A method for analyzing the problem of frequent wideband oscillations in grid-connected renewable energy generation systems based on small-world (SW) networks and fast-slow dynamics is proposed, where the mechanism of bursting oscillations in complex power systems has been examined. A direct-driven permanent magnet synchronous generator (DPMSG) and a complex network consisting of multiple DPMSGs connected to the grid were chosen as examples in order to discuss the process of bursting oscillations in a single system with both alternating large-amplitude and micro-amplitude oscillations due to the multi-timescale coupling effect introduced by the disturbance. The process of bursting oscillations in generation nodes spreading among the system nodes, which leads to successive chaotic oscillations of each node of the whole system, was also investigated. The results showed that the bursting oscillations created by the nodes in power generation in grid-connected renewable energy generation systems can lead to oscillation instability of the entire system. Our simulation verified the feasibility and effectiveness of the method proposed in this paper.

This study investigates the research on nickel-cobalt-copper productive collaboration and intelligent decision-making technology for symbiotic coupling enterprises in the Gansu Province of China. The aim is to address the problems of low resource utilization efficiency, weak production collaboration, and an insufficient intelligent decision-making level in the nonferrous metallurgy industry. First, the present situation of nickel-cobalt-copper industry chain-level collaboration in the agglomeration area is analyzed extensively, and the corresponding problems are proposed. Second, the functional framework of productive collaboration and intelligent decision-making is presented from the industrial chain and industrial agent levels. In addition, the design methods of various balance strategies in the production collaboration within the industrial agent are provided. These can realise the daily balance of material, metal, and energy data in an individual industrial agent. Finally, with regard to intelligent decision-making at the industrial chain level, six key measures surrounding different themes are provided to support the implementation of productive collaboration and intelligent decision-making in the nonferrous metallurgy agglomeration area.

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To promote the efficient use of energy storage and renewable energy consumption in the integrated energy system (IES), an economic dispatch strategy for the concentrating solar power (CSP)-IES with generalized energy storage and a conditional value-at-risk (CVaR) model is proposed. First, considering the characteristics of energy storage and distributed power supply timing, a CSP-IES configuration is established by using a CSP plant to achieve thermal decoupling of the combined heat and power unit and by defining the thermal storage system of the CSP plant and the battery as the actual energy storage. Second, the fuzzy response of the logistic function is used to optimize the time-of-use tariff to guide load shifting, and the load shifting is defined as virtual energy storage. Third, the CSP-IES economic dispatch model is established to consider the carbon emission allowance model. Finally, considering the system uncertainty, a fuzzy chance constraint is used to relax the system power balance constraint, and then the trapezoidal fuzzy number is transformed into a deterministic equivalence class, and the CVaR model is used as a risk assessment index to quantify the risk cost of the system due to uncertainty. The CSP-IES economic dispatch model with CVaR is constructed. The feasibility and effectiveness of the proposed optimization model are verified by comparing various scenarios.