Aiming at the problems of various influencing factors, complex modeling and insufficient prediction accuracy, a combined forecasting method of energy demand based on variational modal decomposition and deep belief network is proposed. Firstly, the periodicity and randomness of the cooling and heating load series are analyzed, and the variational modal decomposition method is proposed to decompose the cooling and heating load. Secondly, based on the fact that modal decomposition are prone to be redundant after decomposition, the sample entropy is used to reconstruct the decomposed mode components to reduce the degree of redundancy. Finally, because the initial weights of the deep belief network are too random, crisscross optimization algorithm is adopted. The cooling and heating load is predicted by optimizing the deep belief network, and the prediction results are analyzed according to the simulation example. The example shows that the proposed prediction method can effectively improve the prediction accuracy and is practical.

The N-k contingency constrained economic dispatch method guarantees the system stability and security while N-k contingency occurs. However, the introduction of N-k contingency leads to a higher operation cost. Flexible AC transmission system (FACTS) devices are adopted to control the power flow following N-k contingencies, which helps enhance system flexibility. An N-k contingency-constrained two-stage robust unit commitment with FACTS is thus proposed. Since this model is a two-stage tri-level mixed integer linear optimization problem that cannot be solved directly, a two-level solution method based on the nested column-and-constraint generation (Nested C&CG) is proposed. The upper level decomposes the primal problem into master problem and subproblem. The lower level is used to solve the subproblem and obtain the worst scenario. The proposed model and solution technique are tested on a six-bus and a modified IEEE RTS-79 system. The numerical results show the effectiveness of the proposed model and solution method.

After the electrolytic aluminum load is connected to Yunnan Power Grid on a large scale, it aggravtes the power flow of relevant sections. At the same time, due to the weak grid structure in Southeast Yunnan, power grid stability problems may occur and the stability level of power grid will be reduced after near-zone short circuit fault aluminum is modeled according to the load modeling group of IEEE Task Force, so as to more accurately reflect the external characteristics of electrolytic aluminum load different from the conventional load model. In combination with the characteristics of "heavy load in dry season and light load in wet season" of Yunnan power grid, the simulation software BPA is used to calculate and analyze the power grid stability under various trends of large modes in dry season, and the conclusion of power grid stability in Southeast Yunnan that can cover most operation modes is obtained. Aiming at the relevant power grid stability problems, the management means and technical measures that can be taken are studied to improve the power grid stability, which ensure the continuous and reliable power consumption of users.

A power sharing and demand response model of intelligent community is proposed in this paper to optimize the energy flow and power structure of a residential community with multiple intelligent buildings including photovoltaic output (PV), energy storage unit (ESS), electric vehicle (EV) and user load. Firstly, the demand response model of intelligent residential area is established to optimize the electricity consumption structure of residential area users. On this basis, all members in the community share energy, and EV and ESS are added to the sharing model. The whole community forms an energy sharing alliance by sharing renewable resources and energy storage system, and the benefits obtained from the alliance are distributed among the members through the cooperative game method (Shapley value). Finally, the example simulation analysis and strategy comparison experiment are carried out. The results show that the energy sharing and demand response model proposed in this paper can effectively realize the optimal distribution of electric energy and save the cost of electric power consumption for each intelligent building and the whole community.

Unbalanced cost management is one of the key issues that need to be resolved in the construction of China’s electricity spot market. By analyzing the composition of unbalanced cost and considering the key characteristics of China’s electricity spot market, a risk management strategy for unbalanced cost based on electricity price swaps is proposed. Based on the basic law of power market operation and market risk management, the price swap trading mechanism not only reallocates the risk of unbalanced cost between the two sides of the transaction, but also reduces the generation of unbalanced cost to a certain extent. Further the expected utility and risk attitude theory are used to give the transaction costs of electricity price swaps, and the analysis of examples shows that electricity price swaps transactions can be effectively used in the unbalanced cost risk management of the electricity spot market.

With the implementation of "carbon emission trading management measures"in China, the virtual power plant (VPP) is an effective means to solve the fluctuation of large-scale distributed energy and electric vehicle access to the grid, and its scheduling optimization in the carbon trading market and other energy markets have become a research hotspot. In this context, the virtual power plant in this paper introduces electric vehicles, electricity-to-gas, and carbon capture equipment, and uses the combined effect of electricity-to-gas and carbon capture equipment to make the electricity market, natural gas market, and carbon trading markets are united to form a multi-cooperative market. Taking into account the uncertainties of wind and photovoltaic, an optimal scheduling model of virtual power plants with electric vehicles is established in the multi-cooperative market. The charging and discharging management of electric vehicles and the multi-market transaction framework are introduced. In the multi-cooperative market, the highest total revenue is the objective function, including multi-cooperative market transaction revenue, various equipment costs, and electric vehicle compensation costs. Finally, a commercial solver YALMIP/CPLEX is used to solve the established optimization model, and the results of calculation examples show the rationality and economy of the established model.

In order to study the market mechanism and clearing strategy of virtual power plants participation in integrated demand response, an integrated demand response market mechanism and clearing strategy considering the adjustable capacity of virtual power plant are proposed. Firstly, the mechanism of virtual power plant participating in the integrated demand response market is analyzed, and the integrated demand response resource model considering the internal resources of virtual power plant is established. Then, the mathematical model of adjustable capacity of virtual power plant is proposed and solved by improved particle swarm algorithm. Finally, the integrated demand response market clearing strategy considering the adjustable capacity of the virtual power plant is proposed, and the interactive clearing method of the superior distribution network and the virtual power plant operator optimization strategy is designed. The results show that the integrated demand response market clearing strategy in this paper can reduce the total cost on the basis of ensuring the interests of virtual power plant operators, and achieve peak load shifting and new energy consumption.

Epoxy resin impregnated paper (RIP) bushings are widely used as transformer bushings and wall bushings. This type of bushing has stable electrical properties, explosion-proof, small size, light weight and other advantages. But its manufacturing process is complicated and difficult, improper process control will result in defects. In order to find out the characteristic parameter of defects, some samples are manufactured to simulate defects and their insulation parameters are investigated in this paper. For example, the dry time is shortened and the moisture is not dried completely during the heating & drying process; crack is resulted by uneven release of thermal stress during solidification process; incomplete degassing of material and residual gas creates bubbles in the condenser core. Insulation parameters such as insulation resistance, dielectric loss factor, and capacitance, frequency-domain dielectric spectroscopy (FDS), polarization and depolarization current (PDC) are studied. Test results indicated that all type of defects may lead to a larger tanδbut a smaller insulation resistance than normal bushing,and different defect bushings exhibit different rates of decrease and stability value at the polarization current. By analyzing FDS curves on different frequency bands and the PDC pattern, different bushing defects can be distinguished effectively. This study can provide reference for factory test and on-site test to diagnose the insulation state of the bushing.

In order to get closer to the actual path condition of transmission line and deeply understand the seismic response of transmission line under large span, large elevation difference and inconsistent excitation, a large span section of ± 500 kV DC transmission line is selected, and the refined finite element models with four tower and three span lines are established for seismic response analysis. The results show that the ground wire and conductor significantly reduces the natural frequency of the tower. The cross-over tower is obviously constrained by the ground wire and conductor, and the peak displacement of the tower top is very small. The member stress of ground wire peak, cross arm and tower body are all within the elastic range. The peak tension force of cross-over span conductor is much higher than the design value, but still less than the breaking force, and the value is related to the length of anchor tower cross arm. The influence of traveling wave excitation on the displacement response is irregular, and it has little effect on the member stress and conductor tension force.

To study the effect of degassing on the space charge distribution in the insulation of 525 kV HVDC crosslinked polyethylene (XLPE) cable, sample slices are cut from the outer, middle and inner insulation layers of both the degassed and undegassed XLPE cables. Space charge distributions in the samples are tested based on pulsed electro-acoustic method, the electric field distortion rate and the charge volume density attenuation rate are calculated. The results show that the residual amount of crosslinking byproducts in cable insulations decreases successively from inner to outer layers by degassing time, and the contents of the byproducts keep stable after a 30-day degassing. The degassing process of XLPE cable is considered to be completed when the total content of α-methylstyrene, acetophenone, and cumyl alcohol in the insulation inner layer is less than 3 mg/g and, at the same time the content of cumyl alcohol is less than 2 mg/g. The results of space charge measurement illustrate that the accumulation of heteropolar charges in XLPE samples is closely related to the content of crosslinking byproducts. The heteropolar space charges are mainly caused by the disintegration of the byproducts, and their distribution decreases gradually from the inner layer to the outer layer. Compared with the undegassed XLPE samples, the heteropolar space charges accumulation of the degassed samples decreases dramatically, and the electric field distortion rate and the charge density attenuation rate are significantly reduced.

Accurate identification of insulator jacket crack images requires a large number of samples for model training, but the actual crack image dataset for model training is seriously insufficient. To solve the problems of untrained models, overfitting and low accuracy caused by too few training samples, this paper proposes a new method applicable to insulator jacket crack image recognition under small sample conditions, which combines image enhancement techniques and meta-learning techniques to train the U-Net image segmentation network and finally obtain the insulator jacket crack image recognition model. Crack recognition models with and without meta-learning method are compared respectively by experiments, and the results show that the proposed method can achieve accurate recognition of insulator jacket crack images with small-scale raw data sets. Crack recognition is performed on 180 insulator images, 36 of which have crack defects. 30 images are recognized by the model without the meta-learning method, with a success rate of 83.3%; while all 36 images are accurately recognized by the proposed method, with a success rate of 100%.

Due to the influence of high intensity alternating magnetic field generated by transmission power lines, the conventional physical sign monitoring system cannot accurately identify the physical sign information of operators during live working, making it difficult to effectively guarantee their life safety. Aiming at the above problems, an anti-electromagnetic interference (EMI) monitoring system for live working signs is designed and implemented. Under the premise of not affecting the normal work of operators, the system monitors their physical signs, and realizes the real-time transmission of the physical signs of operators through 4G communication technology. At the same time, in order to make the monitoring equipment work normally in the high-intensity alternating electromagnetic field environment with live operation, a switchable multi-band pass filter is designed to achieve selective filtering of signals, so that it can meet the needs of communication and anti-electromagnetic interference. Mobile software can display real-time data curve, alarm, tips, information such as time, equipment electricity, and can process the obtained signs information, review the status of workers signs in advance, so that workers can timely stop operation before entering the sub-health state, to achieve the function of real-time monitoring, alarm information.