Inverter products have been developing towards higher power density and more compact structure. To enhance the power density of inverter systems within a limited structural space， several prototypes need to be made and a large number of experiments conducted during the research and development process. To shorten the development cycle and reduce the number of prototypes and experiments， a thermal simulation method was proposed for the power unit of the inverter. Through this method， the system steady-state temperature rise of each scheme and the temperature rise of core components can be simulated during the research and development stage. It is possible to compare the advantages and disadvantages of different schemes without making prototypes or conducting experiments. Experimental results verify that the thermal simulation method has relatively accurate prediction of the cooling capacity of the thermal system. This method can effectively improve engineers' ability to control system thermal characteristics during the power unit design stage， quickly compare the advantages and disadvantages of different cooling solutions. It can also reduce the number of prototypes and experimental times， increase the first-time design yield， and reduce research and development costs.

Aiming at ultra-low frequency oscillation in power system caused by hydraulic turbine governing system，an additional damping control strategy for governing side was developed. Firstly，according to the damping torque method，the negative damping generated by the hydraulic turbine governing system was regarded as the main reason for the ultra-low frequency oscillation of the power system. Secondly，the damping torque coefficient expression of the speed regulation system was derived，which proves that the coefficient is closely related to the time constant of water hammer effect and the PID parameters of the governor. Besides，based on the additional damping control strategy，the positive damping compensation was introduced in the speed control side of the system. The grey wolf optimization（GWO） algorithm was applied to optimize the PID parameters to further improve the damping characteristics of the system. Finally，simulation verification in a single-machine system and a four-machine two-area system was executed through Matlab/Simulink. The results illustrate that the proposed control strategy can significantly enhance the damping characteristics of the speed control system and effectively suppress ultra-low frequency oscillation.

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.

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

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 order to study the distribution of magnetic field and temperature field of dry-type transformer iron core more accurately，analyze the influence of different excitation on the magnetic field loss and hot spot temperature rise of dry-type transformer core，firstly，Maxwell was used to calculate the transient magnetic field distribution of dry-type transformer，and the loss of the iron core under no-load condition was obtained. On this basis，a three-dimensional dry-type transformer magnetic field-temperature field coupling calculation method was proposed. The magnetic field loss was coupled to Fluent as the heat source of temperature field calculation，and the fluid structure coupling method was used to calculate the temperature field distribution of dry-type transformer. Finally，based on the above method，the magnetic field and temperature field of transformer core under harmonic action were calculated，and the influence of harmonic on core loss and temperature rise of dry-type transformer was analyzed，which provides a reference for the monitoring of the temperature rise about the transformer core under harmonics.

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.

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.

Voltage source converter（VSC） connected to weak AC power grid has the risk of small disturbance instability. Under the traditional control strategy，VSC has to reduce output power to maintain stable operation. In order to improve the stability of the weak grid connected VSC system，first established a universal analysis model for revealing the stability mechanism of weak grid connected VSC based on the AC voltage outer loop，and revealed the influence of the coupling characteristics among the phaselocked loop （PLL） and the VSC outer loop control on system stability. On this basis，a parameter adaptive control strategy for virtual parallel point was proposed. The detailed switch model of VSC in the PSCAD/EMTDC environment verifies the effectiveness of the proposed control method.

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.