Controlling the flow of light on-chip is of great importance for quantum computing and optical signal processing. In this paper, we present a theoretical study to reveal the underlying physics of how to effectively trap, store and release a signal pulse, and eventually break the delay-bandwidth limit, based on controllable EIT-like effect in dynamically tuned standing-wave cascaded nanocavities. Using this mechanism, we design a compact silicon photonic crystal system with long storing time and a delay-bandwidth product over 460, which is about two orders of magnitude greater than the reported results obtained by other methods based on static resonator system, and the trapped signal pulse can be released on demand.
With the deepening of China’s energy market reform and the promotion of integrated energy services, the regional integrated energy system becomes an important development direction of energy supply system. In order to maximize the economic efficiency and reduce the air pollutant emission of the regional integrated energy system, the distributed power generation module and the cooling-heat-power (CCHP) triple-supply module are formed into a model, and the power balance, equipment capacity and environmental factors of the system are constrained with the objective function of minimizing the daily operation cost of the system as well as minimizing the air pollutant emission. Based on the mathematical system framework model and the optimal operation control strategy, the NSGA-II algorithm is used to solve the multi-objective programming model to obtain the Pareto solution set, and the hourly output of the optimal operation of the system equipment with both economic and environmental benefits is obtained. The results show that the daily operating costs and pollutant emissions of the district energy system are significantly reduced compared with those without optimization, which effectively solves the problems of low operating efficiency and serious environmental pollution of the district energy system and achieves the optimal operation with both economic and environmental benefits.
With the proposal and implementation of the "double carbon" goal in China, it is necessary to further improve the dynamic energy efficiency of the operation process of combined cooling, heating and power (CCHP) units to maximize the economic efficiency of the system. In this paper, the optimization algorithm based on the combination of chaos search of Tent map and nonlinear adaptive particle swarm optimization combines the schedulable resources of energy production, energy storage and energy consumption into a CCHP "source storage" system, which can simultaneously meet the power, heat and cooling needs of the user side. Taking the operation cost and pollutant emission of CCHP system as the objective, a multi-objective optimization model is established. Under the constraint conditions of equipment output, power balance and so on, the equipment operation hourly output with the best economic and environmental benefits is obtained. The calculation results show that the CCHP "source storage and load" system reduces the operation and maintenance costs by 22.31%, and carries out the economic and environmental advantages.
In order to solve the randomness and volatility of new energy power generation, promote the local consumption of renewable energy, and maximize the economic efficiency of CCHP system, this paper combines the schedulable resources of energy production, energy storage and energy consumption into a “source storage” system, which can meet the demand of power supply, heating and cooling at the same time. The objective function is to minimize the daily operation cost of the cold heat electric hybrid energy system, and the power balance and equipment capacity of the system are constrained. Using the established mathematical model of the system framework, the particle swarm optimization algorithm is used to improve the CCHP programming model to obtain the adaptation curve and the hourly output of the optimal operation of the equipment with the maximum economic benefit. The operation and maintenance costs of the two modes are analyzed in depth. The results show that the optimization of “source storage and load” system not only improves the reliability of energy supply, but also reduces the cost of operation and maintenance and improves the economic benefits of the system.
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