Optimal scheduling method of distribution network considering random output of high-density distributed power generation
A technology for distributed power generation and optimized scheduling, applied to AC networks with the same frequency from different sources, wind power generation, photovoltaic power generation, etc., to achieve the effects of ensuring feasibility, avoiding dimensionality disaster, and ensuring approximation accuracy
Active Publication Date: 2022-08-09
ZHEJIANG UNIV CITY COLLEGE
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[0002] Due to the great uncertainty of distributed power sources such as wind energy and solar energy, the operation and control of power systems with a high proportion of new energy are facing new challenges
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[0075] In order to express the idea of the present invention more clearly and intuitively, the technical solutions of the present invention are further introduced below with reference to specific embodiments. like figure 2 A joint active and reactive power scheduling method for a distribution network with a high proportion of distributed power sources for a 33-node distribution network shown, 4, 6, 7, 14, 16, 20, 24, 25, 30, and 32 nodes in the distribution network The wind and light distributed power sources are respectively connected.
[0076] like figure 1 As shown, the technical solution specifically includes the following steps:
[0077] S1: Use the orthogonal series expansion representation to establish a low-order approximate model that simulates the random timing characteristics of distributed power output.
[0078] Further, in the step S1, simulating the random timing characteristics of the output of the distributed power supply includes the following steps:
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The invention discloses a distribution network optimization scheduling method that takes into account the random output of high-density distributed power sources. The method models the random time sequence characteristics of power injected by wind and light distributed power sources at grid nodes, and is based on a sparse grid. The distribution theory samples the stochastic power flow space; aiming at reducing the active power loss and node voltage deviation of the distribution network, a joint stochastic optimization model for the active and reactive power of the distribution network with power flow balance and opportunity constraints is established; Orthogonal polynomial approximation is carried out on the random space in the work scheduling problem, and a convex approximate deterministic optimization model equivalent to the random optimization model is established. The dimensional disaster of the joint active and reactive power optimization scheduling model of distribution network in high-dimensional random parameter space is avoided. It can be widely used in the optimal scheduling of distribution network under the influence of high-dimensional random factors to improve the power quality of distribution network.
Description
technical field [0001] The invention belongs to the technical field of power system optimization, and in particular relates to a combined active and reactive power optimal scheduling method for a distribution network that takes into account high-dimensional randomness and chance constraints. Background technique [0002] Due to the great uncertainty of distributed power sources such as wind energy and solar energy, the operation and control of power systems with a high proportion of new energy are facing new challenges. Studying the stochastic optimal dispatching technology of power system can ensure the minimum active power loss of the power grid while improving the node voltage deviation of the distribution network in a stochastic environment. In order to overcome the complexity of a large number of distributed power sources and high-dimensional random parameter processing technology, an effective uncertainty quantification method is used to analyze the influence of random...
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IPC IPC(8): H02J3/00H02J3/38H02J3/46H02J3/06H02J3/32
CPCH02J3/003H02J3/381H02J3/466H02J3/06H02J3/32H02J2203/10H02J2203/20H02J2300/24H02J2300/28H02J2300/40Y02E10/76
Inventor 李静李艳君肖铎杜鹏英
Owner ZHEJIANG UNIV CITY COLLEGE