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With increasing volatility in natural gas markets and the need for residential heat, research for alternative thermal systems based on green hydrogen-based fuels is necessary. Massive implementation of hydrogen in the current fleet presents a challenge for the decarbonisation of conventional thermal processes. This paper presents the integration of green methanol from a seasonal thermochemical energy storage system (TCES) coupled with district heating networks (DHN). It allows for a solar-based storage and low-temperature heat generation from the exothermic discharge reaction. The system uses concentrated solar thermal energy to decompose methanol into syngas at moderate temperatures (<315 °C), reducing GHG emissions from combustion to meet residential heat. Its potential is assessed through an analysis of 458 rural municipalities in Spain, achieving a substitution of 3.1 % of the natural gas demand. The system allows the production of green fuels from syngas using an open-loop approach, offering new market pathways in primary sector. In a closed-loop configuration, roundtrip efficiencies exceeding 60 % and chemical conversion efficiencies exceeding 70 % are reached, resulting in a global efficiency of 12 % for the DHN and methanol-TCES. The results show a levelized cost of stored energy highly competitive with other storage systems (<200€/MWh), given its simplicity. • A novel district heating network integration with methanol TCES is proposed. • Round-trip above 65 % and an overall efficiency of 11.6 % were achieved. • Analysis of presented DH-TCES in 499 rural municipalities in Spain. • Competitive levelized storage price values of €150/MWh was obtained. [ABSTRACT FROM AUTHOR]

Effectively utilizing low-grade thermal energy is a promising approach to mitigating greenhouse gas emissions while reducing the burden on centralized power grids. Current thermoacoustic heat pumps and power generators face challenges such as high onset temperature differentials and low performance. This paper addresses these challenges by introducing a gas-liquid resonator into a thermoacoustic combined heat and power systems to recover low-grade thermal energy in residential buildings. Through Sage modeling and calculations, the internal characteristics of the proposed system and its output performance under different operating conditions are explored. At a heating temperature of 350 °C, the system can generate 6.4 kW of output thermal power, 0.9 kW of electricity, and overall exergy efficiency is 79.3 %. Combining neural network models with case studies conducted in Spain and Finland, the system can annually save 5.6 MWh and 20.7 MWh in fuel energy, reduce emissions of 1374 kg and 5180 kg of carbon dioxide, and save a total cost of €611 and €2324, respectively. Furthermore, comparisons with other emerging micro-CHP systems highlight the efficiency of the proposed system. These results indicate the high potential of thermoacoustic combined heat and power systems in recovering low-grade thermal energy and achieving energy savings and emission reductions. • Introducing an innovative thermoacoustic micro-CHP system. • Achieving an exergy efficiency of 79.3 % under standard operating conditions. • One system can annually reduce household CO 2 emissions by 5180 kg. • Ideal for households, balancing lower output levels for both heat and electricity. [ABSTRACT FROM AUTHOR]

Marine renewable energies can play a key role by reducing the dependency on fossil fuels and, therefore, mitigating climate change. Among them, it is expected that wave energy will experience rapid growth in the upcoming decades. Thus, it is important to know how wave climate will change and how suitable the wave energy converters (WECs) will be to the new wave conditions. This paper aims to evaluate the capability of four different WECs—a WaveRoller type device (WRTD), Atargis, AquaBuoy and RM5—to extract wave energy on the Northwest coast of Spain (NWCS). The analysis was performed using the high-resolution wave data obtained from the Simulating Waves Nearshore (SWAN) model over the near future winters (2026–2045). The energy output (P E), the power load factor (ε), the normalized capture width (NC w) and the operational time (OT) were analyzed. According to these parameters, among the devices that work for intermediate-deep waters, Atargis would be the best option (P E = 1400 ± 56 kW, ε = 55.4 ± 2.2%, NC w = 35.5 ± 4.1% and OT = 84.5 ± 3.3%). The WRTD would also be a good option for shallow nearshore areas with P E = 427 ± 248 kW, ε = 12.8 ± 7.4%, NC w = 48.9 ± 9.6% and OT = 88.7 ± 18.9%. A combination of Atargis and WRTDs is proposed to make up the future wave energy farms on the NWCS. • Dynamical downscaling using SWAN to simulate near-shore wave conditions. • Wave energy converters suitability is analyzed in the context of climate change. • Atargis is the most suitable device to future sea conditions in intermediate waters. • WaveRoller type devices can constitute future wave farms for shallow waters. [ABSTRACT FROM AUTHOR]

This paper focuses on the economics of a cross-border transmission interconnector. The domestic spot electricity price is modelled as a stochastic process with mean reversion and jumps; it also includes a deterministic part that accounts for hourly and daily sasonalities along with non-working days. The two domestic spot prices are assumed to be correlated. As an illustration of the approach, we consider the particular case of the interconnector between Spain (an 'electric island') and France. Domestic prices are first calibrated and then used for simulating the stochastic behavior of the price gap between the two countries. In addition, the actual import/export behavior as a function of the price gap is captured by a Tobit model fitted from observed data. This model is then combined with the simulated price gaps to compute a multiple series of hourly prices and exports/imports of electricity through the interconnector. Drawing on these simulations we derive the probability distributions of revenues and expenses from exports and imports, and also some risk measures. According to our results, the economics of this interconector depends on different domestic seasonalities (hourly and daily), the growing trend of the price gap and some stochastic idiosyncrasies. They call for an expanded link. • This paper focuses on the economics of a cross-border electricity interconnector. • Domestic price is a stochastic process with seasonality, mean reversion and jumps. • A Tobit model is estimated to capture trade patterns as functions of the price gap. • Trade patterns and simulated price gaps yield probability distributions of revenue. • Results strongly support expanding the link France ― Spain (an 'electric island'). [ABSTRACT FROM AUTHOR]

In this paper, we decompose a family of energy poverty indices into incidence, intensity and inequality among the poor. When continuous variables such as income are used, it is well known that any income poverty index should take into account these three poverty terms. Therefore, every energy poverty measure should also take into account these three. We propose to follow an analogous idea to decompose a family of energy poverty indices in these three components. The novelty of this proposal is that the multidimensional family of energy poverty measures is applied to multiple dichotomous variables and not to a single continuous variable, when, to date, no decomposition has been proposed based on these types of variables. We then extend this decomposition to a further decomposition by population subgroups. In this way, we will be able to know more precisely the origins of energy poverty in order to implement more specific anti-poverty policies targeting the incidence, intensity or/and inequality among the energy poor. Finally, we apply the proposed decomposition to Spain in 2020 as regards certain individual and household characteristics, so as to identify the individuals most likely to suffer from energy poverty in the first year of the Covid-19 pandemic. • An decomposable index to measure energy poverty. • Poverty Decomposition in Incidence, Intensity and Inequality. • Sources of energy poverty increase in Spain on 2020. [ABSTRACT FROM AUTHOR]

With the economic growth of recent centuries, energy has become a structural good of prime necessity (Sovacool, 2011). The prevailing productive and economic model has made energy vulnerability, inequality and poverty a palpable reality in Spain. One of the instruments used to address this situation by the Government has been the implementation of the Bono Social de Electricidad (BSE) in 2009 based on a discount on the electricity tariff borne by families, a priori , with fewer resources. In 2017, the eligibility criteria were revised in such a way that the concept of vulnerable household was redefined. In this paper, through quasi-experimental methods and using the 2008–2011 and 2016–2019 longitudinal sample of the Living Conditions Survey, the effectiveness of this subsidy in reducing fuel poverty is evaluated. The results show that the BSE has not helped to mitigate it, identifying "new typologies of households" energetically poor. • Energy has become a structural good of prime necessity. • There is an increase in the energy vulnerability of households in Spain. • We identify poor households with novel subjective and objective indicators. • We found that BSE has not helped to mitigate fuel poverty. • Fuel poverty is a specific phenomenon that is included within the general poverty. [ABSTRACT FROM AUTHOR]

Photovoltaics (PV) has reached high level of maturity in terms of material efficiency and low production costs. For this reason, nowadays, lot of emphasis is put on the reduction of the operation and maintenance costs. Soiling is one of the issues that most affect these costs. So, the understanding of its electrical and economic implications is essential to optimize the cleaning routines and minimize the associated costs. This paper investigates the possibility of estimating soiling directly from PV performance data, without the need of installing specific soiling monitoring equipment, which typically needs careful and regular maintenance. Five analytical methods are evaluated and applied to the data of PV modules of different technologies (m-Si, CdTe and CIS). An experimental campaign is conducted in a location in Southern Spain with low-moderate levels of soiling. The methods show promising accuracies when used to obtain the soiling losses of a module, especially during soiling-intense and long dry periods. • Soiling losses were directly extracted from the performance data of PV modules. • The goodness of five different analytical methods was assessed. • These methods allow soiling to be quantified without need for additional sensors. • Each methodology was applied to PV modules of three different technologies. • The accuracies of the methods were higher in periods with greater soiling losses. [ABSTRACT FROM AUTHOR]

Photovoltaics (PV) has reached high level of maturity in terms of material efficiency and low production costs. For this reason, nowadays, lot of emphasis is put on the reduction of the operation and maintenance costs. Soiling is one of the issues that most affect these costs. So, the understanding of its electrical and economic implications is essential to optimize the cleaning routines and minimize the associated costs. This paper investigates the possibility of estimating soiling directly from PV performance data, without the need of installing specific soiling monitoring equipment, which typically needs careful and regular maintenance. Five analytical methods are evaluated and applied to the data of PV modules of different technologies (m-Si, CdTe and CIS). An experimental campaign is conducted in a location in Southern Spain with low-moderate levels of soiling. The methods show promising accuracies when used to obtain the soiling losses of a module, especially during soiling-intense and long dry periods. • Soiling losses were directly extracted from the performance data of PV modules. • The goodness of five different analytical methods was assessed. • These methods allow soiling to be quantified without need for additional sensors. • Each methodology was applied to PV modules of three different technologies. • The accuracies of the methods were higher in periods with greater soiling losses. [ABSTRACT FROM AUTHOR]