Application of Analytical Uncertainty Costs of Solar,Wind and Electric Vehicles in Optimal Power Dispatch

Juan Arévalo, Fabian Santos, Sergio Rivera


Context: Currently, renewable energy sources are playing an important role in counteracting the environmental impact of traditional energy sources. For this reason, system operators must have analytical tools that allow them to incorporate these new forms of energy. In electrical power systems, when incorporating renewable resources such as photovoltaic solar generation, wind power generation or electric vehicles, uncertainty is introduced due to the stochasticity of primary resources.

Method: Uncertainty costs are proposed that incorporate the injected power variability of the main sources of renewable energy (solar and wind) and the consumed power (electric vehicles). Variability is considered by the probability distributions of the primary sources of renewable energy (solar irradiation and wind speed).

Results: The main result of this research is the application of analytical costs of uncertainty. In this way it is possible to modify the cost function of a traditional economic dispatch. Additionally, it is proposed to solve the problem with a heuristic optimization method of economic dispatch of active-reactive power. Finally, a comparison is made with the operating cost of the system without the incorporation of renewable energies.

Conclusions: The proposed model in this article is a potential decision-making tool that power system operators may consider in the operation of the system. The tool is capable of considering the uncertainties of the primary sources of renewable energy. The probability distribution of the primary source forecast is assumed to be known. An opportunity in order to extend the model is to study its applicability to dynamic time horizons, contemplating the constraints of the unit commitment problem


economic dispatch, renewable energy, uncertainty cost


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Facultad de Ingeniería

Universidad Distrital Francisco José de Caldas

ISSN 0121-750X   E-ISSN 2344-8393