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The increasing depletion of natural resources, combined with a wider set of pressures on the environment, has, in recent years, highlighted the need for a more efficient use of energy and a development process that involves alternative energy sources. Energy efficiency has received much attention as a solution, implying both monetary and emissions savings. However, the latter may be partially offset by the income and demand effects of the former, both in more efficient sectors and in spreading to the wider economy. This is the problem of rebound effects. Taking Spain as a case study, and introducing an energy-related CGE model that develops the inclusion of renewables, this paper evaluates a combination of efficiency initiatives to deliver both reduced energy use by households and a more sustainable supply of energy. Our findings suggest that a package aimed at improving efficiency in household electricity and petroleum use, combined with a more competitive supply of energy from renewable sources, may be the only way to get reductions in all energy use, and thus benefit the economy. Specifically, we consider how this package may lead to positive economic impacts and associated rebound effects, where the latter are focused on a greener energy supply.

Abstract Wave trends have been shown to be relevant to energy generation in various areas of the world. Accordingly, this article describes the impact of wave trends on the design of oscillating water column wave energy converters. First, wave trends across the North-East Atlantic Ocean are analysed based on the ERA5 reanalysis. In addition, an empirical model that provides the capture width of an oscillating water column is employed, identifying an approximately linear relationship between the average wavelength and the optimal width of the chamber. Thus, combining wave trends and the empirical model, the optimal size of the chamber is found to vary significantly between different geographical locations and over the four decades between 1979 and 2018. Differences between the original geometry and the geometry optimised considering wave trends, reach up to 15% in some locations. As a consequence, oscillating water column chambers designed based on past available resources rather than the resource corresponding to the time when the device is to be deployed are demonstrated to be inefficient, with a significant difference in the optimal width and absorbed energy of the chamber. Accounting for changes in resource availability over time may assist in cost optimisation of unconventional renewable energy technologies.

Abstract Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1–24 h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24 h ahead.

Abstract Oscillating Water Column (OWC) devices are usually modelled as simple systems containing ideal, dry air. However, high humidity levels are likely to occur in a prototype device open to the sea, particularly in warm climates such as prevail in the lower latitudes. In this paper, a real gas model is implemented to take into account humidity variations inside an OWC chamber. Using a modified adiabatic index, theoretical expressions are derived for the thermodynamic state variables including enthalpy, entropy and specific heat. The model is validated against experimental data, and shown to provide better agreement than obtained using the ideal gas assumption. By calculating real air flow in an OWC it is shown that the mechanical efficiency reduces and the flow phase alters with respect to the ideal gas case. Accurate prediction of efficiency is essential for the optimal design and management of OWC wave energy converters.

This paper proposes a hybrid renewable energy system (HRES) consisting of photovoltaic (PV), wind and forest wood biomass power for cogeneration, and applies a multi-objective optimization methodology to study the trade-offs between life-cycle cost and environmental impact (EI) of such a system. The optimization is achieved by applying an operation strategy that maximizes the efficiency of the biomass power subsystem coupled with an optimization model based on the use of genetic algorithm (GA) to obtain the optimal system sizing. The system is designed to supply the electricity demand of a rural township and the thermal demand – both heating and sanitary hot water (SHW) – of a neighborhood in a district heating (DH) scheme. Indigenously available renewable energy sources (RES) are used, taking special care in the case of biomass to not exceed the self-growth rate of local tree species. Results show that by taking advantage of the thermal energy produced, the payback time of the investment required to install the system is significantly reduced, being profitable after 9 years. Furthermore, it is also observed that layouts with low costs have greater EI and vice versa. However, it is shown that moderate cost increases have great returns on EI reduction.

Abstract The implementation of externalities in energy policies is a potential measure for sustainability-oriented energy planning. Furthermore, decisions on energy policies and plans should be based on the analysis of a number of potential energy scenarios, considering the evolution of key techno-economic and life-cycle sustainability indicators. The joint interpretation of these multiple criteria should drive the choice of appropriate decisions for energy planning. Within this context, this work proposes –for the first time– the combined use of Life Cycle Assessment, externalities calculation, Energy Systems Modelling and dynamic Data Envelopment Analysis to prioritise prospective energy scenarios. For demonstration and illustrative purposes, the application of this methodological framework to the case study of electricity production in Spain leads to quantitatively discriminate between 15 prospective energy scenarios by taking into account the life-cycle profile of the transformation path of the power generation system with time horizon 2050. When compared to the application of the framework without implementation of external costs, the internalisation of climate change externalities is found to affect the ranking of energy scenarios but still showing the rejection of those scenarios based on the lifetime extension of coal power plants, as well as the preference for those scenarios leading to a high penetration of renewable technologies.

Abstract Herein a novel path is analysed for its economic viability to synergize the production of biomethane and dimethyl ether from biogas. We conduct a profitability analysis based on the discounted cash flow method. The results revealed an unprofitable process with high cost/revenues ratios. Profitable scenarios would be reached by setting prohibitive DME prices (1983–5566 €/t) or very high feed-in tariffs subsidies (95.22 €/MWh in the best case scenario). From the cost reduction side, the analysis revealed the need of reducing investment costs. For this purpose, we propose a percentage of investment as incentive scheme. Although the size increase benefits cost/revenues ratio, only the 1000 m3/h biogas plant size will reach profitability if 90% of the investment is subsidized. A sensitivity analysis to check the influence of some important economical parameters is also included. Overall this study evidences the big challenge that our society faces in the way towards a circular economy.

Abstract Liquefied Natural Gas (LNG) is becoming vital in relation to energy transition and fighting climate change. Because of its cryogenic temperature (111 K), LNG is an exergy “mine” that can be exploited in the regasification process for multiple industrial applications. But this exergy is usually wasted. This research presents a Combined Cold and Power (CCP) system with exergy recovery from LNG-regasification. This exergy is exploited for the combined production of electricity and low-temperature refrigeration distributed through a CO 2 District Cooling Network. These systems entail many benefits, but also pending challenges. The CCP system is modelled using real operation data, and its performance is analyzed and benchmarked against that of a cryogenic power plant, both at design and off-design operating conditions. The proposed CCP system reports an equivalent electricity saving of 139 kWh/t-LNG with an exergetic efficiency of 40%, turning into useful energy up to 64% of the maximum cold recoverable in the regasification process. The performance enhances as the heat source temperature rises. Higher LNG flow rates contribute to increase the electricity and refrigeration production, but irreversibilities also increase. Finally, findings show that a low LNG regasification pressure is preferable in spite of the negative effect on the power generation.