Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Tortuosity regulation of two-dimensional nanofluidic films for water evaporation-induced electricity generation

Water evaporation-induced electricity generation is a promising technology for renewable energy harvesting.However,the output power of some reported two-dimensional(2D)nanofluidic films is still restricted by the relatively weak water–solid interactions within the tortuous nanochannels.To further enhance the comprehension and utilization of water–solid interactions,it is of utmost importance to conduct an in-depth investigation and propose a regulatory concept encompassing ion transport.Herein,we propose tortuosity regulation of 2D nanofluidic titanium oxide(Ti_(0.87)O_(2))films to optimize the ion transport within the interlayer nanochannel for enhanced efficiency in water evaporation-induced electricity generation for the first time.The significance of tortuosity in ion transport is elucidated by designing three 2D nanofluidic films with different tortuosity.Tortuosity analysis and in situ Raman measurement demonstrate that low tortuosity can facilitate the formation of efficient pathways for hydrated proton transport and promote water–solid interactions.Consequently,devices fabricated with the optimized 2D nanofluidic films exhibited a significantly enhanced output power density of approximately 204.01μW·cm^(−2),far exceeding those prepared by the high-tortuosity 2D nanofluidic films.This work highlights the significance of the construction of low tortuosity channels for 2D nanofluidic films with excellent performance.

Optimization Method for Electrical Water Heaters Considering Shifting Potentials of Electricity Consumption and Water-use Activities

Electrical water heaters(EWHs)are important can-didates to provide demand-response services.The traditional optimization method for EWHs focuses on the optimization of the electricity consumption,without considering the shifting potential of the wateruse activities.This paper proposes an optimization method for EWHs considering the shifting potentials of both the electricity consumption and wateruse activities.Con-sidering that the wateruse activities could be monolithically shifted,the shifting model of the water-use activities was developed.In addition to the thermodynamic model of the EWH,the optimal scheduling model of the EWH was developed and solved using mixed-integer linear programming.Case studies were performed on a single EWH and aggregate EWHs,demon-strating that the proposed method can shift the water-use activities and therefore increase the load-shifting potential of the EWHs.

Pulsed high-current discharge in water:adiabatic model of expanding plasma channel and acoustic wave

This paper presents the results of a theoretical and experimental study of the use of a pulsed discharge in water to obtain a strong acoustic wave in a liquid medium.A discharge with a current amplitude of 10 kA,a duration of 400 ns,and an amplitude pulsed power of 280 MW in water at atmospheric pressure created an expanding acoustic wave with an amplitude of more than 100 MPa.To describe the formation of the discharge channel,an isothermal plasma model has been developed,which made it possible to calculate both the expansion dynamics of a high-current channel and the strong acoustic wave generated by it.Our calculations show that the number density of plasma in the channel reaches 10^(20) cm^(-3),while the degree of water vapor ionization is about 10%,and the channel wall extends with a velocity of 500 m s^(−1).The calculations for the acoustic wave are in good agreement with measurements.

Evaporation-driven water flow induced electricity from porous carbon film

Subject code:E02 With the support by the National Natural Science Foundation of China,a collaborative study by the research group led by Prof.Zhou Jun(周军)from Wuhan National Laboratory for Optoelectronics,Huazhong University of Science and Technology,Prof.Guo Wanlin(郭万林)from Nanjing University

Bifunctional polyaniline electrode tailored hybridized solar cells for energy harvesting from sun and rain

Pursuit of energy-harvesting or-storage materials to realize outstanding electricity output from nature has been regarded as a promising strategy to resolve the energy-lack issue in the future. Among them,the solar cell as a solar-to-electrical conversion device has been attracted enormous interest to improve the efficiency. However, the ability to generate electricity is highly dependent on the weather conditions,in other words, there is nearly zero power output in dark-light conditions, such as rainy, cloudy, and night, lowering the monolithic power generation capacity. Here, we present a bifunctional polyaniline film via chemical bath deposition, which can harvest energy from the rain, yielding an induced current of 2.57 μA and voltage of 65.5 μV under the stimulus of real raindrop. When incorporating the functional PANi film into the traditional dye sensitized solar cell as a counter electrode, the hybridized photovoltaic can experimentally realize the enhanced output power via harvesting energy from rainy and sunny days. The current work may show a new path for development of advanced solar cells in the future.

Combined peak reduction and self-consumption using proximal policy optimisation

Residential demand response programs aim to activate demand flexibility at the household level.In recent years,reinforcement learning(RL)has gained significant attention for these type of applications.A major challenge of RL algorithms is data efficiency.New RL algorithms,such as proximal policy optimisation(PPO),have tried to increase data efficiency.Addi tionally,combining RL with transfer learning has been proposed in an effort to mitigate this challenge.In this work,we further improve upon state-of-the-art transfer learning performance by incorporating demand response domain knowledge into the learning pipeline.We evaluate our approach on a demand response use case where peak shaving and self-consumption is incentivised by means of a capacity tariff.We show our adapted version of PPO,combined with transfer learming,reduces cost by 14.51%compared to a regular hysteresis controller and by 6.68%compared to traditional PPO.

From laboratory to on-site operation:Reevaluation of empirically based electric water chiller models

Chiller model is a key factor to building energy simulation and chiller performance prediction.With spread of new types of electric water chillers that have higher performance and wider operating range,new challenges have been faced by building energy simulation tools and their chiller models.This work takes a new type of electric water chiller as a case study and reevaluates eight typical empirically based models for predicting the energy performance of electric water chiller to verify whether they are suitable for the new type of chiller,using both laboratory test data from chiller manufacturer and online monitoring data from on-site operation of a central cooling plant with chillers of the same type.The prediction ability of the chiller models(including model prediction accuracy and generation ability)in laboratory test and on-site operation situations are examined.The results show that the existing models can well describe the chiller performance in the laboratory test situation but perform poorly in the on-site operation situation.As the best two models in the laboratory dataset,the overall prediction errors of DOE-2 and GN model increase more than 250%and 75%respectively in the field dataset.The big discrepancy of model prediction accuracy in the two situations is mainly due to the differences of evaporator and condenser water flow rates between the laboratory and on-site operation datasets,which indicates the limitations of the empirical chiller models and implies further research in future in order to improve the suitability and reliability of chiller model.

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

In this paper,interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling.First of all,interval numbers are used to describe uncertain parameters including hot water demand,ambient temperature,and real-time price of electricity.Moreover,the traditional thermal dynamic model of electric water heater is transformed into an interval number model,based on which,the day-ahead load scheduling problem with uncertain parameters is formulated,and solved by interval number optimization.Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices.Furthermore,the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day.Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand,ambient temperature,and real-time price of electricity,enabling customers to flexibly adjust electric water heater control strategy.