Under the background of carbon emission reduction，fully controlled power device IGBT is widely used in various of converters with its excellent performance，effective and reliable drive circuit is crucial to the safe operation of IGBT，especially for high-power applications. Aiming at the requirement of flexible and reliable of IGBT drive circuit in high-power applications，an IGBT drive and protection circuit based on intelligent integrated optocoupler driver ACPL-332J was designed，the parameters of ACPL-332J were analyzed，and the driving circuit was designed with ACPL-332J as the core. With Infineon FF600R12ME4 as the application IGBT，the effectiveness of the designed drive and protect circuit was verified by double pulse test and short circuit test.

Based on full-bridge（FB） and half-bridge（HB） sub-modules（SMs），the conventional hybrid modular multievel converter（MMC） is a typical topology of MMC with DC fault clearing ability. However，the proportion of FB SMs in conventional hybrid MMC is usually greater than 50%，so as to increase the cost and losses. To solve this mentioned issue，a DC fault commutated circuit based on thyristor-switched capacitor（TSC） structure in the hybrid MMC was integrated to reduce the number of FBs，the improved TSC-hybrid MMC was proposed in follows. In TSC-hybrid MMC，HB-MMCs and FB-MMCs were both retained their complete commutated body，and meanwhile，they were connected by a three-winding transformer in AC side and in series with DC side. In particularly，a thyristor-switched capacitor structure was integrated in the DC side of TSC-hybrid MMC to clear the DC fault. According to the analysis，the proportion of FB SMs in TSC-hybrid MMC can be reduced to 10%~25% or even lower （the AC-side voltage quality is a main limiting condition），the cost is reduced as well as the on-state losses. Simulation results validate the correctness of analyses.

With the large increase of load users，the load side adjustable resources gradually increase，and the load side demand response（DR） resources are used to participate in microgrid scheduling to improve the level of new energy consumption. In order to give full play to the scheduling potential of DR resources and optimize the user side load management capability， a multi-time scale optimal scheduling strategy for microgrids that takes into account scheduling priorities was proposed. Firstly，according to the response characteristics of different DR resources，the price-based demand response（PDR） resources and incentive-based demand response（IDR） resources were subdivided into five types，and a DR model was constructed to match the scheduling period. Secondly，the multi-times cale optimal scheduling model of "day-intra-day 1 h-intra-day 15 min" was constructed，optimized scheduling of various adjustable resources in the microgrid，and established priority weights for real-time adjustable resources that have a direct impact on users' electricity consumption behavior. Finally，taking an actual microgrid as an example in Fujian，the simulation verifies the validity of the model.

The traditional active distribution network location and capacity determination ignores the multi-energy complementary coordination characteristics of the energy system，which led to high cost. Therefore，an active distribution network location and capacity determination method based on energy interconnection was proposed. On the basis of energy interconnection，the objective function was established，and the whole life cycle cost theory was used to comprehensively consider the equipment purchase cost，installation cost，operation and maintenance cost，system operation cost and salvage value recovery. Taking the distribution network location and capacity determination comprehensive cost in the form of probability as the objective function，the necessary constraint models were constructed，including equipment configuration capacity constraint，system power supply reliability constraint，power balance constraint and equipment operation constraint. On this basis，the improved artificial fish swarm algorithm was used to solve the location and capacity determination algorithm. The simulation results show that the cost of the location and capacity determination of the active distribution network with distributed power is lower than that without distributed power. The total cost of network loss and reactive power compensation calculated by the improved artificial fish swarm algorithm is lower. Compared with other methods，the method proposed has lower loss cost and reactive power compensation cost. It shows that the proposed method can reduce the cost of active distribution network location and capacity determination，and the practical effect is better.

In order to effectively manage the grid short-circuit current overrun problem，optimization decision-making evaluation method of short-circuit current limitation scheme based on hybrid decision model considering asymmetric closeness was designed. Considering the relevant influence of the short-circuit current limiting measures of the power grid，a four-level evaluation index system considering short-circuit current，static safety，transient stability and implementation cost was established，eight three-level evaluation index factors were simplified and analyzed，and the decision evaluation results were divided further. An improved DEMATEL+ANP index weight assignment method for balancing the interaction relationship between indexes was proposed，and a hybrid decision-making model for the optimization decision evaluation of the short-circuit current limitation scheme of power grid was established by further considering asymmetric closeness，priority and cloud theory. Combined with simulation example based on PSASP，the effectiveness of the proposed optimization decision evaluation method was verified. This method can better balance the evaluation indexes，fully consider the fuzziness and randomness in the optimization decision evaluation，not only can realize the evaluation of multiple schemes，but also can realize the evaluation of its own scheme，and improve the accuracy and applicability of the optimization decision evaluation of the short-circuit current limit scheme of the power grid.

There are many elderly people with limb disorder in China，and exercise rehabilitation technology is an effective means of rehabilitation treatment. However，the serious imbalance of doctor-patient ratio makes it difficult for everyone to enjoy rehabilitation medical services. Impedance control technology is used for the safe interaction between rehabilitation robot and human body. However，constant impedance control is used in the existing rehabilitation robots，which has weak environmental adaptability and is difficult to be applied in clinical practice. In view of the above problems，a variable impedance control method was proposed. The user's surface electromyography signal（sEMG） was collected as input，and his upper limb motion angle was trained and recognized by the improved random forest algorithm. With the end force sensor，the motion intention was obtained，and then the rehabilitation motion was completed by the variable impedance controller. The experimental platform was built，and the track tracking and rehabilitation training abilities were verified and evaluated. The results show that the designed controller could control the robot to complete rehabilitation movement.

The process automation control system L2 of an aluminum zinc plating production line was explored.In response to potential production faults on the production line，a process data control module of the process automation control system was provided. Through the analysis of process data，the fault location of the strip steel or production line was analyzed. Finally，a quick method for finding the fault location was provided. The actual operation shows that this method is stable，reliable，and meets the control needs of actual production.