Oscar Danilo Montoya

Bio: Oscar Danilo Montoya is an academic researcher from District University of Bogotá. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 18, co-authored 183 publications receiving 1324 citations. Previous affiliations of Oscar Danilo Montoya include Universidad Tecnológica de Bolívar & Technological University of Pereira.

Economic dispatch of energy storage systems in dc microgrids employing a semidefinite programming model

Abstract: A mathematical optimization approach for the optimal operation focused on the economic dispatch for dc microgrid with high penetration of distributed generators and energy storage systems (ESS) via semidefinite programming (SDP) is proposed in this paper. The SDP allows transforming the nonlinear and non-convex characteristics of the economic dispatch problem into a convex approximation which is easy for implementation in specialized software, i.e., CVX. The proposed mathematical approach contemplates the efficient operation of a dc microgrid over a period of time with variable energy purchase prices, which makes it a practical methodology to apply in real-time operating conditions. A nonlinear autoregressive exogenous (NARX) model is employed for training an artificial neural network (ANN) for forecasting solar radiation and wind speed for renewable generation integration and dispatch considering periods of prediction of 0.5 h. Four scenarios are proposed to analyze the inclusion of ESS in a dc microgrid for economic dispatch studies. Additionally, the results are compared with GAMS commercial optimization package, which allows validating the accuracy and quality of the proposed optimizing methodology.

Power Flow Analysis in DC Grids: Two Alternative Numerical Methods

Abstract: This express brief proposes two new iterative approaches for solving the power flow problem in direct current networks as efficient alternatives to the classical Gauss–Seidel and Newton–Raphson methods. The first approach works with the set of nonlinear equations by rearranging them into a conventional fixed point form, generating a successive approximation methodology. The second approach is based on Taylors series expansion method by using a set of decoupling equations to linearize the problem around the desired operating point; these linearized equations are recursively solved until reach the solution of the power flow problem with minimum error. These two approaches are comparable to the classical Gauss–Seidel method and the classical Newton–Raphson method, respectively. Simulation results show that the proposed approaches have a better performance in terms of solution precision and computational requirements. All the simulations were conducted via MATLAB software by using its programming interface.

An energy management system for optimal operation of BSS in DC distributed generation environments based on a parallel PSO algorithm

Abstract: This paper proposes an energy management system (EMS) for the day-ahead dispatch of battery storage systems (BSS) under a distributed generation environment for direct current (DC) networks, with the main objective of reducing the cost of the energy purchased to the utility grid. This approach considers the state-of-charge (SOC) of the BSS and the production variation of the renewable generators, in particular of wind and photovoltaic technologies, and the variations in the power consumption and energy costs. The proposed EMS uses a master-slave strategy formed by a parallel implementation of the particle swarm optimizer (PPSO) and a multi-period power flow method based on successive approximations (SA), with the aim of achieving the optimal daily operation of the BSS. The objective function selected for the optimization was the reduction of the energy purchasing costs, also including the power balance, devices capabilities and voltage regulation. The effectiveness of the EMS is evaluated in a test system of 21 buses, comparing the solution quality and speed with three optimization techniques published in literature: a black hole optimizer, a continuous genetic algorithm with matrix structure, and a traditional Chu & Beasley genetic algorithm. In addition, two simulation scenarios were used to identify the optimal final SOC conditions for the BSS. Finally, the results show that the proposed EMS provides the best trade-off between quality solution and speed. The simulations are conducted in MATLAB software using sequential quadratic programming.

Optimal Power Flow on DC Microgrids: A Quadratic Convex Approximation

Abstract: This express brief shows a convex quadratic approximation for the optimal power flow (OPF) in direct-current microgrids (dc- ${\mu }$ Grid) via Taylor’s series expansion This approach can be used for solving OPF problems on radial and meshed dc- ${\mu }$ Grids with multiple constant power terminals, allowing to cover a wide range of configurations Two test dc- ${\mu }$ Grids with 10 and 21 nodes were used to validate the proposed model Nonlinear large-scale solvers were employed to compare the proposed linearization with the conventional nonlinear nonconvex model

Differential Equations and Dynamical Systems

Abstract: Series Preface * Preface to the Third Edition * 1 Linear Systems * 2 Nonlinear Systems: Local Theory * 3 Nonlinear Systems: Global Theory * 4 Nonlinear Systems: Bifurcation Theory * References * Index

L2 Gain And Passivity Techniques In Nonlinear Control

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DC Microgrid Planning, Operation, and Control: A Comprehensive Review

Abstract: In recent years, due to the wide utilization of direct current (DC) power sources, such as solar photovoltaic (PV), fuel cells, different DC loads, high-level integration of different energy storage systems such as batteries, supercapacitors, DC microgrids have been gaining more importance. Furthermore, unlike conventional AC systems, DC microgrids do not have issues such as synchronization, harmonics, reactive power control, and frequency control. However, the incorporation of different distributed generators, such as PV, wind, fuel cell, loads, and energy storage devices in the common DC bus complicates the control of DC bus voltage as well as the power-sharing. In order to ensure the secure and safe operation of DC microgrids, different control techniques, such as centralized, decentralized, distributed, multilevel, and hierarchical control, are presented. The optimal planning of DC microgrids has an impact on operation and control algorithms; thus, coordination among them is required. A detailed review of the planning, operation, and control of DC microgrids is missing in the existing literature. Thus, this article documents developments in the planning, operation, and control of DC microgrids covered in research in the past 15 years. DC microgrid planning, operation, and control challenges and opportunities are discussed. Different planning, control, and operation methods are well documented with their advantages and disadvantages to provide an excellent foundation for industry personnel and researchers. Power-sharing and energy management operation, control, and planning issues are summarized for both grid-connected and islanded DC microgrids. Also, key research areas in DC microgrid planning, operation, and control are identified to adopt cutting-edge technologies. This review explicitly helps readers understand existing developments on DC microgrid planning, operation, and control as well as identify the need for additional research in order to further contribute to the topic.

A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities

Abstract: In recent years, smart cities have emerged with energy conservation systems for managing energy in cities as well as buildings. Although many studies on energy conservation systems of smart homes have already been conducted, energy management at the city level is still a challenge due to the various building types and complex infrastructure. Therefore, this paper investigated the research themes on smart homes and cities through a quantitative review and identified barriers to the progression of smart homes to sustainable smart cities through a qualitative review. Based on the results of the holistic framework of each domain (smart home and city) and the techno-functional barriers, this study suggests that the following innovative solutions be suitably applied to advanced energy conservation systems in sustainable smart cities: (i) construction of infrastructure for advanced energy conservation systems, and (ii) adoption of a new strategy for energy trading in distributed energy systems. Especially, to reflect consumer behavior and energy in sustainable smart cities, the following responses to future research challenges according to the “bottom-up approach (smart home level to smart city level)” are proposed: (i) development of real-time energy monitoring, diagnostics and controlling technologies; (ii) application of intelligent energy management technologies; and (iii) implementation of integrated energy network technologies at the city level. This paper is expected to play a leading role as a knowledge-based systematic guide for future research on the implementation of energy conservation systems in sustainable smart cities.