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Current energy market designs and pricing schemes fail to give investors the appropriate market signals. In particular, energy prices are not high enough to attract investors to build new or maintain existing power capacity. In this paper we propose a method to compute second-best Pareto optimal equilibrium prices for any market exhibiting non-convexities and, based on this result, an energy market design able to restore the correct energy price signals for supply investors.

Abstract In many visions and roadmaps, there is a broad agreement that fuel cells – both for stationary and mobile applications – are the key technology to allow the development of a hydrogen infrastructure. Furthermore, this development is generally thought to be based on a gradual, decentralised evolution. Nevertheless, in this paper it is argued that, taking into account the entire hydrogen chain (production, transport, storage, distribution and end-use), this decentralised fuel-cell based philosophy shows some serious flaws. Therefore, a new hydrogen-transition approach was pushed forward: mixing in of hydrogen into the natural-gas bulk. Using Flanders – the Northern part of Belgium – as a case study, the development of a transitory hydrogen infrastructure has been studied, taking into account the entire hydrogen chain and its dynamics, from production to end use. In a next step, this transition is being quantified. An optimisation model has been developed using Matlab and the commercial solvers GAMS and CPLEX. Following a mixed-integer linear-programming approach, this model is able to determine the economically optimal hydrogen-production mix and operational behaviour of each hydrogen-production plant separately. The model then allows gaining valuable insights in the importance of storage and the influence of fuel prices and carbon taxes with regard to the development of an early hydrogen economy.

This study is to our knowledge the first to describe the effect of a Gas-Gas Heater (GGH) of a coal fired power plant's has on (i) the H2SO4 concentration and (ii) the particle/aerosol number concentration and particle size distribution present in the flue gas. In the absence of a GGH, homogenous nucleation takes places inside the Wet Flue Gas Desulphurisation (WFGD) converting the gaseous H2SO4 into aerosol H2SO4. This leads to a high aerosol number concentration behind the WFGD with 80% of the aerosols being smaller than 0.02 μm. This implies that an amine based carbon capture (CC) installation treating this flue gas can suffer from amine mist formation due to the high amount of available nuclei (i.e., H2SO4 aerosols) resulting in high amine emissions. In contrast, in the presence of a GGH not only 70% of the H2SO4 is removed from the flue gas (measured at the Nijmegen powerplant), but also homogenous nucleation in the WFGD is prevented resulting in low particle number concentrations. The flue gas leaving the GGH will not create any mist formation issues in an amine based CC installation due to the low amount of nuclei present in the flue gas. It is not the reduction in H2SO4 concentration by 70% inside the GGH as such that prevents mist formation but absence of H2SO4 in its aerosol form. These results are most likely quite widely transformable to other power plants that burn low sulfur coal i.e., around 0.7 weight%. This information will serve future pilot and demo CC installation around the world; in particular when retrofitted on power plants that have a GGH.

Abstract This paper presents some research activities conducted at the Centre Spatial de Liege (CSL) in the field of space solar arrays and concentration. With the new generation of high efficiency solar cells, solar concentration brings new insights for future high power spacecrafts. A trade-off study is presented in this paper. Two different trough concentrators, and a linear Fresnel lens concentrator are compared to rigid arrays. Thermal and optical behaviors are included in the analysis. Several technical aspects are discussed: • Off-pointing with concentrators induces collection loss and illumination non uniformity, reducing the PV efficiency. • Concentrator deployment increases the mission risk. • Reflective trough concentrators are attractive and already proven. Coating is made of VDA (Aluminum). A comprehensive analysis of PV conversion increase with protected silver is presented. • Solar concentration increases the heat load on solar cells, while the conversion efficiency is significantly decreasing at warm temperatures. To conclude, this paper will point out the new trends and the key factors to be addressed for the next generation of solar generators.

This paper presents an integrated vehicle model to simulate simultaneously the driver, powertrains, chassis, body, road condition, vehicle dynamics and the Active Suspension (AS) system with/without an energy harvesting module. The developed model is used to investigate the ride comfort and influences of energy harvesting AS system on the total energy consumption of battery Electric Vehicles (EVs) relative to EVs with a passive suspension system. Preliminary simulation results show that compared to EVs with a passive suspension system, the ones with AS system improve ride comfort, up to 31% reduction of the vehicle body acceleration RMS value, with an expense of higher energy consumption. This expense can be reduced to about 2.8% when using an energy harvesting AS system. Simulation results also demonstrate that the available energy for recuperation during the AS system operation is significant in relation to the regenerative braking energy of the propulsion system, up to approx. 70% on bumpy road surfaces.

Abstract This paper provides a forecast of electricity consumption in Cyprus up to the year 2030, based on econometric analysis of energy use as a function of macroeconomic variables, prices and weather conditions. If past trends continue electricity use is expected to triple in the coming 20–25 years, with the residential and commercial sectors increasing their already high shares in total consumption. Besides this reference scenario it was attempted to assess the impact of climate change on electricity use. According to official projections, the average temperature in the Eastern Mediterranean is expected to rise by about 1 °C by the year 2030. Using our econometrically estimated model, we calculated that electricity consumption in Cyprus may be about 2.9% higher in 2030 than in the reference scenario. This might lead to a welfare loss of 15 million Euros in 2020 and 45 million Euros in 2030; for the entire period 2008–2030 the present value of costs may exceed 200 million Euros (all expressed in constant Euros of 2007). Moreover, we assessed the additional peak electricity load requirements in the future because of climate change: extra load may amount to 65–75 Megawatts (MW) in the year 2020 and 85–95 MW in 2030.

Data Availability: The data that support the findings of this study are available from the corresponding author, C. Wen, upon reasonable request. ; Deep-learning-based fault diagnosis of wind turbine has played a significant role in advancing the renewable energy industry. However, the imbalanced data sampled by the supervisory control and data acquisition systems has led to low diagnosis accuracy. Additionally, deep neural networks can encounter issues like gradient vanishing and insufficient feature learning during backpropagation when the model is too deep. This article introduces a novel approach that is based on dynamic weight loss functions to modulate unbalanced data and improve diagnostic accuracy by focusing on misclassification of a small sample number. The proposed approach employs a 1D-CNN model and an ensemble-learning-based convolution neural network (EL-CNN) to enhance diversity of models and complementarity of feature learning. The EL-CNN model addresses the problem of local features being overlooked and provides more accurate results. The effectiveness of this proposed approach is well demonstrated through experimental cases on real wind turbine pitch system fault data. Two different networks using three different loss functions and three state-of-the-art fault diagnosis models are tested, demonstrating the EL-CNN model’s superiority. ; This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 820776 (INTEGRADDE), the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, the Alexander von Humboldt Foundation of Germany, the BRIEF Award of Brunel University London, the National Natural Science Foundation of China under Grant 61973209, the Natural Science Foundation of Shanghai of China under Grant 20ZR1421200, and the Capacity Building Project of Shanghai Local Colleges and Universities of China under Grant 22010501100.

Abstract In this paper, a strategy is proposed in order to introduce in a realistic way wind generation into a transmission power system non sequential Monte Carlo adequacy study with economic dispatch. Thanks to the implemented solution, wind generation is consequently confronted to operational constraints related to high powered thermal units, nuclear parks or thermal machines with technical minimum value. Moreover, during each simulated system state, a DC load flow is also calculated in order to evaluate reinforcements optimizing the large scale integration of wind power production. The simulation tool modified during the present work is called Scanner© and is the property of Tractebel Engineering (Gaz de France – Suez) company. It has been here applied to an academic test system: the Roy Billinton Test System (RBTS).

Technical and economic developments in battery and fast-charging technologies could soon make fuel cell electric vehicles, which run on hydrogen, superfluous in road transport