http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113935239-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_f7b587cdf287a5bfb94b13cbbe008c8f |
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F2111-04 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-047 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-01 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F30-27 |
| classificationIPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F111-04 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F30-27 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 |
| filingDate | 2021-10-13^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_78dcfa5beec4620914db3336be8e3263 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9d68e2ee6da64424a6514dccee5d4d1f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_22f75cc204f8274553f18cc8ea19054f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_11e24218567adc337ee65f0c0c5dfa52 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_e0d3ffe80da4a026dae2dbfac0f471ef http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_9b89167ebf7ebf32f65491e44e328689 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_def82733191d3e08f18a5f831c4709a6 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d5607b411197ec384effc6aa3c74d293 |
| publicationDate | 2022-01-14^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113935239-A |
| titleOfInvention | A new energy method for regional electric water heater load cluster consumption based on user behavior prediction |
| abstract | The invention discloses a new energy consumption method for regional electric water heater load clusters based on user behavior prediction, comprising: constructing a Bayesian normalized BP neural network-based electric water heater user water behavior prediction model, and obtaining the electric water heater user water behavior prediction Results: Based on the prediction results and the current water temperature of the electric water heaters, the electric water heaters in the regional electric water heater load cluster were weighted and sorted, and the electric water heaters that could not be accommodated were eliminated according to the current operating state of the electric water heaters to obtain the regional electric water heater regulation sequence; the optimal scheduling model was established. , the number m of electric water heaters to be dispatched is obtained by solving, and the first m electric water heaters are selected from the control sequence for orderly dispatch to realize new energy consumption. The present invention can obtain a reliable prediction result of water consumption behavior of electric water heater users, considers the difference of electric water heater load and the priority of dispatching, can realize full consumption of new energy and help to improve dispatching flexibility and user satisfaction . |
| priorityDate | 2021-10-13^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419512635 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID962 |
Showing number of triples: 1 to 28 of 28.