There are abundant information on the network, such as weather information, book information and so on. Now the Web information has far exceeded human imagination. However, most deep web information resources are not available through simple click, and often need query interface. We use domain ontology to construct the interface schema extraction method, the approach extracts interface schema from the perspective of visual units and the internal codes. There are many data extraction methods. Among them, CAW (Context-Aware Wrapper) is representative and outstanding. Thus, we choose it as our state-of-art baseline algorithm. The extraction effect of this method is better than CAW in the experiment. Finally, the effectiveness of this method is verified.
Due to serious new energy abandonment in Jilin grid of China, an adaptive energy-load matching optimization method for wind-photovoltaic complementary is built in this paper. Among certain new energy sources, we adaptively select the combination of new energy stations with high load matching, so that more new energy is consumed and less power is discarded. In this paper, the optimization method of maximizing new energy consumption without energy-load matching is taken as the comparison benchmark, and the advantages of adaptive energy-load matching optimization method are analyzed from multiple scenarios of different total amount of new energy. By selecting the combination of new energy stations with high load matching degree, the method can obtain lower curtailment of new energy, and the complexity of decision space is reduced, making the decision variables of new energy stations can be solved in a short time,when the number of decision variables is big.
In order to solve the problems of insufficient new energy consumption and serious abandonment of wind and light in the three north areas of China, the electric boiler is installed in the power grid area where the wind power consumption is insufficient, and the electric boiler is used to absorb wind power on the spot. In this paper, the heating demand and the maximum heat storage capacity of the electric boiler with heat reservoir are reversely deduced based on the user's electricity consumption data for the first time. According to the time of use electricity price in Jilin Province, the bubble sorting principle is used to tap the adjustable potential of the electric boiler with heat reservoir, and the peak power consumption is shifted to the low, so as to reduce the user's electricity charge and absorb the abandoned wind during the low period of the power grid, it plays the role of cutting peak and filling valley and stabilizing power grid. Compared with the brute force exhaustive method, this method greatly reduces the computational complexity. Compared with the method relying on the parameters of electric boiler and environmental parameters, this method greatly reduces the data which is needed to be collected, and reduces the evaluation errors caused by the performance degradation of electric boiler.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.