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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 Increasing electrification of final uses can be a viable solution towards low-carbon energy systems, when coupled with local renewable power generation. Mountain areas can already benefit from high shares of hydro-power generation, but, at the same time, rely on oil products for transport and for the heating sector in remote areas where natural gas infrastructures are not available. This research work evaluates potential scenarios for the electrification of transport and heating sectors, by coupling the simulation tool EnergyPLAN with a multi-objective optimization algorithm to analyse economic and environmental aspects. Results show that the largest benefits are expected from the electrification of the heating sector. Indeed, a CO2 emissions reduction up to 30% can be reached by acting on the transport sector alone, while up to 65% combining it with measures on heating, industry and agriculture sectors and additional electricity generation from photovoltaic systems. Moreover, the use of heat pumps can lead to significant CO2 emissions decrease with only to a slight increase in the overall annual costs thanks to lower variable costs that partly compensate the higher required initial investment and electricity storage deployment. The optimization analyses also highlight the effect of progressive penetration of electric vehicles in the private cars fleet and hydrogen trucks in the light-duty vehicles one.

An operational cost minimisation model is established for a smart energy hub (S.E. Hub) consisting of a combined heat and power (CHP) unit, a heating, ventilation and air-conditioning (HVAC) system, and thermal and electricity storage units. The optimal operation of CHP is combined with the load management of HVAC under a time-of-use (TOU) tariff. The heat and power split ratio of CHP is dynamically determined during the operation. The scheduling of HVAC load and the charging/discharging of energy storage systems are also determined through the optimisation model. The energy management system can therefore shift the load demand and manage energy supply simultaneously. System operation requirements and environment factors including the outdoor air-temperature variation, seasonal variation, and battery degradation are considered. Comprehensive case studies are carried out to examine the effectiveness of the proposed strategy, from which insights are obtained for different energy management strategies and possible upgrade of S.E. Hub. Simulation results reveal that dynamic control of the CHP heat and power split ratio is an effective way to save the total operational cost, and a clear cost saving is shown through the proposed optimal operation strategy.

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 Methane from biomass is a well suited renewable energy carrier with a wide range of applications. The main technologies for its production out of biomass are biochemical conversion from the upgrading of biogas and thermochemical conversion by gasification and methanation. Presently there exists no methodology to compare the process alternatives for methane production from biomass. This paper investigates a comprehensive evaluation method based on a multi-criteria analysis. Due to the comparable well developed biomethane market in Europe, compared to other regions in the world, the study area was restricted to Europe. The weighting of the different criteria is carried out in two rounds as a pair-to-pair comparison of the criteria by experts from different technology fields in a Delphi-Survey. As a result, the prioritisation can be used to classify the biomass conversion technologies to convert biomass to biomethane. According to the weightings given by experts, the two criteria energy efficiency and production costs are of great importance compared to the other criteria.

‘Gher’ farming is a unique system that incorporates the joint operation of three enterprises: freshwater prawn, fish and HYV rice, and is expanding rapidly in the coastal regions of Bangladesh because of its proven high income earning potential. In this paper, the sustainability of this system is evaluated by analysing its performance in terms of energy use by applying a stochastic distance function approach which revealed interesting and unexpected results. The prawn enterprise which is the key income earning component is found to be technically inefficient while the rice enterprise is found to be efficient. The net energy balance and the energy use efficiency of the ‘gher’ farming system is estimated at 18,510 MJ ha−1 and 1.72 respectively. The ‘gher’ farmers are operating at a very high level of technical (energy) efficiency (92%). Diversification amongst enterprises is associated with technical (energy) inefficiency. However, larger operation size enhances efficiency. The key policy implication is that the ‘gher’ farming system can be sustained in the long run provided that productivity from the rice enterprise remains high. Also, policies to support the expansion of ‘gher’ farm sizes will improve efficiency.

Abstract This paper presents the application of the AHP (analytic hierarchy process) method to evaluate bioenergy developments regarding their regional sustainability in a case study area (Tayside and Fife/Scotland). Achieving regional sustainable bioenergy generation is challenging due to the complexity of this sector and the multidimensionality of the sustainability goal. The paper presents a complete and comprehensive AHP application by taking account of two different scenarios and their alternatives, C&I (criteria and indicators) and preferences of bioenergy experts. Although, case-specific C&I weighting and performance assessments are required to make this study valuable for similar decision making situations, the rather generic scenarios allow elements of this study to be transferred to a wide range of decision making situations within the energy and particularly the bioenergy field. The detailed analysis of results, including analyses by end node C&I and by alternatives, demonstrates that decentralized bioenergy generation should be preferred to achieve regional sustainable bioenergy generation in the case study area. Sensitivity analyses explore variations of the subjective judgments made on the different levels of the AHP hierarchies. The results of the sensitivity analyses show that all results can be considered robust.

Abstract To gain the benefits of solar-biomass cogeneration plant, supplying energy to industry, the design optimization procedure is required to holistically integrate economical, technical and environmental aspects. This entails formulation of a performance criterion that maximizes solar fraction, reduces investment cost, lowers thermal storage loss and puts less pressure on biomass resources. It is also necessary to consider factors influencing the plant’s performance while giving active role to industrial demand. This kind of optimization approach adaptively evolves as influences change and is not static. However, such a criterion is not yet part in many of the existing design optimization schemes. In this work, an alternative optimization approach that addresses the aforementioned issues is proposed. To this end, a molten salt biomass boiler is modeled in MATLAB and integrated to a solar plant model in TRNSYS. The resulting configuration is latter optimized in GenOpt to minimize biomass power utilization index (BPUI) and excess saturated steam generation (ESSG). Demonstrated by a case study, a plant efficiency of 31.5% with 23.5% solar gain is optimally designed resulting in about 0.094$/kWh levelized cost of generation. Furthermore, considering global power outage loss, the hybrid plant could be seen as a preferred industrial source of energy.