Browsing by Author "Pozo, David"

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Robust microgrid operation under renewable generation
(Institute of Electrical and Electronics Engineers Inc., 2018) Lopez Quizhpi, Julio Cesar; Pozo, David; Lopez Quizhpi, Julio Cesar
Renewable generation is shifting conventional generation in microgrids. Thus, the operation of microgrids is becoming more complex and challenging for ensuring stability and reliability. In this paper, we introduce a risk-averse approach for optimal operation of microgrids in the presence of renewable generation (RG) and Battery Energy Storage System (BESS). These sources are modeled and embedded into an AC optimal convex power flow equations. A Two-Stage Adaptive Robust Optimization mathematical framework is presented to address uncertainties in the load demand and renewable resources. Uncertainty is depicted with a polyhedron instead of probability distribution function. The resulting model is a three-level min-max-min problem. The robust model is formulated to minimize the total cost of energy purchased from the distribution substation and energy cost of distributed generation. Results of an illustrative example and a case study based on the 11-node test system show the effectiveness of the proposed approach.
Static and dynamic convex distribution network expansion planning
(Springer Verlag, 2018) Lopez Quizhpi, Julio Cesar; Pozo, David
This chapter presents static and dynamic optimization-based models for planning the electric distribution network. Based on a branch flow model, two Mixed-Integer Conic Quadratic Programming (MICQP) convex formulations are proposed to solve the network expansion planning models including high modeling fidelity of the intrinsic interaction of the manifold elements of the networks. The objective of the presented models is to minimize investment and operation costs by optimally deciding on installing new feeders and/or changing existing ones for others with larger capacities, installing new substations or expanding existing ones and, finally, installing capacitor banks and voltage regulators, modifying the network topology. In addition, discrete tap settings of voltage regulators are modeled as a set of mixed-integer linear equations, which are embedded in an ac optimal power flow. The presented MICQP models are convex optimization problems. Therefore globality and convergence are guaranteed. Computational results to verify the efficiency of the proposed methodology are obtained for a 24-node test system. Finally, conclusions are duly drawn