Abstract: A wind power accommodation oriented low-carbon operation scheduling method for offshore oil and gas platform energy system. Aiming at uncertainty and fluctuation of wind power, the method constructs a target linear planning model. A target function result of the model is the lowest power synthesis of a gas generator. Constraints of the model include a gas power generation and wind power synergetic ramp flexibility constraint, a gas generating capacity and wind power capacity synergetic flexibility constraint, an operating characteristic constraint of a gas generator set, an operating characteristic constraint of a gas compressor and a grid-connected operating characteristic constraint of a wind generator. The scheduling method can effectively cope with the uncertainty and fluctuation of wind power, so as to reduce carbon emission of the energy system of the offshore oil and gas field.

Abstract: The present invention relates to an optimal load curtailment calculating method based on Lagrange multiplier and an application thereof in power system reliability assessment, wherein the calculating method comprises the following steps: inputting all system states to be analyzed for reliability assessment and establishing corresponding optimal load curtailment models; classifying the optimal load curtailment models according to Lagrange multiplier to obtain several sets; and solving the optimal load curtailment models in each set by using Lagrange multipliers to obtain an optimal load curtailment corresponding to the system state. The core of the present invention is to establish Lagrange-multiplier-based linear functions between the optimal load curtailment and the system states, and the iterative optimization processes of the traditional optimal load curtailment calculating method are substituted with the simple matrix multiplications.

Abstract: The present disclosure discloses a method for fast determining a time-delay stability margin of a power system, which focuses on three steps, i.e., Jordan standardization, Taylor separation and Schur simplification, to reconstruct a new time delay system and reduce the system dimension. In this method, firstly, a time delay model is Jordan standardized; further, Taylor expansion is applied in a process for separating state variables with time delay from stage variables without time delay; then, balanced model reduction is realized by Schur simplification; and finally, a WSCC 3-generator-9-bus power system with multiple delays will be used to validate the proposed method via several typical criteria.

Abstract: The present disclosure discloses a method for fast determining a time-delay stability margin of a power system, which focuses on three steps, i.e., Jordan standardization, Taylor separation and Schur simplification, to reconstruct a new time delay system and reduce the system dimension. In this method, firstly, a time delay model is Jordan standardized; further, Taylor expansion is applied in a process for separating state variables with time delay from stage variables without time delay; then, balanced model reduction is realized by Schur simplification; and finally, a WSCC 3-generator-9-bus power system with multiple delays will be used to validate the proposed method via several typical criteria.

Abstract: A planning method of EV fast charging stations on the expressway, comprising the following steps: Step 1: forecasting the spatial and temporal distribution of EV charging load, that is to determine the time and location of each EV needing charging on the expressway; Step 2: based on the forecast result achieved by Step 1, determining the locations of the fast charging stations on the expressway by the nearest neighbor clustering algorithm; Step 3: according to the spatial and temporal forecast result of the EV charging load and the locations of the fast charging stations, determining the number c of the chargers in each fast charging station by queuing theory. Due to battery characteristics, traditional gas stations do not completely match the fast charging stations.

Abstract: The present invention discloses an impact increments-based state enumeration (IISE) reliability assessment approach and device thereof. The method includes: inspecting the accessibility of all elements of the independent adjacency matrix by the breadth-first search method; if there is inaccessible element, the impact increment is zero and the power system state is reselected; if there is no inaccessible element, evaluating the impact of the power system state under all load levels via optimal power flow algorithm, acquiring the impact expectations of power system state under different load levels, and then acquiring the impact increments of the power system state; acquiring the reliability index of power system by impact increment when all the centralized power system states have been analyzed and the maximum number of contingency order has reached.

Abstract: The present invention comprises a partition-composition method and its equipment for online detection of transient stability of interconnected power system. The method consists of three parts. Firstly, according to the dynamic response data of the generators at the actual time, the key parameters of transient stability analysis of local areas can be obtained from local dispatch control center based on the wide area measurement system. Secondly, the key parameters of entire grid can be obtained using the uploaded parameters from the local area. Lastly, using the partition-composition method, parameters of an adjoint power system of the entire grid can be obtained. The equipment consists of 4 modules, including the first obtained module, transport module, the second obtained module and the composition module. Using these modules, transient stability data of entire grid can be obtained exactly without the limitation of network topology, system model and parameters.

Abstract: A planning method of EV fast charging stations on the expressway, comprising the following steps: Step 1: forecasting the spatial and temporal distribution of EV charging load, that is to determine the time and location of each EV needing charging on the expressway; Step 2: based on the forecast result achieved by Step 1, determining the locations of the fast charging stations on the expressway by the nearest neighbor clustering algorithm; Step 3: according to the spatial and temporal forecast result of the EV charging load and the locations of the fast charging stations, determining the number c of the chargers in each fast charging station by queuing theory. Due to battery characteristics, traditional gas stations do not completely match the fast charging stations.