The ground–airborne frequency-domain electromagnetic (GAFDEM) survey is a mixture of ground and airborne electromagnetic methods with a source on the ground and a magnetic field receiver in the air. The technique probes different depths of the earth by transmitting waveforms at different frequencies. Therefore, multiple closely spaced frequencies are needed when surveying a specific target depth in detail. However, in the existing GAFDEM systems using a square wave or a 2n pseudorandom wave, the ground source needs to transmit more sets of waveforms with different fundamental frequencies in more flights to improve the vertical resolution for the same observed line, which will seriously reduce the exploration efficiency. In this paper, we design a depth-focused waveform to solve this problem based on a new full-cycle asymmetrical selective harmonic elimination pulse width modulation (SHEPWM) method. In the SHEPWM method, we obtain a desired spectrum by directly controlling the switching angles of a binary sequence with an artificial neural network algorithm. In our study, we first provide the basic theory and method for waveform design. Then, we realize the depth-focused waveform and pseudorandom waveform via simulation. Next, we employ the depth-focused waveform into practice and compare it with the 2n pseudorandom wave in a GAFDEM field survey. The test shows that the survey result with a depth-focused waveform has a higher vertical resolution and efficiency.

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system’s carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system.

Restricted by the symmetrical characteristics of the output waveform and the solving method of the mathematical model, selective harmonic elimination pulse width modulation (SHEPWM) technology cannot output pulse waveforms with variable and complex time-frequency domain information in real-time, which limits its application in many automation fields. This paper establishes a full-cycle (FC) asymmetrical SHEPWM mathematical model capable of outputting pulse waveform with arbitrary time-frequency domain information. Moreover, the step modulation Newton algorithm (SMN) is proposed to solve nonlinear transcendental equations. This method actualizes the real-time calculation of FC asymmetrical SHEPWM due to its advantages of low requirement in a precise initial value, high speed, as well as high accuracy in solving problems. The simulation and experimental results further verify the real-time, resiliency, and stability of the control system based on SMN.

This paper aims at developing a spectrum analysis approach to suppress the electromagnetic interference (EMI) and the current harmonics in an active power filter (APF) via periodic carrier frequency modulation sinusoidal pulsewidth modulation (PCFMSPWM) control signals based on double Fourier series. The APF EMI concentrated at multiples of switching frequency results from the concentrative current harmonics. A novel spectrum analysis method based on PCFM and double Fourier series is developed to reduce the APF current harmonics. In this scheme, the optimal frequency deviations and waveforms of periodic signals are selected by calculating the spectrum of PCFMSPWM control signals. As a result, the modulation signal which has the best suppression effect on the interference peak is obtained and the quantitative design of PCFM is realized. Simulations and experiments of an APF driven by standard SPWM and triangular PCFMSPWM are implemented. On the basis of the simulations and experiments, effectiveness of triangular PCFM in alleviating APF current harmonics and EMI are validated.