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.

Optimisation of Electrical Distribution System by Using Solar Thermal Powered Systems and Its Impact on Electrical Distribution Feeders

In this research, the performance of the solar thermal powered systems (STPS) is analyzed with different models (without inserts, with inserts and with Nano fluids with different concentrations) and its impact on the Electric load in a residential/Institutional Electrical Distribution system. For this purpose, the electrical and solar thermal water heater is tested and validated. Solar thermal powered systems and its impact on the Institutional electrical distribution feeders are tested and compared with the energy efficiency (EE) and cost optimization. The goal of this paper is to analyze the impact of solar thermal energy on electrical energy consumption in the electrical distribution feeder level. The electrical system cost and energy consumptions are tabulated and observed that there is a considerable savings.

Cordierite Ceramics Prepared from Poor Quality Kaolin for Electric Heater Supports: Sintering Process, Phase Transformation, Microstructure Evolution and Properties

To efficiently utilize the kaolin, an economical way of preparing cordierite ceramic with high performance for electric heater supports was put forward. In this study, sintering process, phase transformation, microstructure evolutions were systematically studied by heating microscope, X-ray diffraction, scanning electronic microscope and thermal analysis. Properties（physical properties, electrical properties and coefficient of thermal expansion（CTE）） were tested for comprehensive performance evaluation. The results showed that the utilization of poor quality kaolin broadened the firing range of cordierite ceramic which was from 1 200 to 1 380 ℃. Microstructure becomes loose with increasing of the pore size, which had significant influence on bending strength and electrical properties. High content of K2 O in poor quality kaolin was the reason for liquid phase generation in sintering process, which further leads to microstructural changes. The cordierite ceramic sintered at 1 320 ℃ had the properties as follows： CTE of 1.98×10^（-6） ℃^（-1）（500 ℃）, bending strength of 90 MPa, apparent porosity of 15.1%, dielectric constant of 7.5（100 Hz）, and volume resistivity of 1.05×109 Ω·cm（100 Hz）. The comprehensive properties are very suitable for use as electric heater supports.

Experimental study on the new type of electrical storage heater based on flat micro-heat pipe arrays

A new type of electrical storage heater that utilizes latent heat storage and flat micro-heat pipe arrays （FMHPAs） was developed. The thermal characteristics of the heater were tested through experimentation. The structure and operating principle of the storage heater were expounded. Three rows of FMHPAs were applied （three rows with five assemblies each） with a mass of 28 kg of phase change material （PCM） in the heat storage tank. Electric power was supplied to the PCM in the range of 0.2-2.04 kW, and air was used as heat transfer fluid, with the volume flow rate ranging from 40-120 m3/h. The inlet temperature was in the range of 15-24~C. The effects of heating power, air volume flow rate, and inlet temperature were investigated. The electrical storage heater exhibited efficiencies of 97% and 87% with 1.98 and 1.30 kW of power during charging and discharging, respectively. Application of the proposed storage heater can transfer electricity from peak periods to off-peak periods, and the excess energy generated by wind farms can be stored as heat and released when needed. Good economic and environmental benefits can be obtained.

Parallel fabrication of silica optical microfibers and nanofibers

Optical micro/nanofibers(MNFs)taper-drawn from silica fibers possess intriguing optical and mechanical properties.Recently,MNF array or MNFs with identical geometries have been attracting more and more attention,however,current fabrication technique can draw only one MNF at a time,with a low drawing speed(typically 0.1 mm/s)and a complicated process for high-precision control,making it inefficient in fabricating multiple MNFs.Here,we propose a parallel-fabrication approach to simultaneously drawing multiple(up to 20)MNFs with almost identical geometries.For fiber diameter larger than 500 nm,measured optical transmittances of all as-drawn MNFs exceed 96.7%at 1550-nm wavelength,with a diameter deviation within 5%.Our results pave a way towards high-yield fabrication of MNFs that may find applications from MNF-based optical sensors,optical manipulation to fiber-to-chip interconnection.

Combined peakreductionandself-consumptionusingproximalpolicy 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.

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.