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This paper studied the influence of transformer inrush current on commutation failure prevention control of Ultra-high voltage DC (UHVDC) transmission system. An actual event occurred on Tianzhong UHVDC transmission project was analyzed with data from fault recorder. UHVDC transmission model with commutation failure prevention control was established in PSCAD/EMTDC, and then it was applied to replay the event. It is found that the frequent maloperation of commutation failure control and the fluctuation of DC power exist when inrush current occurred. An improved commutation failure prevention control strategy was proposed to avoid this phenomenon. Validity of the improved method was proved by the simulation results.

This paper studied the influence of transformer inrush current on commutation failure prevention control of Ultra-high voltage DC (UHVDC) transmission system. An actual event occurred on Tianzhong UHVDC transmission project was analyzed with data from fault recorder. UHVDC transmission model with commutation failure prevention control was established in PSCAD/EMTDC, and then it was applied to replay the event. It is found that the frequent maloperation of commutation failure control and the fluctuation of DC power exist when inrush current occurred. An improved commutation failure prevention control strategy was proposed to avoid this phenomenon. Validity of the improved method was proved by the simulation results.

Abstract A numerical method is presented for solving a transient inverse heat conduction problem. First, the non-linear problem is reduced to an equivalent linear problem. Next, an adjoint solution technique is used to solve the equivalent linear problem for either the surface temperature of heat flux.

Abstract A numerical method is presented for solving a transient inverse heat conduction problem. First, the non-linear problem is reduced to an equivalent linear problem. Next, an adjoint solution technique is used to solve the equivalent linear problem for either the surface temperature of heat flux.

Abstract As states and utilities are moving to deep decarbonization, one challenge is to balance supply and demand on a longer duration. Despite great progresses, current battery storage technology can at best achieve daily balancing but is prohibitively expensive for monthly or seasonal balancing. This paper discusses the potential of a cross-seasonal balancing option, which is a cross-seasonal load shift by firms in the industrial sector (or seasonal demand flexibility).

Abstract As states and utilities are moving to deep decarbonization, one challenge is to balance supply and demand on a longer duration. Despite great progresses, current battery storage technology can at best achieve daily balancing but is prohibitively expensive for monthly or seasonal balancing. This paper discusses the potential of a cross-seasonal balancing option, which is a cross-seasonal load shift by firms in the industrial sector (or seasonal demand flexibility).

In allusion to the characteristic that transformer noise is mainly low-frequency noise, firstly the sound absorber is studied and analyzed on aspect of materials, sound absorption structure cavity thickness and punching rate etc in standing wave tube laboratory, secondly transformer substation low-frequency sound absorber is presented, and finally sound absorption properties of absorber is verified through random incidence Test. The analyses and study indicates that: compared with thin plate resonance absorber and micropunching sound absorber, the sound absorption band width of transformer substation low-frequency sound absorber has been improved under unchanged sound absorption effect and transformer low-frequency noise may be effectively absorbed.

In allusion to the characteristic that transformer noise is mainly low-frequency noise, firstly the sound absorber is studied and analyzed on aspect of materials, sound absorption structure cavity thickness and punching rate etc in standing wave tube laboratory, secondly transformer substation low-frequency sound absorber is presented, and finally sound absorption properties of absorber is verified through random incidence Test. The analyses and study indicates that: compared with thin plate resonance absorber and micropunching sound absorber, the sound absorption band width of transformer substation low-frequency sound absorber has been improved under unchanged sound absorption effect and transformer low-frequency noise may be effectively absorbed.

Risk preference is an important factor in electricity market strategy analysis and decision-making. The existing methods of risk preference analysis need to design and execute questionnaires or experiments on the subjects, and hence are costly and time-consuming for bidding in electricity markets. This article proposes a new method of data-driven risk preference analysis for power generation plants based on historical data and inverse reinforcement learning. Historical data are transformed to the transition function model according to the specific market mechanism. An adjusted inverse reinforcement learning model is thereafter proposed along with the optimization objective and technical constraints. The proposed method is tested in a simulated electricity market environment using the Australian Energy Market Operator (AEMO) day-ahead bidding data. Simulation results show that 1) thermal power plants prefer to adjust risk preferences within the day; 2) apart from the thermal power plants, the rest types of power plants are risk-neutral; 3) the daily risk preference trend of the thermal power plants varies in different seasons and is closely related to the load level.