Three-phase unbalanced dynamic power flow model predictive control method for distribution network with smart community
A technology of model predictive control and dynamic power flow, which is applied to AC networks, circuit devices, and AC network circuits with the same frequency from different sources, and can solve the problem of load uncertainty, Issues such as the grid-connected operation of the CCHP system, unbalanced three-phase, and real-time performance of difficult systems are not considered
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2018-08-31
Smart Images

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Abstract
Description
technical field
[0001] The invention relates to the energy Internet, in particular to the dynamic power flow of a distribution network including a community multi-energy flow optimization management system, and belongs to the technical field of multi-energy intelligent management and control. Background technique
[0002] Due to the decentralized and uncertain nature of distributed energy, direct access to the distribution network will have a greater impact on the power flow of the distribution network and increase the difficulty of regulating the distribution network. How to improve the distribution network's consumption and active management and control of distributed energy has become the focus of research on the premise of taking into account system economy, environmental protection, and safe operation.
[0003] For the problem of distributed energy access to the distribution network, there are two types of processing methods: one is to directly connect distributed energ...
Examples
Embodiment Construction
[0012] In order to more clearly illustrate the purpose and technical solutions of the present invention, further description will be given in conjunction with examples and accompanying drawings.
[0013] 1. Community multi-energy flow optimization model considering economic operation and environmental protection indicators.
[0014] 1) Uncertainty analysis
[0015] The random response surface method is used to analyze the probability density curves of forecast errors such as distributed wind power and light output, load and real-time electricity price, and discretize them, and the roulette algorithm is used to generate an initial scene set with corresponding probabilities, and the nearest neighbor clustering is used to reduce the scene . Take wind power output as an example for illustration.
[0016] Step 1: Taking the wind speed subject to the double-parameter Weibull distribution as an example, the standard normal distribution is used to standardize the wind speed, and the...