• Energy Research
• 2021-2025close
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Electrolyte imbalance caused by the undesired vanadium-ions cross-over and water transport through the membrane is one of the main critical issues of vanadium redox flow batteries, leading to battery capacity loss and electrolytes volume variation. In this work, the evolution of discharged capacity and electrolyte volume variation were firstly investigated adopting commercial electrolyte for hundreds of charge-discharge cycles in vanadium redox flow batteries employing different membranes, varying thickness and equivalent weight. Subsequently, with the support of a 1D physics-based model, the origin of the main phenomena regulating capacity decay and volume variation has been identified and different modifications in the preparation of electrolytes have been proposed. Electrolytes characterized by an equal proton concentration between the two tanks at the beginning of cycling operation turned out to limit capacity decay, while increasing electrolyte proton concentration was effective also in the mitigation of volume variation. The most promising electrolyte preparation combined the effect of high proton concentration and null osmotic pressure gradient between the two tanks: compared to commercial electrolyte this preparation reduced the capacity decay from 47.7% to 20.9%, increased the coulombic efficiency from 96.2% to 98.9% and the energy one from 79.9% to 83.4%, and also implied a negligible volume variation during cycles. The effectiveness of this electrolyte preparation has been verified with different membranes, increasing the range of validity of the results, that could be thus applied in a real system regardless of the adopted membrane.

Abstract Efficient electric heat pumps have the potential to significantly reduce greenhouse gas emissions from heating and cooling buildings. However, heat pumps’ initial costs can be prohibitively high and their lifetime costs are only situationally competitive with incumbent technologies. Here we show that a business model based on heat purchase agreements could lower these barriers to heat pump adoption. In this business model, a user hosts a heat pump owned by an aggregator. The aggregator installs the heat pump at low or no initial cost to the user. The user buys the heat pump’s heat or cooling output from the aggregator. The aggregator buys the heat pump’s input electricity in the wholesale energy market and sells the flexibility of their aggregate electrical load in ancillary service markets. This paper presents the first economic analysis of heat purchase agreements as a third-party ownership model for electric heat pumps. We derive conditions under which a heat purchase agreement is mutually beneficial to the user and the aggregator. We also provide a method to fairly price heat and cooling. A case study of a typical United States home shows that a heat purchase agreement could more than double the value of a heat pump investment relative to the incumbent business model. The potential impact of this work is to reduce emissions both directly, by accelerating replacement of fossil-fueled or inefficient heating or cooling equipment, and indirectly, by helping power system operators reliably integrate wind and solar generation.

Abstract This paper describes an analysis approach to assess water consumption attributed to electricity generation required to meet the demand for the entire Saudi residential building stock. In addition, the analysis aims at estimating the water consumption reduction due to cost-effective energy retrofit measures for the Saudi housing stock. The analysis estimated that the water consumed annually to generate electricity for the Saudi entire housing stock is 135 MCM representing almost 10% and 4% of the water used by the industrial sector. Moreover, it is found that both electricity generation need and associated water consumption can be reduced by 15.7% when lighting is retrofitted with low-energy fixtures and by 25.8% when high efficiency air conditioning systems are installed for all the existing Saudi housing stocks. For the housing stock located in the Central region with prevalent dry climates, replacing existing air conditioning by evaporative coolers can save 11.1 TWh/a (25.5%) in electricity consumption but increase the water consumption by 36.2 MCM/a (80.6%). A cost-benefit analysis of lighting retrofit is found to be highly cost-effective for both households and the government with payback periods of less than 1 year.

Energy production from clean sources is mandatory to reduce pollutant emissions. Among different options for hidden hydropower potential exploitation, Pump-as-Turbine (PaT) represents a viable solution in pico- and micro-hydropower applications for its flexibility and low-cost. Pumps are widely available in the global market in terms of both sizes and spare parts. To date, there are several PaTs’ performance prediction models in the literature, but very few of them use optimization algorithms and only for specific and limited prediction goals. The present work proposes evolutionary Artificial Neural Networks (ANNs) based on JADE, which is a typology of differential evolution algorithm, to forecast Best Efficiency Point (BEP) and performance curves of a PaT starting from the pump operational data. In this model, JADE is employed as optimizer of basic ANNs to upgrade parameter values of the learning rate, weights, and biases. The accuracy of the proposed model is evaluated through experimental data available from the literature and compared to a basic ANN and two versions of the differential evolution algorithm. Results are also validated with experiments on a PaT showing that the proposed method can achieve an average R2-value of 0.97, which is 5% higher than the one obtained with a basic ANN.