In order to intervale evaluate saddle node bifurcation points（SNB） in a power system during load growth quickly and accurately， a quadratic approximation method to directly calculate the power system voltage collapse point of was proposed. Based on the approximate quadratic PV-curve of output PQ nodes in the system， load parameters were introduced into the node power balance equation， by using the complex function derivative rules to differentiate power equation twice， the first and second derivatives of node voltage to load parameters were derived theoretically， and the expression of PV curve function was further determined， then vertex coordinates were used to determine the initial position of saddle junction bifurcation point in the power system and the voltage collapse point was approximated by multiple iterations of convergence. The proposed method avoids multiple power flow calculations using the continuous power flow method，significantly reducing computational complexity. Simulation results on IEEE 14 and IEEE 118 bus systems demonstrate the effectiveness of this method. Compared with the supplemented P'Q node method and Thevenin's equivalent method， the quadratic form iterative approximation method has higher computational efficiency and robustness.

Under the "dual carbon" goal，the electric energy systems need to gradually develop towards the way of energy saving and low carbon. The integrated energy system （IES） is an important measure to solve energy and environmental protection problems. At present，the research on IES mainly focuses on distributed energy，energy storage grid connection and multi-objective optimization. Intelligent algorithm is an essential way to deal with optimization problems. However，with the complexity of the model，the traditional intelligent algorithms have the problem of poor convergence and easy to fall into the local optimum. Centering on the objectives of economy，environmental protection and stable operation，a multi-objective optimization model of IES based on improved particle swarm optimization considering three indicators of economy，environmental protection and output imbalance was built. Firstly，the IES model was established with the goal of optimizing the three indicators. Secondly，the membership function and the analytic hierarchy process （AHP） were used to normalize and determine the weight coefficient. Finally，the particle concentration evaluation operator was introduced to improve the particle swarm algorithm to solve the proposed model，and the operating results of the system under single-objective and multi-objective conditions were analyzed，which verifies the effectiveness of the model and algorithm. The improved algorithm significantly improve the convergence speed and effectively avoide the particles falling into the local optimum.

The safe and efficient operation of lithium batteries depends on accurate state of charge （SOC） estimation. However，the traditional battery model and SOC estimation have poor robustness and reliability under noise interference. Aiming at the problem of SOC cooperative estimation under noise interference，firstly，the maximum available capacity and open circuit voltage （OCV） characteristics of the battery were analyzed，and the curve characteristics of lithium battery SOC—OCV were studied. Then，the problem of online model parameter identification and SOC estimation under noise interference was studied，and a two-swarm cooperative particle swarm optimization （TCPSO） method based on adaptive dynamic sliding window was proposed. Experimental results show that the maximum SOC estimation error of the proposed method is less than 1%，which shows that the proposed method can realize online parameter identification，and it is superior to the existing collaborative estimation methods in terms of anti-noise performance and SOC estimation accuracy.

With the development of power electronics technology，microgrid type energy storage inverters with virtual synchronous generator（VSG） function have also been widely used. In VSG technology，due to the presence of inertial frequency regulation loop and voltage regulation loop，the inverter can realize the grid frequency regulation and voltage regulation function independently when it is connected to the grid，and it can realize the parallel power without communication when it is off-grid. However，in the microgrid system，due to the access of load and transformer，the parallel black start technology is one of the urgent problems to be solved when the inverter is off-grid. Through theoretical simulation analysis，an industrial frequency synchronous soft start method was proposed，which can realize smooth bus voltage establishment. The parallel power equalization of two VSGs during the soft start process achieved the completion of the black start of the whole system. Finally，the effectiveness of the parallel VSG black start control strategy was verified through experimental analysis.

The state of charge （SOC） of batteries is one of the most important parameters in lithium-ion battery management technology，and high-precision SOC estimation is beneficial for the grid connection and control of energy storage stations. Battery charge and discharge data are not only time-series in nature，but also have certain spatial relationships between feature variables. To improve the accuracy and generality of the estimation method，a SOC estimation method was proposed for lithium-ion batteries based on a joint convolutional neural networks-long short term memory networks（CNN-LSTM） network structure. Firstly，the feature relationships between different dimensions of lithium-ion battery data were obtained through CNN feature extraction，and then the time series relationships were extracted through the LSTM network structure. The joint network fully captures the spatial and temporal characteristics of the battery dataset. The experimental results show that the average error of predicting battery SOC based on the CNN-LSTM joint network model is controlled at 0.65%，which is about 4.4% lower than the average error predicted by a single CNN network and about 0.2% lower than the average error predicted by a single LSTM network. It has good application prospects.

In view of the frequent occurrence of omissions and false alarms of partial discharge insulation defects in on-site gas insulated switchgear（GIS），the partial discharge multi-source detection test platform was built by using true GIS to carry out the intermittent discharge test of metal contamination defect on the surface of insulator. Different partial discharge detection methods were used to study the variation of intermittent discharge characteristics of different discharge degrees. The research results show that the discharge amount of metal contamination defect shows a trend of first increasing and then decreases with the prolongation of discharge time；the overall discharge time interval shows an increasing trend；ultrasonic detection method and chemical detection method cannot realize the effective perception of intermittent discharge of metal contamination defect；the distribution law of intermittent discharge can be preliminarily obtained from the 200 frequency period ultra high frequency（UHF）phase-resolved partial discharge（PRPD）spectrum composed of 4 groups of 50 frequency period UHF PRPD spectrum data；metal contamination defect in intermittent discharge state will not gradually evolve into breakdown discharge failures. The research results are of great significance for expanding the cognition of intermittent discharge characteristics and the field detection of GIS discharge defects.

To address the issue that existing microgrid planning evaluation methods do not adequately account for the influence of uncertainties in the system and environment on the evaluation results，a microgrid planning evaluation method based on regret theory-vlsekriterijumska optimizacija i kompromisno resenje（VIKOR） was proposed. Firstly，a microgrid planning evaluation index system was constructed，which includes system economics，environmental protection and technology，taking into account the needs of the microgrid planning stage. Then，the analytic hierarchy process（AHP）-criteria importance though intercrieria correlation（CRITIC） method was used to assign weights to the indicators，taking into account the subjective experience of experts and the information contained in the objective data of the indicators. Finally，considering the influence of uncertainties on the evaluation results，the VIKOR method was improved by introducing the euphoria-regret function and state variables in the evaluation process based on regret theory，and a microgrid planning evaluation model based on regret theory-VIKOR method was established. The analysis of the example shows that the proposed evaluation method consider the influence of uncertainties in the system and environment as well as the psychological expectations of decision-makers on the evaluation results of the planning scheme，and is close to the actual microgrid planning scheme decision needs.

Industrial communication technology is an effective way to achieve network control of industrial equipment. With the development of Ethernet technology in recent years，a top layer application technology based on Ethernet，PROFINET has rapidly developed. However，due to the lack of high-speed network interfaces in the lower layer devices，it is necessary to convert the control and status words in the high-speed communication protocol into a protocol that can be easily parsed by the lower layer devices，and then connect the devices to high-speed Ethernet. This scheme adopted the ERTEC200P-2 communication protocol chip for high-speed data exchange with external Ethernet，and the lower layer was connected to the frequency converter through the UART serial interface. The scheme has passed experimental verification and on-site verification，achieved good results

In order to effectively adjust and control the motion amplitude of the flexible manipulator and avoid large deviation between the actual motion track of the flexible manipulator and the target track，a flexible manipulator motion track control system based on the combination of distributed control system （DCS） and inertial weight was designed. It is a computer system that integrates computer，communication，display and control and is controlled by process control and process monitoring. The DCS algorithm was used to control the behavior amplitude of the monitored object and calculate the inertia weight of the flexible manipulator. The DCS-inertia weight combination was used to solve the specific value of the prime control index. The software design of the flexible manipulator motion trajectory control system was realized. The experimental results show that the motion amplitude of the end coordinates of the manipulator in the horizontal，vertical and spatial axes under the action of the DCS-inertia weight combination algorithm can be controlled within 10 units of length，and the optimal control state of the manipulator's motion trajectory can be entered within 0.52 s，with the maximum difference of the motion trajectory being only 0.01 rad，which verifies the feasibility and effectiveness of the system.

In order to solve the problem of low accuracy of small substation fault diagnosis，a small substation fault diagnosis model based on cooperative game and cloud model was proposed. By analyzing the characteristics and causes of faults，the diagnosis index system was established. Entropy method and expert weighting method were used to obtain index weight，cooperative game method was used to calculate consistency coefficient and combination weight，and the final fitting weight was obtained through normalization. Through the cloud model，the quantitative expression of each index was realized，and the weighted deviation degree was obtained. According to the weighted deviation degree，the final diagnosis result was determined. The experimental results show that the index weight distribution of the established model meets the consistency requirements，and the diagnostic accuracy of fault location and degree is high，which can provide more guarantee for the safe operation of substation.