131 results about "Quantum genetic algorithm" patented technology

The invention discloses a fault feed line positioning method suitable for a power distribution network with high proportion of connected distributed power supplies. The method comprises the steps of constructing a power distribution network topology model graph which comprises high-proportion DG; constructing a switching function according to the constructed power distribution network model; constructing a fitness function according to the constructed power distribution network model; performing coding on the constructed model, namely performing quantum bit coding through using a wire inlet breaker, a section switch and a connecting switch of each feed line segment of the power distribution network as nodes; and when a true fault of a certain feed line occurs, performing the following fault determining steps according to an actual operation condition: reading the on-off state value of each breaker, the section switch and the distributed power supply connecting switch by an FTU system,and transmitting to a main station; after the main station receives fault information, performing simulation verification by means of a quantum genetic program; outputting a result, reading the faultfeed line and determining the fault switch. According to the method of the invention, fault positioning time is reduced through the improved quantum genetic algorithm, and real-time performance in fault positioning of the power distribution network is improved.

The invention relates to a quantum-genetic-algorithm-based fault diagnosis method for a medium-voltage distribution network. The method is characterized in that the method comprises the following steps that: step one, an improved medium-voltage distribution network fault diagnosis model is established by employing actual and expected values of element movement and combining the circuit breaker failure protection and the protection state of automatic opening and closing of the circuit breaker; and step two, a quantum-genetic-algorithm-based improved medium-voltage distribution network fault diagnosis model is solved to carryout fault diagnosis on the medium-voltage distribution network. According to the invention, the distribution network fault diagnosis model is established by analyzing the element type and the protection configuration situation of the distribution system; protection and the movement situation of and circuit breaker after a fault scene are simulated; and then the fault model is solved by using the quantum genetic algorithm. Therefore, functions that a fault element can be localized accurately after fault occurrence at a distribution network and the fault of the distribution network can be diagnosed rapidly and comprehensively can be realized.

The invention belongs to the technical field of bioinformatics and discloses an RNA secondary structure prediction method for a quantum genetic algorithm based on multi-population assistance. According to the method, a stem pool and a stem compatibility matrix of an RNA sequence is established according to the RNA sequence; quantum bit vectors are used to initialize multiple chromosome populations; quantum measurement is performed on each population; optimal individuals are acquired according to measurement results; the optimal individual b in all the populations is obtained and used to replace worst individuals, nonhomologous to b, among the optimal individuals in other populations, then all the populations are updated by use of different rotational angles, and other populations not participating in replacement are updated by use of a fixed rotational angle; and the process is iterated till a stop condition is met. Through the method, the global search capability and search efficiencyof the quantum genetic algorithm are effectively improved, and the evolution algebra of the genetic algorithm is lowered. Meanwhile, all the populations suppress competition and cooperate mutually, so that the globality of the algorithm is improved, and prediction accuracy is substantially enhanced.

The invention relates to an alternating-current / direct-current-system reactive power optimization method based on a good-point set quantum particle swarm algorithm. The method comprises the following steps of step1, establishing an alternating-current / direct-current-system reactive power optimization model; step2, improving a quantum genetic algorithm; and step3, using the improved quantum genetic algorithm to solve the alternating-current / direct-current-system reactive power optimization model. In the invention, the QPSO is improved and a problem of premature convergence generated because the QPSO is easy to fall into local optimum is solved.

The invention belongs to the technical field of network information, in particular to a network security situation awareness method for a power distribution communication network. The method comprisesthe following steps: dividing data of the power distribution communication network into real-time data and historical data, collecting the data by event triggering and periodic collection separately,and uploading the data; performing duplication removal on the collected data by fingerprint extraction algorithm and simhash dimensionality reduction, performing denoising by proximity algorithm, organizing different features of the data into a vector form, and distinguishing the real-time data from the historical data by status bits; performing data fusion and situation assessment on the real-time data from the historical data by a Bayesian network security situation awareness model and a ball vector machine classifier model with parameters optimized and trained by quantum genetic algorithmseparately; and performing security prediction on the power distribution communication network, and visually displaying the security situations, including real-time security situation prediction, real-time situations, history and other information.