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Multi-output regression in electric power systems adequacy assessment using monte-carlo method

Boyarkin D., Krupenev D., Iakubovskii D. Multi-output regression in electric power systems adequacy assessment using monte-carlo method // SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. ID: 8958279. 2019. P.690-694. ISBN (print): 9781728144016. DOI: 10.1109/SIBIRCON48586.2019.8958279 This paper deals with the computational efficiency related problem appearing in electric power systems adequacy assessment using Monte-Carlo method. When...

Теги: adequacy assessment , energy power system , machine learning , monte-carlo , computational efficiency , electric power systems , learning systems , nonlinear programming , computational experiment , effective approaches , non-linear optimiza
Раздел: ИСЭМ СО РАН
Parametric optimization of supercritical power plants using gradient methods

Kler A.M., Zharkov P.V., Epishkin N.O. Parametric optimization of supercritical power plants using gradient methods // Energy. ID: 116230. 2019. DOI: 10.1016/j.energy.2019.116230 Gradient nonlinear optimization methods are among the most effective approaches to determine the optimal parameters of thermal power plants. These methods allow us to consistently optimize a large number of thermodynamic and design parameters and mass flow rates of actuation fluids and of heat-transfer fluids. This paper...

Теги: cost of electricity , gradient methods , mathematical modeling , nonlinear optimization , specific plant investments , supercritical power plants , costs , heat transfer , mathematical models , nickel alloys , nonlinear equations , nonlinear programming , superheater
Раздел: ИСЭМ СО РАН
An effective method for optimization of continuous and discrete parameters of heat and power plants

... continuously, and the other can take only discrete (integer) values. An effective method is developed to solve a thermal power plant optimization problem with continuous and discrete parameters. The method suggests an iterative procedure for solving continuous nonlinear programming problems and discrete-continuous linear programming problems. For each iteration, we add new constraints obtained by linearizing nonlinear inequality constraints and the objective function of the initial problem to the system of ...

Теги: discrete-continuous nonlinear optimization , heat and power plants , mathematical simulation , combined cycle power plants , constraint theory , integer programming , iterative methods , linear programming , nonlinear programming , thermoelectric power plants , was
Раздел: ИСЭМ СО РАН


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