The optimal dispatch of a microgrid is a complex issue with both important economic benefits and social benefits. To ensure the microgrid with distributed power to operate in a more economical, flexible and environmental way, and the advantages of distributed generation can be fully utilised, according to the problem of optimal scheduling of the microgrid, this study proposes a multi‐objective optimisation function model of the microgrid with an electric vehicle, which is used as a load and power generation unit at the same time, which aims to maximise the economic benefit and minimise the environmental cost of multi‐objective optimisation of the microgrid. In the process of optimisation, this study introduces the structure of a double chain and the adjustment strategy of the dynamical rotation angle, proposes a new modified quantum genetic algorithm, and compares with the traditional genetic algorithm and the fundamental quantum genetic algorithm. Finally, numerical examples are provided to verify the effectiveness and feasibility of the proposed model, strategy and algorithm.

The uniformity of the excitation magnetic field is an important factor affecting the measurement accuracy of the electromagnetic flowmeter and its adaptability to different flow states of the complex multiphase flow. The main purpose of this paper is to improve the measurement accuracy of electromagnetic flowmeter by improving the uniformity of magnetic field excitation of electromagnetic flowmeter sensor. Firstly, an evaluation index system based on area weight magnetic field deviation degree is established, and the concept of flow state adaptability is put forward. According to this evaluation system, the excitation structure of the conventional electromagnetic flowmeter sensor is improved and optimized, and an excitation model with high uniformity is designed. Meanwhile, the ANSYS software is used for numerical simulation, and normalized standard deviation is used to compare between the new and the traditional electromagnetic flowmeter models. Finally, according to the requirements of the index function, the magnetic pole detection angle of the improved excitation model is simulated and analyzed, and the optimal magnetic pole detection angle is determined to be 45°. On this basis, a new electromagnetic flowmeter is designed for complex multiphase flow at oil wellhead. The field test proves that the measurement error of this flowmeter can reach less than 5%. Compared with the traditional electromagnetic flowmeter, the measurement accuracy has been greatly improved.

Due to the difficulty in accurately detecting the health status of cable joints, a new method of identifying and assessing the cable joints’ health status based on traveling wave reflection is proposed. By transmitting nanosecond pulse signals at the head end of the cable, the health status characteristics of the cable joints can be obtained, and the noise reduction of the measurement signals is performed by the wavelet function to identify the reflected wave at the joint and the end of the cable. The equivalent circuits and simulation models of contact resistance and leakage resistance are established, and the contact resistance and leakage resistance of the cable joints are calculated according to the amplitude and phase of the reflected signals at the joint and the end of the cable. By comparing with the resistance when the joint is in healthy operation, any measured parameter exceeding the corresponding standard is considered a joint fault. Simulations and test results show that the method can accurately identify the reflected signals of the cable joints in different operating states, and with changes in joint health, clear regular features can be extracted from the reflected signals, and the quality and health of the joints can be determined. The traveling wave method can be used to detect cable joint faults and provide an early warning of defects, which provides a new idea for online monitoring and early warning of cable joints in both theory and engineering practice.

The influence of load rate and other factors is not considered in the temperature rise monitoring process of traditional motor, which will lead to the wrong diagnosis of motor health status. In this paper, the characteristics of motor temperature rise under different ambient temperatures and different load factors are studied. Taking an 11kW three-phase asynchronous motor as an example, the temperature rise model of the motor is based on the finite element method established using ANSYS software. The thermal conductivity coefficient and surface heat dissipation coefficient of each part of the motor are determined. According to the electromagnetic field calculation, the motor loss distribution is obtained, and the temperature rise distribution curve of the motor is obtained by the simulation of the three-dimensional steady temperature field of the motor. In this paper, the temperature rise variation law of the motor considering the influence of environmental temperature and load factors is proposed, and combined with the temperature rise threshold curve of the motor under different load rates, a dynamic threshold judgment system is established to accurately warn the motor of overheating under any load rate. When the motors health status changes after running for a long time, it provides an important theoretical basis for accurate diagnosis of the motors health status.