Algorithms for Optimal Power Flow Extended to Controllable Renewable Systems and Loads

Algorithms

Elkin D. Reyes¹  Sergio Rivera¹ 

[1] Electrical and Electronic Engineering, Universidad Nacional de Colombia, Sede Bogotá, Bogotá 111321, Colombia;

关键词: solar;    hydraulic and wind energy generation;    electric vehicles;    uncertainty cost function;    marginal costs;    uncertainty and risk analysis;   

DOI  :  10.3390/a14100276

来源: DOAJ

【 摘 要 】

In an effort to quantify and manage uncertainties inside power systems with penetration of renewable energy, uncertainty costs have been defined and different uncertainty cost functions have been calculated for different types of generators and electric vehicles. This article seeks to use the uncertainty cost formulation to propose algorithms and solve the problem of optimal power flow extended to controllable renewable systems and controllable loads. In a previous study, the first and second derivatives of the uncertainty cost functions were calculated and now an analytical and heuristic algorithm of optimal power flow are used. To corroborate the analytical solution, the optimal power flow was solved by means of metaheuristic algorithms. Finally, it was found that analytical algorithms have a much higher performance than metaheuristic methods, especially as the number of decision variables in an optimization problem grows.

【 授权许可】

Unknown