Downloads provided by UsageCounts
This paper presents the operation of the optimization module of the Capacity Reserve Market application. First, a brief overview of the entire application and its business process, as well as the software architecture, is given. Then, a description of algorithms is given, ie a mathematical model of the optimization process. The following is a functional description of the optimization module software, as well as a description of the software technologies used. Finally, a brief overview of the further development plan is given. The optimization module was developed using the C ++ programming language on the Linux platform (specifically Oracle Linux 7.9). The basic optimization problem comes down to the linear programming problem, and open source libraries, specifically the GNU Linear Programming Toolkit, are used to solve this problem. Data on auctions, participants, CZC / ATC and other data are stored in a relational database on a MySQL compatible MariaDB platform. The described module was developed within the HORIZON 2020 project TRINITY (H2020-863874 Transmission system enhancement of regional borders by means of Intelligent market technology). Presented at: 35th Session of CIGRE Serbia, Zlatibor, Serbia, 3-7, October 2021
Presented at: 35th Session of CIGRE Serbia, Zlatibor, Serbia, 3-7, October 2021
Capacity trade-Optimization-GLPK-Linear programming-TRINITY, Capacity trade-Optimization-GLPK-Linear programming-TRINITY
Capacity trade-Optimization-GLPK-Linear programming-TRINITY, Capacity trade-Optimization-GLPK-Linear programming-TRINITY
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 25 | |
| downloads | 21 |

Views provided by UsageCounts
Downloads provided by UsageCounts