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Energy management systems allow the Smart Grids industry to track, improve, and regulate energy use. Particularly, demand-side management is regarded as a crucial component of the entire Smart Grids system. Therefore, by aligning utility offers with customer demand, anticipating future energy demands is essential for regulating consumption. An updated examination of several forecasting techniques for projecting energy short-term load forecasts is provided in this article. Each class of algorithms, including statistical techniques, Machine Learning, Deep Learning, and hybrid combinations, are comparatively evaluated and critically analyzed, based on three real consumption datasets from Spain, Germany, and the United States of America. To increase the size of tiny training datasets, this paper also proposes a data augmentation technique based on Generative Adversarial Networks. The results show that the Deep Learning-hybrid model is more accurate than traditional statistical methods and basic Machine Learning procedures. In the same direction, it is demonstrated that more comprehensive datasets assisted by complementary data, such as energy generation and weather, may significantly boost the accuracy of the models. Additionally, it is also demonstrated that Generative Adversarial Networks-based data augmentation may greatly improve algorithm accuracy. [ABSTRACT FROM AUTHOR]

One of the main identified causes of energy poverty (EP) is the low energy efficiency of housing. In this line, since 2018, public administrations and NGOs collaborating with the Naturgy Foundation's Energy Renovation Solidarity Fund have implemented several shallow renovation interventions in 3660 Spanish vulnerable households. However, the effects of these measures on domestic energy affordability were not evaluated before because of a lack of a proper method. This paper presents a methodology to objectively assess the impact of these interventions on EP. In particular, this work proposes calculating a hidden EP indicator using data from a primary survey and applies it to a local case study (54 vulnerable households in Catalonia—10% of dwellings renovated by the Fund in the region) by processing their characteristics and energy bills before and after the implementation of the interventions. Considering the whole sample of households analysed, the hidden EP indicator drops by 10% in absolute terms (11.2% in relative terms) after the retrofit, and the average EP gap goes from 423 €/year to 313 €/year, thus marking a significant positive effect of the analysed interventions on the EP situation of this population. Eventually, extrapolating the results to the vulnerable population in Spain, this paper points out a series of recommendations that could be useful for decision-makers and organisations when designing and implementing shallow renovation interventions. [ABSTRACT FROM AUTHOR]

Combined Heat and Power (CHP) has been identified by the EU as a powerful resource capable of making substantial contributions to energy savings and reducing GHG emissions. Spain's effort to promote CHP has been prolific since the 1980s. In this regard, there have been various Laws, Royal Decrees (RDs) and European Union (EU) Directives addressed to reach the national objectives set for the CHP sector. Despite these attempts, the evolution and growth of installed CHP capacity has been irregular, compared to other technologies. Likewise, the academic treatment of the Spanish CHP evolution has not deserved the same attention as other technologies such as wind, photovoltaic and thermal solar systems. As a result, this article is aimed at providing a comprehensive overview of the regulatory frameworks applied to the Spanish CHP sector and analysing the reasons behind the variable evolution of the installed CHP capacity. The study covers the legislative context from 1980 to 2020, describing the evolution during both the pre-liberalization and liberalization periods, highlighting the modifications in economic policies that affected self-producers and the so-called Special Regime (SR) for CHP, and examining the challenges faced during the cost containment measures that followed. The manuscript finds and explains the connection between the regulatory framework and the evolution of installed CHP capacity in Spain. Likewise, the connection between the industrial situation and the promotion of CHP, as well as the influence of the Spanish Electricity Sector (SES)'s liberalization on the CHP sector are also pointed out. The paper intends to provide valuable insights for CHP experts and policymakers by showcasing the importance of aligning regulatory measures with the objectives of energy efficiency. It also serves as a reference for countries in various stages of promoting CHP, and provides evidence for the importance of stable energy-policy control mechanisms. [ABSTRACT FROM AUTHOR]

Accurate electricity price forecasting (EPF) can provide a necessary basis for market decision making by power market participants to reduce the operating cost of the power system and ensure the system's stable operation. To address the characteristics of high frequency, strong nonlinearity, and high volatility of electricity prices, this paper proposes a short-term electricity price forecasting model based on a two-layer variational modal decomposition (VMD) technique, using the sparrow search algorithm (SSA) to optimize the long and short-term memory network (LSTM). The original electricity price sequence is decomposed into multiple modal components using VMD. Then, each piece is predicted separately using an SSA-optimized LSTM. For the element with the worst prediction accuracy, IMF-worst is decomposed for a second time using VMD to explore the price characteristics further. Finally, the prediction results of each modal component are reconstructed to obtain the final prediction results. To verify the validity and accuracy of the proposed model, this paper uses data from three electricity markets, Australia, Spain, and France, for validation analysis. The experimental results show that the proposed model has MAPE of 0.39%, 1.58%, and 0.95%, RMSE of 0.25, 0.9, and 0.3, and MAE of 0.19, 0.68, and 0.31 in three different cases, indicating that the proposed model can well handle the nonlinear and non-stationarity characteristics of the electricity price series and has superior forecasting performance. [ABSTRACT FROM AUTHOR]

This paper presents an economic assessment of three drying systems (DS) with different configurations: diesel-powered (DDS), grid-powered (GDS), and photovoltaic-powered (PVDS). The third configuration, PVDS, presents important technological innovations regarding the electric configuration (stand-alone PV, without batteries or grid support) and the heat pump technology used (optimized for drying the recirculated air, which permits a reduction in the electricity consumption by more than 45% if compared to a diesel air-heater or an electric resistance). The profitability of the investment required for the installation of the three systems is proven by calculating the profitability index (PI), the internal rate of return (IRR), the payback period (PBP), and the levelized cost of energy (LCOE). All the indicators show good profitabilities for the three technologies (the PI values range from 6.78 to 10.11, the IRR values range from 24% to 37%, and the PBPs are between 3 and 4 years), but the PVDS clearly offers important economic advantages: its PI and IRR are more than 40% higher, the PBP is 25% shorter, and the LCOE is between 40 and 47% lower than for the two other systems. The results of this analysis correspond to a particular base case but are obviously sensitive to geopolitical and economic changes: the ultimate strength of the PVDS configuration is its resilience against a possible rise in electricity and diesel prices, reducing the uncertainty for investors and policymakers. [ABSTRACT FROM AUTHOR]

Soiling of PV modules is an issue causing non-negligible losses on PV power plants, between 3 and 4% of the total energy production. Cleaning is the most common way to mitigate soiling. The impact of the cleaning activity can be significant, both in terms of cost and resources consumption. For these reasons, it is important to monitor and predict soiling profiles and establish an optimal cleaning schedule. Especially in locations where raining is irregular or where desert winds carry a high concentration of particles, it is also important to know how precipitation and dust events affect the soiling ratio. This paper presents a new model based on environmental conditions that helps the decision-making process of the cleaning schedule. The model was validated by the analysis of five large grid-connected PV plants in Spain over two years of operation, with a total power of 200 MW. The comparison between the model and soiling sensors at the five locations was included. Excellent results were achieved, the mean difference between sensors and model being 0.71%. [ABSTRACT FROM AUTHOR]

In recent years, important regulatory changes have been introduced in Spain in the fields of self-consumption and energy tariffs. In addition, electricity prices have risen sharply, reaching record highs in the last year. This evidences the need to conduct new research studies in order to provide an accurate picture of the profitability of battery energy storage systems and photovoltaic systems. This paper proposes a complex simulation tool developed to assist in the optimal design of these kinds of facilities. The tool is used in this study to analyze the benefits of including batteries in PV systems under different self-consumption models, different consumer profiles and different locations across the country. The research results indicate that at current electricity prices, the use of batteries is less profitable than selling excess energy to the grid, unless the price of batteries drops drastically by more than 50% in all the cases analyzed. However, at current battery prices, they become a valuable resource in facilities that do not feed energy surplus into the grid. [ABSTRACT FROM AUTHOR]

This paper shows a practice to raise the reliability of an electric power system by the installation of distributed generation, taking gasified biomass as fuel. To calculate the reliability index, a probabilistic load flow was used. This index is determined as the fault probability of the system. The resolution of this probabilistic load flow combines the method of cumulants and Gram–Charlier expansion. To achieve the reliability index, simulating a number of contingencies is required; the greater the number of simulated contingencies, the higher the accuracy of the index obtained. This probabilistic technique uses the random variables as starting information, so the two generators and loads are simulated as random variables. The generators of this distributed generation are biomass-fueled gas engines, commonly found in Spain. The simulations carried out on the IEEE 14-bus Test System, including three biomass generators, show that the inclusion of this type of generation improves the overall reliability indices of the electrical system. [ABSTRACT FROM AUTHOR]

In hospitals, operating rooms are energy-intensive spaces, due to the high flow of outside air required to achieve the necessary indoor air quality. Operating rooms demand ventilation continuously, despite periods of low daily surgical activity. However, by controlling ventilation during inactive periods in the operating room, significant energy savings can be achieved, avoiding penalties on IAQ levels. This paper evaluates the energy savings achieved by introducing ventilation flow control and regulation systems in operating rooms of hospitals located in different climatic zones within Spain. In addition, emissions and economic savings have also been evaluated. Two control and regulation strategies of the air flow to be supplied and extracted in the operating rooms, during periods of inactivity, are studied and include regulation by schedule and regulation by occupancy. Data from a 900-bed university hospital center are used as a reference to evaluate the average occupancy of the operating rooms, and the energy consumption, thus validating the model for calculating the demand of a typical operating room. The energy savings for the regulation by occupancy are 37.5%, and the regulation by schedule are 40% of the annual demand, with respect to an operating room working permanently. [ABSTRACT FROM AUTHOR]

The ongoing spread of electric sustainable mobility is transforming the local ways of transport in metropolitan areas. This is meant to be extended outside of big cities in the near future thanks to new technological developments. Little towns should adapt to these changes, as they are located geographically far from the big cities and are generally characterized by low economic and demographic indicators. Hence, little towns must keep pace with these changes in mobility to avoid being isolated from the main cities in a country. People living in the countryside usually move toward big cities for various reasons, either related to work or living necessities. Therefore, it must be possible to conduct usual displacements through the use of electric vehicles (EVs), i.e., reaching the destinations and supplying the batteries through charging infrastructures. This paper studies the full implementation of electric mobility applied in the case of Cuenca, a city located in middle Spain. A brief geographical context is provided, together with the routes and destinations of interest considered. Then, different EVs are considered and an analytical vehicle model is provided. The model was exploited to simulate the electrical energy demand to reach the destinations chosen; the results allow comparing the performances offered by different types of EVs. This aspect is then considered as the basis to propose further upgrades in the charging infrastructures where needed, to comply with the widespread use of electric mobility. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to analyze the effect of industrial agglomeration on the degree of interorganizational cooperation and the innovative performance of firms of the electricity supply sector in Spain. For this purpose, the agglomeration coefficient in each of the 50 provinces of Spain is calculated, based on secondary data from SABI database. Subsequently, primary data are obtained from a sample of 197 companies through a structured questionnaire. In this case, the PLS-SEM technique is used. The results show that there is a positive and significant relationship between the variables analyzed. It is concluded that industrial agglomeration and cooperation are relevant external factors that boost the innovative performance of firms and that business associations foster interorganizational cooperation. [ABSTRACT FROM AUTHOR]

Climate change motivated by human activities constitutes one of the main challenges of this century. To cut carbon emissions in order to mitigate carbon's dangerous effects, the current energy generation mix should be shifted to renewable sources. The main drawback of these technologies is their intermittency, which will require energy storage systems to be fully integrated into the generation mix, allowing them to be more controllable. In recent years, great progress to develop an effective and economically feasible energy storage systems, particularly motivated by the recent rise of demand for electric transportation, has been made. Lithium-ion (Li-ion) battery prices have fallen near 90% over the past decade, making possible the affordability of electric vehicles and transforming the economics of renewable energy. In this work, a study on storage capacity demand previously presented as conference paper is expanded, including a deep analysis of the Spanish generation mix, the evaluation of the energy storage requirements for different low-carbon and carbon-free scenarios in Mainland Spain, and the calculation of the CO2 emissions' reduction and the associated storage costs. [ABSTRACT FROM AUTHOR]

Aiming at the problem that power load data are stochastic and that it is difficult to obtain accurate forecasting results by a single algorithm, in this paper, a combined forecasting method for short-term power load was proposed based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-sample entropy (SE), the BP neural network (BPNN), and the Transformer model. Firstly, the power load data were decomposed into several power load subsequences with obvious complexity differences by using the CEEMDAN-SE. Then, BPNN and Transformer model were used to forecast the subsequences with low complexity and the subsequences with high complexity, respectively. Finally, the forecasting results of each subsequence were superimposed to obtain the final forecasting result. The simulation was taken from our proposed model and six forecasting models by using the load dataset from a certain area of Spain. The results showed that the MAPE of our proposed CEEMDAN-SE-BPNN-Transformer model was 1.1317%, while the RMSE was 304.40, which was better than the selected six forecasting models. [ABSTRACT FROM AUTHOR]

Concentrating solar power (CSP), also known as solar thermal electricity (STE), is increasing its deployment worldwide. One of the potential ways to decrease costs in CSP plants is the improvement of corrosion resistance between the heat transfer fluid (HTF) and storage materials, and the materials used for pipes, tanks, containers, and receivers. This paper assesses the literature on this topic (290 publications) through a bibliometric analysis, identifying the trends of the research, the topics of most interest to researchers, and literature gaps. Most documents are from Spain, Germany, and the United States of America. Results show that the most recent approaches for corrosion migration are selective coatings and the use of nanoparticles to reduce corrosiveness. The use of nitrates is changing to other salts such as chloride mixtures and potassium compounds. In addition, the techniques used to evaluate corrosion results are dominated by scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical testing, but new dynamic techniques are starting to be used, representing the biggest gap that needs to be filled for the testing of components such as solar receivers. [ABSTRACT FROM AUTHOR]

The emergence of energy communities represents a promising option to democratize the energy system by empowering consumers to take a more active role. This can aid in achieving energy and environmental goals as well as encouraging more equitable distribution of costs and revenues between all parties on the energy system. Despite this potential, energy communities are still a nascent solution, the success of which is heavily influenced by regulations. As a result, there are a wide variety of organizational structures for energy communities at this time. This paper provides a review of the policy landscape in Spain as it relates to energy communities. This work also presents a formalized method for characterizing different energy community structures and provides a qualitative assessment of the impacts of different measures to encourage energy communities with respect to their organizational structure. Findings suggest that many market-focused measures, including wholesale, local flexibility, capacity, and multisector market measures favor larger, more integrated communities, while regulatory, legal, and organizational measures, including peer-to-peer trading, aggregation, and self-consumption favor smaller, more distributed communities. Additionally, when developing policies to encourage the growth of energy communities, policymakers should be cognizant of the progression of policies in the context of the desired outcomes for energy community growth specific to the region or country and its goals. [ABSTRACT FROM AUTHOR]

This paper on Political Economic and Labour Economic Policies in the European Green Deal framework analyses the Recovery Plan and Resilience Facility. It pays attention to the effects on the design of new green jobs and the necessary skills to develop this type of new positions generated, with higher labour wellbeing. The paper is focused on the analysis of the green jobs' opportunity for Europe, at a country level, with a specific analysis made for the Spanish case. A systematisation of the concepts and calculations on the issue is made and analysed (attending the international institutions and forums proposals) to harmonise the recovery plans, apply them beyond the energy sector to other related green activities and align the public and private sector, and other critical stakeholders, in achieving this goal. The following research questions were formulated: (1) what is the estimated number of new green jobs that would be created as a consequence of the implementation of the Recovery Plan in Spain; (2) which new soft skills or re-skilling would be necessary to develop such new green jobs; (3) how much are the new jobs aligned with Wellbeing Economics? The research was conducted by applying a few research methods, i.e., secondary sources, the desk research method and the exploration method, critical and comparative analysis, inductive and deductive reasoning and some mathematical calculations. The research contribution can provide a valuable source of information to coordinate sectoral plans by the policymakers, particularly those responsible for the economy, business, green activities and education. [ABSTRACT FROM AUTHOR]

Wind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France. [ABSTRACT FROM AUTHOR]

This paper aims at presenting and describing a dimensioning methodology for energy storage systems (ESS), in particular for one based on flywheels, applied for the specific application of reducing power oscillation in a wave energy conversion (WEC) plant. The dimensioning methodology takes into account the efficiency maps of the storage technology as well as the effect of the filtering control techniques. The methodology is applied to the case study of a WEC plant in operation in Spain, using real power generation profiles delivered into the electric grid. The paper firstly describes the calculation procedure of the efficiency maps for the particular technology of flywheels, although it could be extended to other storage technologies. Then, the influence of using future data values in the dimensioning process and the control of the ESS operation is analysed in depth. A moving average filter (MAF) is defined to compensate for power oscillations, studying the difference between considering prediction and not doing so. It is concluded that a filtering control using future values based on a number of samples equivalent to a 4-min time order provides an important reduction in the energy storage requirements for a power generation plant. Finally, and based on the selection of storage modules previously defined, the efficiency maps, and the MAF used for delivering the power into the grid, an optimal operation strategy is suggested for the storage modules, based on a stepped switching technique. The selection of four flywheel energy storage system (FESS) modules achieves a reduction of 50% in power oscillations, covering 85% of the frequency excursions at the grid. [ABSTRACT FROM AUTHOR]

In this paper, the energy benefits of switchable insulation systems (SIS) are assessed when applied as shades for windows as well as dynamic insulation for exterior walls of residential buildings located in European countries including Belgium and Spain. A series of analyses is performed for detached houses and apartments representing common Belgian residential buildings to determine the energy performance of SIS when deployed to windows and exterior walls and operated using simplified rule-based controls. The analysis results indicate that SIS-integrated windows can achieve significant energy savings for both dwelling types in Belgium, including the elimination of any mechanical cooling and a reduction of up to 44% of heating energy end-use. Moreover, the results show that SIS can offer even more energy efficiency and thermal comfort benefits when deployed to both windows and exterior walls for residential buildings. These energy efficiency benefits are higher, especially for reducing heating needs, for the milder climates of Belgium and Spain. However, it should be noted that the energy performance of SIS could be affected substantially by windows' orientation and occupants' behavior. [ABSTRACT FROM AUTHOR]

In this paper, the use of HVAC systems and non-HVAC control measures to reduce virus-laden bioaerosol exposure in a highly occupied indoor space is investigated. A simulation tool was used to model the fate and transport of bioaerosols in an indoor space in the hotel industry (bar or pub) with three types of HVAC system (central air handling system (CAHS), dedicated outdoor air system (DOAS), and wall unit system (WUS)). Non-HVAC control measures such as portable air cleaners (PAC) and local exhaust fans were considered. Occupant exposure was evaluated for 1 μm bioaerosols, which transport SARS-CoV-2, for 3 h/day of continuous source and exposure. The combined effects of ventilation (400 l/s of outdoor air), recirculated air filtration (90% efficacy), and a PAC with a capacity up to 900 m3/h mitigated the (normalized) integrated exposure of the occupant by 0.66 to 0.51 (CAHS) and 0.43 to 0.36 (DOAS). In the case of WUS, the normalized integrated exposure was reduced by up to 0.2 when the PAC with a capacity of up to 900 m3/h was used. The corresponding electricity consumed increased by 297.4 kWh/year (CAHS) and 482.7 kWh/year (DOAS), while for the WUS it increased by 197.1 kWh/year. [ABSTRACT FROM AUTHOR]

The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community. [ABSTRACT FROM AUTHOR]

The goal of the research is to assess the minimum requirement of fast charging infrastructure to allow country-wide interurban electric vehicle (EV) mobility. Charging times comparable to fueling times in conventional internal combustion vehicles are nowadays feasible, given the current availability of fast charging technologies. The main contribution of this paper is the analysis of the planning method and the investment requirements for the necessary infrastructure, including the definition of the Maximum Distance between Fast Charge (MDFC) and the Basic Highway Charging Infrastructure (BHCI) concepts. According to the calculations, distance between stations will be region-dependent, influenced primarily by weather conditions. The study considers that the initial investment should be sufficient to promote the EV adoption, proposing an initial state-financed public infrastructure and, once the adoption rate for EVs increases, additional infrastructure will be likely developed through private investment. The Spanish network of state highways is used as a case study to demonstrate the methodology and calculate the investment required. Further, the results are discussed and quantitatively compared to other incentives and policies supporting EV technology adoption in the light-vehicle sector. [ABSTRACT FROM AUTHOR]

Developing a regional power system to achieve a high level of integration of national systems requires sufficient development of the regional transmission grid. This is possible only with appropriate schemes for the complete cost–benefit analyses, and cost allocation of these transmission investments, which plays a critical role in the selection of the most efficient network investment and the proper assignment of their cost to the national systems. Network reinforcements affect the operation of power systems and, therefore, the externalities of power generation. This paper examines the impacts of integrating local air pollution damage from power production within the benefit assessment and cost allocation of transmission investments. The paper describes the methodology followed and illustrates its application in a real-life case study where a simplified version of a European network is considered. Within this case study, we have assessed the impact of considering the reduction in air pollution damage achieved through a particular HVDC project between France and Spain on the benefits, and benefit-driven cost allocation, computed for this project. In this case study, local pollution related benefits are a relevant fraction of the overall benefits of the considered transmission project. However, considering the local air pollution benefits of the project does not affect the net positive benefits of each country significantly, resulting in a limited change in the cost allocation of the project. [ABSTRACT FROM AUTHOR]

The development of Short-Term Forecasting Techniques has a great importance for power system scheduling and managing. Therefore, many recent research papers have dealt with the proposal of new forecasting models searching for higher efficiency and accuracy. Several kinds of artificial intelligence (AI) techniques have provided good performance at predicting and their efficiency mainly depends on the characteristics of the time series data under study. Load forecasting has been widely studied in recent decades and models providing mean absolute percentage errors (MAPEs) below 5% have been proposed. On the other hand, short-term generation forecasting models for photovoltaic plants have been more recently developed and the MAPEs are in general still far from those achieved from load forecasting models. The aim of this paper is to propose a methodology that could help power systems or aggregators to make up for the lack of accuracy of the current forecasting methods when predicting renewable energy generation. The proposed methodology is carried out in three consecutive steps: (1) short-term forecasting of energy consumption and renewable generation; (2) classification of daily pattern for the renewable generation data using Dynamic Time Warping; (3) application of Demand Response strategies using Physically Based Load Models. Real data from a small town in Spain were used to illustrate the performance and efficiency of the proposed procedure. [ABSTRACT FROM AUTHOR]

Non-cooperative scheduling games can be used to coordinate residential loads in order to achieve a common goal while accounting for individual consumer's interests, privacy, and autonomy. However, a significant portion of the residential flexibility—Thermostatically Controlled Loads (TCLs) such as water and space heating/cooling appliances—has not been fully addressed under this game theoretic approach: their comfort constraints and integer control were not considered. This paper presents a method for properly including TCLs in this framework and discusses its application in energy communities. Specifically, we propose a general mathematical formulation for considering users' comfort in non-cooperative games. We model the integer nature of the TCLs control with binary variables and show that optimal or close to optimal (less than 1%) solutions are reached. Moreover, different total cost functions can be used depending on the market context and the objective of the demand management program. To illustrate and discuss these aspects in practical applications, we used a case study of an energy community in Spain. The results show that the TC solutions are optimal or only 0.80% worse than optimal; different total cost functions result in different results (load curve smoothing or peak load reduction); consumers' comfort is respected; and the proposed game model cooperates with consumers in order to minimize community's costs. [ABSTRACT FROM AUTHOR]

This paper lays out the role of the first centre in the world for the integration into the electrical grid of electricity coming from renewable energy (the Spanish acronym for which is CECRE (Centro de Control de Energías Renovables; Control Centre for Renewable Energies)) and the industrial development of large energy suppliers and wind turbine manufacturers in Spain. These two initiatives enabled the development of one of the first integrated markets for this type of energy source. The key contributions were the development of two software programs (wind management and management of solar light incidence), their visual implementation, and centralized digital control. An economic and business history approach is used to show the rise and relative failure of the Spanish wind industry during the period 2004–2015, when Spain became the fourth country after China, the US, and Germany in terms of installed capacity of renewable energy and, in relative terms, the second country after Denmark. This study is unique in that it provides an integrated vision of the reasons for the relative fall of Spain in the world ranking of wind energy producers. The methodology of the economic analysis of industrial policies makes it possible to explain the fall in the relative importance of Spain in the international panorama of wind farms. [ABSTRACT FROM AUTHOR]

This study provides an in-depth assessment of the environmental performance of five public schools in the transition towards a low-carbon economy and a more sustainable model of society. Life cycle assessment (LCA) methodology is used to conduct the study. The school system includes several activities and processes clustered in three subsystems: management of the school building, training and learning activities (T&L) and mobility and transport (M&T). A detailed primary data inventory of energy and resources consumption was collected in five schools located in Spain and Portugal. Findings on climate change (CC), water depletion (WD), particular matter (PM), acidification (Ac), and human health (HH), as well as associated external cost (EC), are reported per student in one school year as reference unit, allowing the schools' individual performance comparison and identify the potential improvements. Considering the sample of schools, findings reveal that peculiarities of the schools, such as location, specialization, and level of education, are crucial for the environmental performance. Buildings are a relevant contributor to CC as well as heating and electricity needs, although their relevance is dependent on multiple factors. The M&T subsystem also has relevant weight on the metrics evaluated. Educational activities have a lower impact in absolute terms but, in some schools, it becomes the main contributor to HH due to paper and electricity consumption and manufacturing of equipment. External costs results are in the range of 11 to 38 EUR/student·year mainly caused by heating, electricity and wastes from the building subsystem, and the M&T subsystem. [ABSTRACT FROM AUTHOR]

Islands are widely recognised as ideal pilot sites that can spearhead the transition to clean energy and development towards a sustainable and healthy society. One of the assumptions underpinning this notion is that island communities are more ready to engage with smart grids (SGs) than people on the mainland. This is believed to be due to the high costs of energy on islands and the idea that the sense of community and collective action is stronger on islands than on the mainland. This paper presents findings from a survey conducted to assess people's perception of, and readiness to engage with, SG and demand response (DR) in the communities of three islands taking part in a H2020 project called REACT. The main objective of the survey, conducted in 2020, was to inform the recruitment of participants in the project, which is piloting different technologies required for SGs and DR with communities on the three islands. The results show that many island residents are motivated to take part in SG, to engage with energy saving, and are willing to change some energy-related behaviours in their homes. However, the results also indicate that levels of ownership of, and knowledge and familiarity with, the SG and DR related technologies are extremely low, suggesting that the expected uptake of DR in islands might not be as high as anticipated. This brings into question the readiness of island dwellers for the SG, their role in the deployment of such schemes more widely and the validity of the assumptions often made about island communities. This has significant implications for the design of SGs and DR solutions for islands, including devoting sufficient efforts to build knowledge and awareness of the SG, investing in demonstration projects for that purpose and tailoring interventions based on island communities' motivations. [ABSTRACT FROM AUTHOR]

Understanding of energy consumption patterns is extremely important for optimization of resources and application of green trends. Traditionally, analyses were performed for large environments like regions and nations. However, with the advent of Smart Grids, the study of the behavior of smaller environments has become a necessity to allow a deeper micromanagement of the energy grid. This paper presents a data processing system to analyze energy consumption patterns in industrial parks, based on the cascade application of a Self-Organizing Map (SOM) and the clustering k-means algorithm. The system is validated with real load data from an industrial park in Spain. The validation results show that the system adequately finds different behavior patterns which are meaningful, and is capable of doing so without supervision, and without any prior knowledge about the data. [ABSTRACT FROM AUTHOR]

Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS), the chance-constrained programming-based strategy (CPS) and the multi-objective bidding strategy (ECPS). Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets. [ABSTRACT FROM AUTHOR]

As a new technology, electric mobility has the potential to achieve a reduction in CO2 emissions and contribute to the transition from the current transportation system to a better one, environmentally speaking. The objective of the paper is to aid the necessary decision-making for the adoption and development of electric vehicles in Spain, taking the time horizon of 2020. This will be achieved by building a System Dynamics model for various scenarios that will be used for the analysis and comparison of various dynamic variables, as well as to determine how, and to what extent, they will influence the number of electric vehicles that will run on Spanish roads in the coming years, focusing on the cost variable. [ABSTRACT FROM AUTHOR]

This paper analyzes the impact of the fall in household consumption after an economic crisis in Spain on greenhouse gas emissions. To this end, household consumption is differentiated by the age of the main provider by using a conversion matrix that relates consumption groups to activity sectors. A multisectoral model was used to quantify and compare the environmental impact caused by the consumption of each age group, indicating that the older the age of the main household provider, the smaller the reduction in GHG emissions associated with their consumption. The results facilitate an analysis of how the greenhouse gas emissions of the different sectors of the Spanish economy, associated with the population under study, varied before and after the 2008 crisis, and confirm that the sectors with the greatest reduction in emissions were, in this order, extractive industries, construction, manufacturing industry, wholesale and retail trade and transport and storage. This is relevant for decision making in the field of environmental policies in crises, akin to the one the world is currently experiencing. [ABSTRACT FROM AUTHOR]

Thermostatic load control systems are widespread in many countries. Since they provide heat for domestic hot water and space heating on a massive scale in the residential sector, the assessment of their energy performance and the effect of different control strategies requires simplified modeling techniques demanding a small number of inputs and low computational resources. Data-driven techniques are envisaged as one of the best options to meet these constraints. This paper presents a novel methodology consisting of the combination of an optimization algorithm, two auto-regressive models and a control loop algorithm able to virtually replicate the control of thermostatically driven systems. This combined strategy includes all the thermostatically controlled modes governed by the set point temperature and enables automatic assessment of the energy consumption impact of multiple scenarios. The required inputs are limited to available historical readings from smart thermostats and external climate data sources. The methodology has been trained and validated with data sets coming from a selection of 11 smart thermostats, connected to gas boilers, placed in several households located in north-eastern Spain. Important conclusions of the research are that these techniques can estimate the temperature decay of households when the space heating is off as well as the energy consumption needed to reach the comfort conditions. The results of the research also show that estimated median energy savings of 18.1% and 36.5% can be achieved if the usual set point temperature schedule is lowered by 1 °C and 2 °C, respectively. [ABSTRACT FROM AUTHOR]

This paper provides a theoretical framework to explore how the support policies for renewable energies can promote rent-seeking incentives in private firms. We develop a political economy of rent-seeking that considers the link between the regulatory decisions of political agents and the potential scope of socially wasteful pursuits. We argue that systematic public support schemes bring rent-seeking as a perception shared by entrepreneurs that influencing political allocations of resources is an essential and potentially preferable source of private profit than other for-profit economic avenues. As evidence of our claims, the framework is applied to the case of Spain to illustrate the economic effects of support policies on the production and distribution of renewable energy. We find rent-seeking behavior in Spain's renewable energy industry, and precisely that: (i) political regulations have induced market concentration and rent-seeking in renewable energy firms, (ii) these firms have required increasing regulations and premiums to survive, and (iii) energy consumers are forced to pay rent-seeking through increasingly expensive electricity bills. The analysis reveals some challenges and opportunities to drive efficient market-based policies to strengthen entrepreneurial competition and curb rent-seeking behavior. These insights have relevant proposals for the Spanish energy industry in complying with the EU Green Deal through a sustainable transition and comprehensive growth. [ABSTRACT FROM AUTHOR]

Improving the energy performance of existing buildings is one of the main strategies defined by the European Union to reduce global energy costs. Amongst the actions to be carried out in buildings to achieve this objective is working with passive measures adapted to each type of climate. To assist designers in the process of finding appropriate solutions for each building and location, different tools have been developed and since the implementation of building information modeling (BIM), it has been possible to perform an analysis of a building's life cycle from an energy perspective and other types of analysis such as a comfort analysis. In the case of Spain, the first BIM environment tool has been implemented that deals with the global analysis of a building's behavior and serves as an alternative to previous methods characterized by their lack of both flexibility and information offered to designers. This paper evaluates and compares the official Spanish energy performance evaluation tool (Cypetherm) released in 2018 using a case study involving the installation of sunlight control devices as part of a building refurbishment. It is intended to determine how databases and simplifications affect the designer's decision-making. Additionally, the yielded energy results are complemented by a comfort analysis to explore the impact of these improvements from a users' wellbeing viewpoint. At the end of the process the yielded results still confirm that the simulation remains far from reality and that simulation tools can indeed influence the decision-making process. [ABSTRACT FROM AUTHOR]

The role of the energy industry has always been central for one reason or another, being environmentalism the main motive in the last two decades. Therefore, attention and research have been directed in this sense. However, human resources—or human capital—have remained understudied, especially concerning the salaries received. Thus, this study is disruptive as it explored the factors that influence employee remuneration in the energy subsector, using Spain as a case study. For this, the PLS-SEM (Partial Least Squares Structural Equation Modelling) path modelling methodology was used, executing a traditional PLS analysis, bootstrapping and, finally, IPMA (Importance-Performance Analysis). Solid and significant relationships were found among labour conditions, human capital, market and wages, with the relationships between human capital and wages and between human capital and labour conditions being especially relevant. Besides, through IPMA, a series of considerations was made regarding the individual indicators according to their relative importance and performance. Consequently, this paper significantly contributes to the extant literature by analysing the composition of wages in the energy sector, which might allow taking valuable management decisions. Nevertheless, the main limitation of this study lies in the availability of data for Spain and, specifically, for workers in the energy supplying industries. [ABSTRACT FROM AUTHOR]

The paper will examine, in detail, (a) the norms that can be featured under the category "Green Deal" connected to the European Commission, (b) their application to Spain, and (c) the different patterns of action and development models that have been shaped by this framework over the last 20 years. These patterns are particularly relevant currently, as the COVID-19 crisis has highlighted the importance of advancing towards new patterns of local sustainability endowed with higher resilience. The notion of cognitive sustainability will be one of the added values to the current reflections on sustainability in general, and energetic sustainability in particular. [ABSTRACT FROM AUTHOR]

The installation of wind power technology is growing steadily and the trend can be expected to continue if the objectives proposed by the European Commission are to be achieved. In some countries a considerable percentage of installed wind power capacity is near the end of its useful lifetime. In the case of Spain, the figure is 50% within five years. Over the last 20 years, wind energy technology has evolved considerably and the expected capacity factor has improved, thus increasing annual energy production, and capital expenditure and operational expenditure have decreased substantially. This paper studies the optimal decision under uncertainty between life extension and full repowering for a generic wind farm installed in the Iberian Peninsula when the future hourly electricity prices and the capacity factor evolve stochastically and seasonally. The results show that in economic terms, full repowering is the best option, with a net present value of €702,093 per MW installed, while reblading is the second best option. The methodology can be transferred to other specific wind farms in different electricity markets and can be used to develop national wind energy policy recommendations to achieve projected shares in the electricity mix. [ABSTRACT FROM AUTHOR]

In recent years, solar price drops and regulations have helped residential users to invest in grid-connected photovoltaic (PV) facilities. In Spain, a novel law promotes self-consumption by discounting electricity fed into the grid from the utility bill. However, the performance of PV-based facilities depends on diverse factors. The contribution of this paper is to evaluate the techno-economic performance of such installations for different considerations linked to the Spanish law. A simulation model is used to examine different representative cities, load profiles and alternative objectives: maximising profitability and self-sufficiency. For profit maximisation, results show that load profile variations entail PV size changes up to 5 kWp for the same location, together with huge economic and self-sufficiency differences. In contrast, the solar radiation and compensation rate have a more limited influence. For self-sufficiency maximisation, the economic performance drops close to EUR 0, as benefits are used to double the PV size, buy batteries and reach close to 70% self-sufficiency. Finally, a sensitivity analysis shows a limited impact of the utility tariff and the technology cost on the PV size, but a relevant influence on the benefits. These results can help investors and families to quantify the risks and benefits of domestic self-consumption facilities. [ABSTRACT FROM AUTHOR]

Short-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for their business. The load series of a given system presents highly repetitive daily, weekly and yearly patterns. However, other factors like temperature or social events cause abnormalities in this otherwise periodic behavior. In order to develop an effective load forecasting system, it is necessary to understand and model these abnormalities because, in many cases, the higher forecasting error typical of these special days is linked to the larger part of the losses related to load forecasting. This paper focuses on the effect that several types of special days have on the load curve and how important it is to model these behaviors in detail. The paper analyzes the Spanish national system and it uses linear regression to model the effect that social events like holidays or festive periods have on the load curve. The results presented in this paper show that a large classification of events is needed in order to accurately model all the events that may occur in a 7-year period. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is having a strong impact on the economies of all countries, negatively affecting almost all sectors. This paper compares Spanish electricity and natural gas prices in the first half-year of 2020 with the prices expected for that period at the end of 2019. The half-year of 2020 selected coincides with the period of greatest impact of COVID-19 on Spanish society. Expected prices and their future probability distributions are calculated using a stochastic model with deterministic and stochastic parts; the stochastic part includes mean-reverting and jumps behaviour. The model is calibrated with 2016–2019 daily spot prices for electricity and with day-ahead prices for natural gas. The results show large monthly differences between the prices expected at the end of the year 2019 and the actual prices for the half-year; in May 2020, wholesale electricity prices are found to be EUR 31.60/MWh lower than expected, i.e., 60% lower. In the case of natural gas, the prices in the same month are EUR 8.96/MWh lower than expected, i.e., 62% lower. The spark spread (SS) is positive but lower than expected and also lower than in the same months of the previous year. [ABSTRACT FROM AUTHOR]

A real case study of an energy system based on a Solar Assisted Heat Pump (SAHP) fed by hybrid photovoltaic-thermal solar panels (PVT) and seasonal storage (SS) is presented in this paper. Exergy and exergy cost analyses are proposed as complementary methods for the assessment and better understanding of the efficiency of this cogeneration solar configuration. The system performance takes advantage of storage heat in summer, when the solar resource is high in Spain, and is then later consumed during the cold winter (heating season). The building is devoted to social housing, and it is currently under construction. The assessment is based on simulations developed using TRNSYS, a dynamic simulation software for energy systems. Results show that the unit exergy cost of the solar field is around 6. The cost of the seasonal storage is higher, about 13, and its formation is affected both by its own irreversibility and by the irreversibility of the PVT solar field. The cost of the heat delivered by the heat pump is around 15, being affected by all the upstream units and even by the grid. Besides, the analysis points out strategies for improving the system efficiency, such as increasing the size of the storage tank or improving the control strategy of the boiler. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a methodology for dimensioning an energy storage system (ESS) to the generation data measured in an operating wave energy generation plant connected to the electric grid in the north of Spain. The selection criterion for the ESS is the compliance of the power injected into the grid with a specific active-power ramp-rate limit. Due to its electrical characteristics, supercapacitor (SC) technology is especially suitable for this application. The ESS dimensioning methodology is based on a mathematical model, which takes into account the power generation system, the chosen ramp-rate limit, the ESS efficiency maps and electrical characteristics. It allows one to evaluate the number of storage cabinets required to satisfy the needs described, considering a compromise between the number of units, which means cost, and the reliability of the storage system to ensure the grid codes compliance. Power and energy parameters for the ESS are obtained from the calculations and some tips regarding the most efficient operation of the SC cabinets, based on a stepped switching strategy, are also given. Finally, some conclusions about the technology selection will be updated after the detailed analysis accomplished. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the economic performance of photovoltaic (PV) self-consumption systems at an industrial park in the Basque Country (north of Spain). The economic feasibility of the installations is largely dependent on self-consumption and compensation due to electricity injected into the grid, as well as the assumed evolution of the electricity prices. A sensitivity analysis is carried out for different installation sizes and different evolution scenarios concerning electricity prices. The potential for installations for shared self-consumption with dynamic and static distribution coefficients is also analyzed. The results show that medium sized installations are generally a cost effective way to reduce energy bills, while the economic performance of larger installations is more uncertain, and is largely dependent on the selling price for electricity injected into the grid. This case study found that the economic benefits of shared self-consumption between different companies are substantial, and are slightly more favorable when applying dynamic distribution factors. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to calculate day-ahead wind speed predictions based on historical measurements done by weather stations. The methodology was tested for three locations: Colombia, Ecuador, and Spain. The data is input into the process in two ways: (1) As a single time series containing all measurements, and (2) as twenty-four separate parallel sequences, corresponding to the values of wind speed at each of the 24 h in the day over several months. The methodology relies on the use of three non-parametric techniques: Least-squares support vector machines, empirical mode decomposition, and the wavelet transform. Moreover, the traditional and simple auto-regressive model is applied. The combination of the aforementioned techniques results in nine methods for performing wind prediction. Experiments using a matlab implementation showed that the least-squares support vector machine using data as a single time series outperformed the other combinations, obtaining the least root mean square error (RMSE). [ABSTRACT FROM AUTHOR]

Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC. [ABSTRACT FROM AUTHOR]

The trend in energy consumption, with a particular focus on heating and cooling demand, is an issue that is relevant to the promotion of new energy policies and more efficient energy systems. Moreover, heating and cooling energy demand is expected to rise in the next several decades, mainly due to climate change as well as increasing incomes in developing countries. In this context, the building sector is currently a relevant energy-intensive economic sector in Morocco; it accounts for 33% of the country's total energy demand (as the sector with the second highest energy demand, after the transport sector), with the residential sector accounting for 25% and the tertiary sector accounting for 8%. Aiming to reduce energy dependence and promote sustainable development, the Moroccan government recently issued a comprehensive plan to increase the share of renewables and improve energy efficiency. This strategy includes novel thermal building regulations promoted by the Moroccan Agency for Energy Efficiency. This paper analyzes the thermal behavior and heating-cooling energy demand of a residential building located in Tangier (Morocco) as a case example, based on the country's new thermal regulations and considering specific climatological conditions. A comparison with common Moroccan residential buildings as well as with those in nearby countries with similar meteorological conditions but significant differences in terms of energy demand regulation and requirements, such as Spain, is also included. Simulations were carried out using the DesingBuilder and EnergyPlus Software packages. According to the results, the last building thermal regulation requirements in Morocco need to be revised and extended in order to achieve the energy efficiency objectives established by the Moroccan government for 2030. [ABSTRACT FROM AUTHOR]

Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC. [ABSTRACT FROM AUTHOR]

The trend in energy consumption, with a particular focus on heating and cooling demand, is an issue that is relevant to the promotion of new energy policies and more efficient energy systems. Moreover, heating and cooling energy demand is expected to rise in the next several decades, mainly due to climate change as well as increasing incomes in developing countries. In this context, the building sector is currently a relevant energy-intensive economic sector in Morocco; it accounts for 33% of the country's total energy demand (as the sector with the second highest energy demand, after the transport sector), with the residential sector accounting for 25% and the tertiary sector accounting for 8%. Aiming to reduce energy dependence and promote sustainable development, the Moroccan government recently issued a comprehensive plan to increase the share of renewables and improve energy efficiency. This strategy includes novel thermal building regulations promoted by the Moroccan Agency for Energy Efficiency. This paper analyzes the thermal behavior and heating-cooling energy demand of a residential building located in Tangier (Morocco) as a case example, based on the country's new thermal regulations and considering specific climatological conditions. A comparison with common Moroccan residential buildings as well as with those in nearby countries with similar meteorological conditions but significant differences in terms of energy demand regulation and requirements, such as Spain, is also included. Simulations were carried out using the DesingBuilder and EnergyPlus Software packages. According to the results, the last building thermal regulation requirements in Morocco need to be revised and extended in order to achieve the energy efficiency objectives established by the Moroccan government for 2030. [ABSTRACT FROM AUTHOR]

This paper presents a preliminary evaluation of the acoustic impact of an offshore experimental wind farm (E2O), conceived and planned to be installed in Asturias on Spain's northwest coast. A simplified assessment of the wind turbines' noise impact at an offshore platform was performed numerically, adapting commercial software for room acoustics to this particular application. As a result, the sound levels at specific receiver sites on the coastline were estimated to select the most convenient level between the two possible locations. Parameters from acoustic emission data of the selected wind turbines were introduced as inputs to the simulation, and the noise propagation in the analyzed domains (for different values of their basic parameters) was simulated. Complementarily, the numerical results were compared to calculations following the ISO 9613-2 standard on sound propagation outdoors for validation purposes, showing good overall agreement. The results revealed that both projected areas under consideration follow the current normative concerning the prescribed acoustic limits, according to the predicted low sound pressure values at the specific considered receiver sites. [ABSTRACT FROM AUTHOR]