Critical Current Simulation and Measurement of Second Generation, High-Temperature Superconducting Coil under External Magnetic Field

This paper studies the critical current of second generation, high temperature superconducting coils under an external magnetic field experimentally and numerically. Two identical coils with different coated conductors are fabricated and tested under a direct current (DC) magnetic field along the axis of the coil. Then, a numerical model in cylindrical coordinates based on a sheet current model is built by taking the measured magnetic field dependency to analyze the current distribution and magnetic field distribution. The simulated critical currents of the coils under the DC magnetic field have good agreement with the measured results. We find that under the in-phase field, the critical current decreases as the magnetic field in the innermost turn is enhanced by the external field. Meanwhile, the anti-phase external field increases the critical current a bit at first, then decreases the critical current. We further discuss the critical current criteria of the coils, showing that the parallel field plays a more important role in critical current determination

Smart Community Energy Cost Optimization Taking User Comfort Level and Renewable Energy Consumption Rate into Consideration

With the rapid development of smart community technologies, how to improve user comfort levels and make full use of renewable energy have become urgent problems. This paper proposes an optimization algorithm to minimize daily energy costs while considering user comfort level and renewable energy consumption rate. In this paper, the structure of a typical smart community and the output models of all components installed in the community are introduced first. Then, the characteristics of different types of loads are analyzed, followed by defining the coefficients of user comfort level. In this step, the influence of load-scheduling on user comfort level and the renewable energy consumption rate is emphasized. Finally, based on the time-of-use gas price, this paper optimizes the daily energy costs for an off-grid community under the constraints of the comfort level and renewable energy consumption rate. Results show that scheduling transferable loads and interruptible loads are not independent to each other, and improving user comfort level requires spending more money as compensation. Moreover, fully consuming renewable energy has side effects on energy bills and battery lifetime. It is more conducive to system economy and stability if the maximum renewable energy consumption rate is restricted to 95%

Energy Management of Combined Cooling, Heating and Power Micro Energy Grid Based on Leader-Follower Game Theory

In this paper, we consider a general model and solution algorithm for the energy management of combined cooling, heating, and power micro energy grid (MEG) under the game theory framework. An innovative dynamic leader-follower game strategy is proposed in this paper to balance the interactions between MEG and user. We show that such game between MEG and user has a unique Nash equilibrium (NE), and in order to quantify the user’s expenditure and dissatisfaction, we model them and adopt the fuzzy bi-objective algorithm. For more details in the proposed game model, the MEG leads the game by deciding energy sales prices and optimizing the power, cooling and heating outputs according to the user’s load plan to maximize its own profit. With the prices being released by MEG, user’s adjustment of energy consumption follows and is again fed to MEG. In practice, we initialize simulations with daily loads of a typical community. As the numerical results demonstrate, MEG is proficient in consumption capacity of renewable energy and energy optimization. It also shows that the user achieves his economic optimum with experience of energy usage taken into account

Peak Load Regulation and Cost Optimization for Microgrids by Installing a Heat Storage Tank and a Portable Energy System

With the rapid growth of electricity demands, many traditional distributed networks cannot cover their peak demands, especially in the evening. Additionally, with the interconnection of distributed electrical and thermal grids, system operational flexibility and energy efficiency can be affected as well. Therefore, by adding a portable energy system and a heat storage tank to the traditional distributed system, this paper proposes a newly defined distributed network to deal with the aforementioned problems. Simulation results show that by adding a portable energy system, fossil fuel energy consumption and daily operation cost can be reduced by 8% and 28.29%, respectively. Moreover, system peak load regulating capacity can be significantly improved. However, by introducing the portable energy system to the grid, system uncertainty can be increased to some extent. Therefore, chance constrained programming is proposed to control the system while considering system uncertainty. By applying Particle Swarm Optimization—Monte Carlo to solve the chance constrained programming, results show that power system economy and uncertainty can be compromised by selecting appropriate confidence levels α and β. It is also reported that by installing an extra heat storage tank, combined heat and power energy efficiency can be significantly improved and the installation capacity of the battery can be reduced