We propose an adaptive ramp control strategy with self-tuning offset and amplitude, as a simple yet effective solution for controlling dc-dc power converters despite load and input voltage variations. It is shown that our control technique is able to suppress chaos and subharmonic oscillations for a wide range of input voltage and loads. Furthermore, a systematic methodology based on bifurcation diagrams for tuning the controller is proposed. Stability and performance analysis have been done together with a proper comparison of our technique, and the classical control strategies often used in the literature. Particularly, Vin feedforward and adaptive slope compensation controllers have been considered for the buck and boost converters, respectively. Finally, the effectiveness of the control technique is validated for the buck converter via experimental setup.

In this paper, the variations in hydropower generation are addressed considering the seasonality and ENSO (El Niño-Southern Oscillation) episodes. The dynamic hypothesis and the stock-flow structure of the Colombian electricity market were analyzed. Moreover, its dynamic behavior was analyzed by using Dynamic Systems tools aimed at providing deep insight into the system. The MATLAB/Simulink model was used to evaluate the Colombian electricity market. Since we combine System Dynamics and Dynamic Systems, this methodology provides a novel insight and a deeper analysis compared with System Dynamics models and can be easily implemented by policymakers to suggest improvements in regulation or market structures. We also provide a detailed description of the Colombian electricity market dynamics under a broad range of demand growth rate scenarios inspired by the bifurcation and control theory of Dynamic Systems.

This paper reports a general model that describes the supply and demand of electricity in a national market based on the system dynamics (SD) approach. From the resulting SD model, it derives piecewise smooth (non-smooth) differential equations from the nonlinear functions and feedback cycles of the corresponding stock-flow structure. Subsequently, the stability of the equilibrium points and non-smooth dynamics of the SD model are investigated using the dynamical systems theory. Filippov systems are found in the proposed SD model and non-smooth vector fields associated with generators investment decisions are accumulated. Under this combining methodology, the non-smooth dynamics of energy markets that are governed by the supply and demand laws are uncovered mathematically and deeply described. In fact, we extend our investigation results to any energy market model attached to various investment decisions, confirming the generalizability of our research.