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Under the wake of COVID-19, agricultural production and people's consumption are seriously affected, in addition, the number of methods to quantitatively analyze of the degree of influence is limited. The big data of electrical power can accurately reflect the business situation of enterprises in the industry. This paper select hundreds of leading enterprises in agricultural industrialization as the analysis objects, and use Keyword Index Technology to construct the corresponding system of enterprise name-electric household number, and use Multilevel Coordination Algorithm to fit the electricity curve of leading enterprises in agricultural industrialization, to study the impact degree difference and resilience of the epidemic situation on the subdivision industry, and use Covariance Analysis Algorithm to analyze the correlation of subdivision industry under the epidemic situation, and to give the prospect of development opportunities in the period after the COVID-19 epidemic situation.

Multi-terminal DC grids based on voltage source converters (VSCs) are widely recognized as a feasible solution to cope with increasing electricity demand and high penetration of new renewable energy sources. The VSCs are vulnerable to DC line faults due to the high discharge current of DC-link capacitance. The high current would damage the insulation of DC cable, and subsequently destroy the anti-parallel diodes during freewheeling stage. In this paper, a current limiting protection scheme, which includes a current limiting circuit and a fault detection method based transient boundary voltage, for multi-terminal DC grids. The current limiting circuit is proposed to suppress the fault current within the interrupting capability of hybrid DC circuit breakers (HCB). The fault detection method is proposed to achieve fast and reliable fault detection of DC line. Comparisons with some conventional protection methods reveal the promising performance of proposed fault detection method. Simulation results of several cases have been verified the effectiveness of the proposed protection scheme, and indicate that the faulted DC line can be identified correctly and quickly, and the non-fault system is able to recover to normal operation immediately after fault clearance without power interruption.

Fault section identification and switching operation are two important tasks for electric dispatching operators in power systems. Now electric supply industries are undergoing restructuring and deregulation, and the operation modes are getting more complicated, electric components are operating near to their security limits along with the probability of fault increasing largely, and operation modes changing more frequently. Automatic fault section identification and expert-system-based switch operation instructing system are much helpful to improve the intelligent level of dispatching operation. At present automatic fault section identification system (AFSIS) as aided decision-making for the operators is put into the field, switch operation instructing system (SOIS) also does. But these systems almost belong to a single agent, with power systems rapidly expanding, they have exposed to some limits. On the basis of research on AFSIS and SOIS for many years, a multi-agent system (MAS) based dispatching operation instructing scheme is proposed in this paper. The cooperation between AFSIS and SOIS is the key problem to study. A task decomposing method based on structural property, and a hybrid coordination control strategy is presented. More researches are focused on MAS task decomposition, coordinated control, data share, communication implementation and MAS learning. A MAS-based dispatching operation instructing system (MASDOIS) is implemented and put into the field. The field application shows MASDOIS more advantageous than individual agent in the sides of integrated solving problems, cooperative control and information share.