A novel high-DPI and monodisperse droplet inkjet printhead with the piezoelectric cutter

High dots per inch (DPI) is the core index of inkjet printer, which is hindered by satellite ink droplet. Herein, we propose a novel high-DPI and monodisperse droplet inkjet printhead with the piezoelectric cutter. The as-established model has optimized the inkjet printhead structural parameters, actuating and cutting signal waveforms. The cutter element achieves moving the break-up point to the middle of the ink column, reducing the length of tail and generating a monodisperse droplet. Additionally, the cutter consistently reduces the droplet length with different ink properties including viscosity, density, surface tension, and contact angle, exhibiting high applicability. The research results provide an in-depth study on the design of high-DPI and monodisperse inkjet printheads, offering an efficient approach to improve inkjet printhead performance

A novel high-DPI and monodisperse droplet inkjet printhead with the piezoelectric cutter

High dots per inch (DPI) is the core index of inkjet printer, which is hindered by satellite ink droplet. Herein, we propose a novel high-DPI and monodisperse droplet inkjet printhead with the piezoelectric cutter. The as-established model has optimized the inkjet printhead structural parameters, actuating and cutting signal waveforms. The cutter element achieves moving the break-up point to the middle of the ink column, reducing the length of tail and generating a monodisperse droplet. Additionally, the cutter consistently reduces the droplet length with different ink properties including viscosity, density, surface tension, and contact angle, exhibiting high applicability. The research results provide an in-depth study on the design of high-DPI and monodisperse inkjet printheads, offering an efficient approach to improve inkjet printhead performance

Dynamics of Cohen-Grossberg Neural Networks with Mixed Delays and Impulses

Impulsive Cohen-Grossberg neural networks with bounded and unbounded delays (i.e., mixed delays) are investigated. By using the Leray-Schauder fixed point theorem, differential inequality techniques, and constructing suitable Lyapunov functional, several new sufficient conditions on the existence and global exponential stability of periodic solution for the system are obtained, which improves some of the known results. An example and its numerical simulations are employed to illustrate our feasible results

Optimal Dispatch of Regional Integrated Heating and Power System Based on Differential Thermal Inertia Model

As the physical carrier of Energy Internet, regional integrated energy system (RIES) has become an important role for improving comprehensive energy utilization efficiency. First, a subtle thermodynamic model of buildings and water-heating network was constructed based on differential thermal inertia model. Different from the traditional single-layer wall thermal inertial model, this paper constructed multi-layer wall thermal model. Then, an optimization scheme combining electricity and heat was established. The optimization results show that, compared with the traditional single-layer wall thermal inertia model, the proposed multi-layer wall thermal inertia model has better performance. The proposed comprehensive energy optimization scheme can reduce the cost of electricity while maintaining indoor comfort, and can provide a reference for the system operation status for distribution network dispatching

Optimizing Capacity Configuration of Photovoltaic and Battery Energy Storage Systems in EV Charging Station based on Time-of-Use Pricing

Abstract In order to improve the utilization efficiency of photovoltaic system (PV system) and battery energy storage system (BESS) in photovoltaic and battery energy storage integrated electric vehicle (EV) charging stations, the capacity of PV system and BESS need to be allocated reasonably. In this paper, the maximization of the net annual financial value is used as the objective function of photovoltaic and battery energy storage integrated EV charging station in its whole life cycle. The control strategy of BESS is proposed based on time-of-use pricing. And then the optimization configuration model of PV system and BESS capacity is built. The economic efficiency of EV charging stations is compared and analyzed with actual test system when PV system and BESS configurating. The results indicate that the income and investment payback period of charging stations can be significantly improved through the reasonable configuration of PV system and BESS.</jats:p

Distributionally Robust Stochastic Optimal Power Flow Considering N-1 Security Constraints with renewable

This paper proposes a data-driven stochastic optimal power flow model considering the uncertainties of renewable energy sources. The proposed model also focuses on the constraints of reactive voltage, aiming at improving the safety of voltage amplitude and reactive power output at each bus. Using data-driven linearization techniques, we simplified the calculation of system. In addition, Wasserstein ambiguity set was used to describe the uncertainties of renewable energy prediction error distribution, and a robust stochastic optimal power flow model considering N-1 security constraints is established. The simulation results on IEEE-39 system showed the accuracy and effectiveness of the distributionally robust optimization model and the reactive voltage constraint model provided a more stable operation schedule

Optimal Dispatch of Regional Integrated Heating and Power System Based on Differential Thermal Inertia Model

As the physical carrier of Energy Internet, regional integrated energy system (RIES) has become an important role for improving comprehensive energy utilization efficiency. First, a subtle thermodynamic model of buildings and water-heating network was constructed based on differential thermal inertia model. Different from the traditional single-layer wall thermal inertial model, this paper constructed multi-layer wall thermal model. Then, an optimization scheme combining electricity and heat was established. The optimization results show that, compared with the traditional single-layer wall thermal inertia model, the proposed multi-layer wall thermal inertia model has better performance. The proposed comprehensive energy optimization scheme can reduce the cost of electricity while maintaining indoor comfort, and can provide a reference for the system operation status for distribution network dispatching.</jats:p

Distributionally Robust Stochastic Optimal Power Flow Considering N-1 Security Constraints with renewable

This paper proposes a data-driven stochastic optimal power flow model considering the uncertainties of renewable energy sources. The proposed model also focuses on the constraints of reactive voltage, aiming at improving the safety of voltage amplitude and reactive power output at each bus. Using data-driven linearization techniques, we simplified the calculation of system. In addition, Wasserstein ambiguity set was used to describe the uncertainties of renewable energy prediction error distribution, and a robust stochastic optimal power flow model considering N-1 security constraints is established. The simulation results on IEEE-39 system showed the accuracy and effectiveness of the distributionally robust optimization model and the reactive voltage constraint model provided a more stable operation schedule.</jats:p