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Despite sustained interest in spatial planning approaches for steering renewable energy development, the effect of these practices remains poorly understood. This paper addresses this knowledge deficit through comparative analysis of the effects of spatial planning approaches on wind energy deployment in Italy and the UK. Our approach elucidates the different roles that spatial planning approaches can perform using a "modes of governing" framework that, innovatively, recognizes the unavoidable compromises involved in their construction. Several distinctive findings emerge. First, governments deploy spatial planning approaches with different governance purposes, thus explaining why the effects on RE outcomes can be ambiguous. Second, many of the challenges that beset spatial planning approaches arise not from technical-methodological issues but from difficult-to-resolve governance challenges of cross-scalar coordination. Third, we show that the efficacy of spatial planning approaches in shaping RE deployment is contextual in nature, reflecting how far their inherent compromises are accepted by key actors. [ABSTRACT FROM AUTHOR]

The availability of freshwater and energy is a serious issue in remote and islanded areas, especially at a small scale, where there may not be the possibility to access the grid and/or water distribution systems. In this context, polygeneration systems operating on the basis of local, renewable energy sources can be an answer to the users' demand for electricity, heating, cooling, and domestic hot water. The scope of the proposed paper was to investigate, numerically, the energy and economic feasibility of a novel hybrid polygeneration system powered by biomass, solar, and wind energy for a micro-district of households. The proposed system consists of a biomass-fueled steam cycle, wind turbine, photovoltaic field coupled with thermal and electrical energy storage, adsorption chiller, and a reverse osmosis water desalination unit. The system is also assisted by an LPG generator set running as backup. The system provides space heating and cooling, electrical energy, and fresh and domestic hot water to 10 households located on Pantelleria Island, Italy. The proposed system is modelled and simulated through TRNSYS software with realistic user demand. The energy and economic performance of the proposed system are assessed with respect to a reference system in different scenarios, taking into account islanded operation, connection to the grid, and biomass tariffs. The results show that the proposed system achieves an excellent primary energy saving performance in all the investigated scenarios, with savings of more than 94% for all the investigated scenarios. Excluding any kind of funding, in case of new investment for the system, the simple payback oscillates between 7 and 12 years, showing that the developed alternative is fairly valid with respect to traditional solutions. [ABSTRACT FROM AUTHOR]

The exploitation of distributed renewable energy sources leads to a low-carbon energy transition, mainly based on the optimal integration of hydro, PV and wind power plants with the remaining high-performance fossil-fuel power stations. In the last twenty years, European Union (EU) countries have shown a significant increase of the power installed in new PV and wind power plants, together with the refurbishment of small and medium size hydro stations. In particular, in Italy, PV and wind energy production has strongly increased and nowadays there are regions characterized by a very green energy mix. In this new scenario, energy storage becomes a viable solution to mitigate the variability of renewable energy sources thus optimizing the network operation. The present paper is focused on the Liguria region, in the North of Italy and in particular on the Bormida Valley where nowadays more than the half of the annual electricity consumption is covered by the renewable energy local production. The paper describes the current energy situation and proposes an optimization tool to investigate the possibility of installing new PV and wind power plants, as well as energy intensive storage units based on sodium-sulphur batteries; moreover, different scenarios are analyzed through the definition of economic and environmental key performance indicators. [ABSTRACT FROM AUTHOR]

New technological solutions are required to control the impact of the increasing presence of renewable energy sources connected to the electric grid that are characterized by unpredictable production (i.e., wind and solar energy). Energy storage is becoming essential to stabilize the grid when a mismatch between production and demand occurs. Among the available solutions, Power to Hydrogen (P2H) is one of the most attractive options. However, despite the potential, many barriers currently hinder P2H market development. The literature reports general barriers and strategies to overcome them, but a specific analysis is fundamental to identifying how these barriers concretely arise in national and regional frameworks, since tailored solutions are needed to foster the development of P2H local market. The paper aims to identify and to analyze the existing barriers for P2H market uptake in Italy. The paper shows how several technical, regulatory and economic issues are still unsolved, resulting in a source of uncertainty for P2H investment. The paper also suggests possible approaches and solutions to address the Italian barriers and to support politics and decision-makers in the definition and implementation of the national hydrogen strategy. [ABSTRACT FROM AUTHOR]

Although it is widely accepted that renewable energy consumption is vital for environmental sustainability, the environmental effectiveness of individual renewable energy types is often overlooked. Therefore, this paper examined the multivariate relationship between disaggregated renewable energy (hydroelectricity, wind, solar and biomass) consumption, economic growth and environmental pollution for the period from 1991 to 2014 in G-7 (The Group of Seven) countries. The study used both augmented mean group estimator and panel bootstrap causality method to consider the cross-sectional dependence and country specific heterogeneity across G-7 countries. Empirical findings indicate that increasing biomass energy consumption was efficient to reduce carbon emission in France, Germany, Japan and the United States; increasing hydroelectricity usage was efficient to reduce carbon emission in Italy and the United Kingdom; wind energy consumption reduced emission in Canada and solar energy usage was efficient on reducing emission in France and Italy for observed period. Moreover, in case of panel, it is found that increasing hydroelectricity, biomass and wind energy consumption reduced carbon emissions while the impact of solar energy consumption is statistically insignificant in G-7 countries. In addition, the hydroelectricity consumption was found the most efficient renewable energy source to reduce environmental pollution for the panel of G-7 countries. • Disaggregated renewable usage consumption and carbon emission nexus is investigated. • Increasing hydroelectricity usage reduces emission in Italy, the UK and the US. • Increasing wind energy usage reduces emission in all G-7 countries excluding Japan. • The effect of solar energy consumption on emissions is statistically insignificant. [ABSTRACT FROM AUTHOR]

The need to reduce greenhouse gas emissions is driving many actions to decarbonize the most impactful sectors. Among these, the energy sector accounts for almost one third of emissions. Increasing the penetration of renewable energy in the energy mix could easily reduce the emissions of this sector. Theoretically, the target to aim for would be 100% renewable energy production. However, the variable nature of power production from photovoltaic and wind systems, which are expected to play a key role in the energy transition, may pose several limitations to the effective penetration of renewable energy. Many concerns arise when one considers the large diffusion of renewable energy that would be required to meet green targets, and the operating conditions of other systems in charge of compensating for renewable energy variations. This study aims to investigate the potential impact of an increase in the amount of renewable energy installed in a country, particularly in Italy. A simplified approach has been used, based on the assumption of knowing the hourly demand and power generation mix, and multiplying the intermittent power generation by a certain factor. Although not accurate, this approach allows the authors to highlight some critical aspects regarding the potential surplus of renewable energy and the operating conditions of other energy sources. The results of this study may provide a useful basis for a preliminary system evaluation, in particular to assess the feasibility of surplus recovery and the operability of residual generation systems. In addition, it may be easily replicated in other countries for similar estimations. [ABSTRACT FROM AUTHOR]

At present, photovoltaics is, after hydro and wind power, the third most important renewable energy source in terms of its capacity to be globally installed; furthermore, for two years in a row, it was the number one new source of electricity generation installed in the European Union. Italy became the second country in the European Union concerning the cumulative installed power of PV (in 2013, the Italian PV cumulative power reached over 17,620 MW), which was also the result of the very attractive support policy. In connection with this development, the issue has emerged about the treatment and disposal of photovoltaic waste when the operative time (approximately twenty-thirty years) of the photovoltaic systems ended. The European Union, to address this environmental impact, passed the Directive 2012/19/EU to increase the amount of waste of electrical and electronic equipment in the form of photovoltaic panels that have been appropriately collected and treated to reduce the volume that become disposed. This paper aims to provide an assessment of the potential waste arising in Italy from the use and end-of-life phases of these renewable energy systems in the coming years and their disposal and/or recycling. Based on the lifetime of 25 years of photovoltaic panels, the estimate has been referred to two periods of waste generation (2012 – 2038 and 2039 – 2050). The importance of managing this flow of waste to enhance the correct disposal of the hazardous substances as well as the importance of the recovery and recycling of valuable resources has also been underlined. [ABSTRACT FROM AUTHOR]

A correlation analysis based on Markowitz Portfolio Theory and data from meteorological station are used to develop a decision-making tool for the optimal spatial installation of renewable energy sources from Wind turbines and PV panels. A case study involving power generation plants and weather stations in the region of Tuscany in Italy is developed. The results show that temporal correlations of solar and wind generation profiles are characterized by correlation and anticorrelation. This feature is used for supporting decision-making on investments in renewable energy at the territorial level. [ABSTRACT FROM AUTHOR]

Abstract: In liberalized markets, there usually exists a day‐ahead session where energy is sold and acquired for the following production day. Owing to the high uncertainty of its production, renewable energy (wind in particular) can significantly influence the network imbalance of the following day. In this work, we consider the problem of predicting the sum of the bid volumes for wind energy of all the producers inside the day‐ahead energy market. This is a valuable tool to be used by an energy provider in order to determine the imbalance of a market zone and, thus, properly size its bids. In particular, we focus on the estimation of the possible relationship between the meteorological forecasts and the wind power offered on the market by the companies for a market zone. We propose a machine learning model which is used to compute a 1‐day‐ahead forecast. The input‐output mapping is obtained by support vector regression. The input feature vector is defined by a suitable feature extraction technique since the meteorological forecasts are given on a lattice of thousands of geographical points. The computational experiments are performed considering the Italian market as a case study (years 2012‐2016). The results show that the proposed feature extraction technique, selecting only some geographical zones, manages to reduce the error attained using all the features. Moreover, classical statistical methods are shown to be outperformed by machine learning models. The analysis reveals also some weaknesses of the model, which may be due to other nonmeteorological factors at play. [ABSTRACT FROM AUTHOR]

Supervisory control and data acquisition (SCADA) systems have become widely diffuse in modern wind energy technology. The slowdown of new installations and the increasing percentage of energy entering the grid from renewable stochastic sources has diverted attention to the careful optimization of operating farms. Elaborating the complex data stream from SCADA systems into knowledge poses technological and scientific challenges. SCADA data analysis therefore lies at the crossroads of mechanical engineering, applied mathematics, statistics and physics. In the present work, mathematical methods are proposed for tackling the complexity of SCADA data. This idea is to elaborate simplified and more powerful data sets through one action: discretization of continuous quantities. The approach is employed for two very different issues: performance evaluation and wake effects analysis, which is investigated from the point of view of power losses, due to the difficulties associated with optimal turbine alignment with the wind. Two indexes for performance evaluation are formulated. Recurrent non-trivial orientation patterns of clusters of turbines are individuated, and the efficiency associated to them is analyzed. The methods are tested on two wind farms situated in southern Italy. [ABSTRACT FROM AUTHOR]