of combustion dynamics and depend on the type of emission control systems used. In this context, they cannot be derived easily and instead must be determined through the use of published emission factors for each combination of fuel, end-use technology, combustion conditions, and emission control systems. Emissions of CH4 play a significant role with regards to the relative CO2-equivalent GHG emissions of the use of alternative transportation fuels, in comparison with the use of conventional fuels. By analyzing a database based on literature review this study analyzes all the factors affecting the creation of CH4 emissions from different vehicle types. Statistical analysis indicated "r" values ranging from 0.10 to 0.85 for all vehicles. [ABSTRACT FROM AUTHOR]

The transportation sector is severely correlated with major problems in environment, citizens' health, climate and economy. Issues such as traffic, fuel cost and parking space have make life more difficult, especially in the dense urban environment. Thus, there is a great need for the development of the electric vehicle (EV) sector. The number of cars in cities has increased so much that the current transportation system (roads, parking places, traffic lights, etc.) cannot accommodate them properly. The increasing number of vehicles does not affect only humans but also the environment, through air and noise pollution. According to EPA, the 39.2% of total gas emissions in 2007 was caused by transportation activities. Studies have shown that the pollutants are not only gathered in the major roads and/or highways but can travel depending on the meteorological conditions leading to generic pollution. The promotion of EVs and the charging stations are both equally required to be further developed in order EVs to move out of the cities and finally confront the range problem. In this work, a wind resource and a GIS analysis optimizes in a wider area the sitting of wind based charging stations and proposes an optimizing methodology. [ABSTRACT FROM AUTHOR]

The transition from the era of massive renewable energy deployment to the era of cheaper energy needed has made scientists and developers more careful with respect to energy planning compared with a few years ago. The focus is--and will be--placed on retrofitting and on extracting the maximum amount of locally generated energy. The question is not only how much energy can be generated, but also what kind of energy and how it can be utilized efficiently. The waste heat coming from wind farms (WFs) when in operation--which until now was wasted--was thoroughly studied. A short-term forecasting methodology that can provide the operator with a better view of the expected heat losses is presented. The majority of mechanical (due to friction) and electro-thermal (i.e., generator) losses takes place at the nacelle while a smaller part of this thermal source is located near the foundation of the wind turbine (WT) where the power electronics and the transformers are usually located. That thermal load can be easily collected via a working fluid and then be transported to the nearest local community or nearby agricultural or small scale industrial units using the necessary piping. [ABSTRACT FROM AUTHOR]

Global carbon dioxide (CO2) emissions reached an all-time high in 2010, rising 45% in the past 20 years. The rise of peoples' concerns regarding environmental problems such as global warming and waste management problem has led to a movement to convert the current mass-production, mass-consumption, and mass-disposal type economic society into a sustainable society. The Rio Conference on Environment and Development in 1992, and other similar environmental milestone activities and happenings, documented the need for better and more detailed knowledge and information about environmental conditions, trends, and impacts. New thinking and research with regard to indicator frameworks, methodologies, and actual indicators are also needed. The value of the overall indicators depends on the production procedure of each material, and indicates their environmental impact. The use of "exergy indicators" based on the exergy content of materials and the use of the second law of thermodynamics in this work presents the relationship between exergy content and environmental impact. [ABSTRACT FROM AUTHOR]

Producing food via vertical farming (VF) is an efficient method since it requires less space with increased yield per unit area. Such a system can assist in solving major food-shortage problems since it presents a higher crop yield per unit area compared to conventional farming. Thus, VF can be seen as a production method that can cope with the challenge of the constantly growing population, making it also possible to cultivate crops in regions with adverse climate conditions. However, the public might be concerned about the sustainability of VF systems since plants are produced in an unconventional setting. Therefore, there is a need to consider and evaluate the consumers' acceptance of VF. The particular study attempts to both analyse consumer acceptance of VF in the Nordic areas and offer insights into VF acceptance among young customers in a comparative analysis. The results indicated that VF is not widely accepted by young Nordic consumers. The concept of sustainability is one of the principles driving forces behind consumer acceptance of vertical farms. The more cases of vertical farms in European cities, the better seems to be the level of acceptance among young customers and their willingness to purchase their products. [ABSTRACT FROM AUTHOR]

In an aim to contribute to already existing knowledge upon the subject of smart cities and the public sector's wider knowledge in Europe, this study investigates the perception by the municipalities and the wider public sector, responsible for implementing smart solutions in the environment. The understanding of the concept of smart cities/villages by municipalities is on a low level due to the fact that the problem is too wide, not well described, solutions even wider, accompanied by the lack of experts able to offer comprehensive solutions to municipalities. The study presents factors according to the current municipalities' knowledge (environmental awareness, knowledge and prior experience) and the existing market, of whether these factors can be said that affect the acceptance of smart cities. The public is already aware of the smart cities as a general concept, however, the study sheds light upon the established knowledge that the decision makers have in five countries, Hungary, Slovakia, Italy, Lithuania, and Denmark. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has affected all areas of socio-economic life around the world. Its impact concerns not only the health system and the health of the population, but also the economy. Tourism is one of the sectors hardest hit by the restrictions imposed by governments in the wake of the pandemic. The pandemic has resulted in restrictions and limitations on movement and travel, covering both domestic and international tourism, which raises the question of have these restrictions imposed on tourist activities also caused an environmental impact? The aim of this article is to examine what impact the COVID-19 pandemic has had on the environmental issues within the tourism sector in the Central and Eastern European (CEE) region. The research task is to investigate whether this impact has changed in the pandemic era compared to previous years, and whether it has been positive or negative. The research method is multiple regression analysis. The results of the study indicated that the COVID-19 pandemic caused a decrease in greenhouse gas emissions from tourism in all CEE countries. Such decreases are both relative to 2019 and the estimated level of emissions that would be achieved if the countries surveyed achieved economic growth in 2020 consistent with the European Commission's projections for that year. The scale of the impact varies from country to country, while the relationship between tourism development and pollution levels is positive. [ABSTRACT FROM AUTHOR]

Covid-19 affects the personal lives of millions and led to an economic crisis. Changed behavioral patterns and a reduction of industrial activity result in a reduction in power demand, and thus Covid-19 impacts the power systems around the world. Bottom-up mapping of the effect of Covid-19 on the energy demand is challenging, if not impossible. In order to analyze the impact of the pandemic on power demand, we instead propose a simplified approach based on an econometric analysis that quantifies the country-wide load reduction of Covid-19, using the number of active cases as well as the specific lockdown period as proxies. The time span covered is from 1 January 2016 to 31 August 2020. This long time span allows us to investigate the effect of Covid-19 on the power demand. We find that in Germany (DE) and Great Britain (GB) the power demand is reduced by about 1–1.7 MW per case, while in France the demand increased by 1 MW per case during times outside of the lockdown. On the other hand, in France the lockdown itself has a much higher load reduction effect in France than in GB and DE. Based on the elasticity of power demand regarding Covid-19 cases, we calculate the impact of Covid-19 on the power prices through reduced loads. We find that Covid-19 reduced power prices by 3 to 6 EUR per MWh. The effect of Covid-19 on carbon emissions in the power sector is likely to be small. In Germany, the country with the highest absolute level, emissions in the power sector were reduced by approximately 2% (4 Mio. t CO2). [ABSTRACT FROM AUTHOR]

The Association of Southeast Asian Nations (ASEAN) faces tremendous challenges regarding the future energy landscape and how the energy transition will embrace a new architecture—including sound policies and technologies to ensure energy access together with affordability, energy security, and energy sustainability. Given the high share of fossil fuels in ASEAN's current energy mix (oil, coal, and natural gas comprise almost 80%), the clean use of fossil fuels through the deployment of clean technologies is indispensable for decarbonizing ASEAN's emissions. The future energy landscape of ASEAN will rely on today's actions, policies, and investments to change the fossil fuel-based energy system towards a cleaner energy system, but any decisions and energy policy measures to be rolled out during the energy transition need to be weighed against potentially higher energy costs, affordability issues, and energy security risks. This paper employs energy modelling scenarios to seek plausible policy options for ASEAN to achieve more emissions reductions as well as energy savings, and to assess the extent to which the composition of the energy mix will be changed under various energy policy scenarios. The results imply policy recommendations for accelerating the share of renewables, adopting clean technologies and the clean use of fossil fuels, and investing in climate-resilient energy quality infrastructure. [ABSTRACT FROM AUTHOR]

Wind energy and wind power forecast errors have a direct impact on operational decision problems involved in the integration of this form of energy into the electricity system. As the relationship between wind and the generated power is highly nonlinear and time-varying, and given the increasing number of available forecasting techniques, it is possible to use alternative models to obtain more than one prediction for the same hour and forecast horizon. To increase forecast accuracy, it is possible to combine the different predictions to obtain a better one or to dynamically select the best one in each time period. Hybrid alternatives based on combining a few selected forecasts can be considered when the number of models is large. One of the most popular ways to combine forecasts is to estimate the coefficients of each prediction model based on its past forecast errors. As an alternative, we propose using multivariate reduction techniques and Markov chain models to combine forecasts. The combination is thus not directly based on the forecast errors. We show that the proposed combination strategies based on dimension reduction techniques provide competitive forecasting results in terms of the Mean Square Error. [ABSTRACT FROM AUTHOR]

Fast-growing energy demand of the world makes the researchers focus on finding new energy sources or optimizing already-developed approaches. For an efficient use of solar and wind energy in an energy system, correct design and sizing of a power system is of high importance and improving or optimizing the process of data obtaining for this purpose leads to higher performance and lower cost per unit of energy. It is essential to have the most precise possible estimation of solar and wind energy potential and other local weather parameters in order to fully feed the demand and avoid extra costs. There are various methods for obtaining local data, such as local measurements, official organizational data, satellite obtained, and reanalysis data. In this paper, the Modern-Era Retrospective analysis for Research and Applications dataset version 2 (MERRA-2) dataset provided by NASA is introduced and its performance is evaluated by comparison to various locally measured datasets offered by meteorological institutions such as Meteonorm and Deutscher Wetterdienst (DWD, or Germany's National Meteorological Service) around the world. After comparison, correlation coefficients from 0.95 to 0.99 are observed for monthly global horizontal irradiance values. In the case of air temperature, correlation coefficients of 0.99 and for wind speed from 0.81 to 0.99 are observed. High correlation with ground measurements and relatively low errors are confirmed, especially for irradiance and temperature values, that makes MERRA-2 a valuable dataset, considering its world coverage and availability. [ABSTRACT FROM AUTHOR]

The current COVID-19 pandemic and the preventive measures taken to contain the spread of the disease have drastically changed the patterns of our behavior. The pandemic and movement restrictions have significant influences on the behavior of the environment and energy profiles. In 2020, the reliability of the power system became critical under lockdown conditions and the chaining in the electrical consumption behavior. The COVID-19 pandemic will have a long-term effect on the patterns of our behavior. Unlike previous studies that covered only the start of the pandemic period, this paper aimed to examine and analyze electrical demand data over a longer period of time with five years of collected data up until November 2020. In this paper, the demand analysis based on the time series decomposition process is developed through the elimination of the impact of times series correlation, trends, and seasonality on the analysis. This aims to present and only show the pandemic's impacts on the grid demand. The long-term analysis indicates stress on the grid (half-hourly and daily peaks, baseline demand and demand forecast error) and the effect of the COVID-19 pandemic on the power grid is not a simple reduction in electricity demand. In order to minimize the impact of the pandemic on the performance of the forecasting model, a rolling stochastic Auto Regressive Integrated Moving Average with Exogenous (ARIMAX) model is developed in this paper. The proposed forecast model aims to improve the forecast performance by capturing the non-smooth demand nature through creating a number of future demand scenarios based on a probabilistic model. The proposed forecast model outperformed the benchmark forecast model ARIMAX and Artificial Neural Network (ANN) and reduced the forecast error by up to 23.7%. [ABSTRACT FROM AUTHOR]

Energy markets with a high penetration of renewables are more likely to be challenged by price variations or volatility, which is partly due to the stochastic nature of renewable energy. The Danish electricity market (DK1) is a great example of such a market, as 49% of the power production in DK1 is based on wind power, conclusively challenging the electricity spot price forecast for the Danish power market. The energy industry and academia have tried to find the best practices for spot price forecasting in Denmark, by introducing everything from linear models to sophisticated machine-learning approaches. This paper presents a linear model for price forecasting—based on electricity consumption, thermal power production, wind production and previous electricity prices—to estimate long-term electricity prices in electricity markets with a high wind penetration levels, to help utilities and asset owners to develop risk management strategies and for asset valuation. [ABSTRACT FROM AUTHOR]

In recent years, a new urban environment in the large metropolitan areas, the so-called "megacities", has emerged. It is estimated that more than five billion people will be located in urban areas by 2030. Many projects have been initiated in the megacities to support the new ecosystem services in providing the most sustainable and efficient food supply solutions, as well as for transporting fresh and clean vegetables. One of the most important focus areas is research on energy sustainability, including how to optimize energy efficiency to meet the needs of citizens and companies. Indoor urban vertical farming (IUVF) is one of the greatest achievements of our time in agriculture, as it is entirely focused on meeting the food needs of people living in urban areas with the lowest environmental and energy costs. IUVF creates a new foundation in the urban food production system, providing opportunities for many other sustainable activities, such as energy and grey water recycling, but beyond all, it helps citizens to have access in fresh and nutritious fruits and vegetables and to become more creative building up their skills regarding sustainable food production. In this study, the internal rate of return (IRR) and the net present value (NPV) indexes were used to compare IUVF and greenhouse (GH) facilities under various financing schemes. Consistent with similar studies, this research also confirms that IUVF is much more profitable for investors, saving significant resources compared to GHs. [ABSTRACT FROM AUTHOR]

Topics such as energy demand, energy security and greenhouse emissions have made countries around the world turn to more environmentally friendly resources to produce electricity. Due to their stochastic behaviour (particularly wind energy and solar photovoltaics (PV)), the energy producers that are renewable energy driven need concrete financial mechanisms in order to sell their generated electricity under uncertainty in a highly competitive environment. In this work, the application of the Feed-in Premium (FiP) policy in the Greek wholesale liberalised electricity market is compared against a multiple revenue stream tactic. The investigation of the financial performance is conducted in terms of Net Present Value and Complete Payback Period of a 10 MW wind park and a 2 MW solar PV park and is questioned under a multiple revenue stream approach. It was found for projects that offer at least 75% of their electricity production to the market, if their operation licence is extended for five more years, incentivising them to participate in the FiP scheme, instead of the Feed-in-Tariff one, this will increase their profitability in most cases, for both wind and PV projects. [ABSTRACT FROM AUTHOR]

In this paper day-ahead electricity price forecasting for the Denmark-West region is realized with a 24 h forecasting range. The forecasting is done for 212 days from the beginning of 2017 and past data from 2016 is used. For forecasting, Autoregressive Integrated Moving Average (ARIMA), Trigonometric Seasonal Box-Cox Transformation with ARMA residuals Trend and Seasonal Components (TBATS) and Artificial Neural Networks (ANN) methods are used and seasonal naïve forecast is utilized as a benchmark. Mean absolute error (MAE) and root mean squared error (RMSE) are used as accuracy criterions. ARIMA and ANN are utilized with external variables and variable analysis is realized in order to improve forecasting results. As a result of variable analysis, it was observed that excluding temperature from external variables helped improve forecasting results. In terms of mean error ARIMA yielded the best results while ANN had the lowest minimum error and standard deviation. TBATS performed better than ANN in terms of mean error. To further improve forecasting accuracy, the three forecasts were combined using simple averaging and ANN methods and they were both found to be beneficial, with simple averaging having better accuracy. Overall, this paper demonstrates a solid forecasting methodology, while showing actual forecasting results and improvements for different forecasting methods. [ABSTRACT FROM AUTHOR]