Browsing by Author "Sacaan, Rafael"

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    Discrete optimization via simulation to determine reliable network investments
    (IEEE, 2017) Lagos, T.; Ordóñez, F.; Sacaan, Rafael; Rudnick Van de Wyngard, Hugh; Navarro-Espinosa, A.; Moreno, R.
    Solving optimization problems in power systems planning often imposes a compromise between the accurate representation of the power system operation and the simplifications made in the mathematical methodologies used to find the optimal solution. Hence, classic heuristic algorithms go deep modelling operational details without having a clear message about the quality of the solution, whereas mathematical programming approaches find the optimal solution by (significantly) simplifying system operation. In this vein, this article proposes the utilization of Discrete Optimization via Simulation algorithms to solve optimization problems when a detailed representation of the system and information about the quality of the solution are required. In particular, the Industrial Strength COMPASS algorithm is applied to find the optimal set of new transmission lines that maximizes power system reliability given a certain budget and considering a detailed power system model, where a full unit commitment with network constraints and an hourly sequential Monte Carlo are implemented.
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    Identifying Optimal Portfolios of Resilient Network Investments Against Natural Hazards, With Applications to Earthquakes
    (IEEE, 2020) Lagos, Tomás; Moreno, Rodrigo; Navarro Espinosa, Alejandro Andrés; Panteli, Mathaios; Sacaan, Rafael; Ordonez, Fernando; Rudnick van de Wyngard, Hugh; Mancarella, Pierluigi
    Although extreme natural disasters have occurred all over the world throughout history, power systems planners do not usually recognize them within network investment methodologies. Moreover, planners had historically focused on reliability approaches based on average (rather than risk) performance indicators, undermining the effects of high impact and low probability events on investment decisions. To move towards a resilience centred approach, we propose a practical framework that can be used to identify network investments that offer the highest level of hedge against risks caused by natural hazards. In a first level, our framework proposes network enhancements and, in a second level, uses a simulation to evaluate the resilience level improvements associated with the network investment propositions. The simulator includes 4 phases: threat characterization, vulnerability of systems components, system response, and system restoration, which are simulated in a sequential Monte Carlo fashion. We use this modeling framework to find optimal portfolio solutions for resilient network enhancements. Through several case studies with applications to earthquakes, we distinguish the fundamental differences between reliability- and resilience-driven enhancements, and demonstrate the advantages of combining transmission investments with installation of backup distributed generation.
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    Improving power system reliability through optimization via simulation
    (IEEE, 2017) Sacaan, Rafael; Rudnick Van de Wyngard, Hugh; Lagos, Tomás; Ordóñez, Fernando; Navarro Espinosa, Alejandro; Moreno, Rodrigo
    Due to the stochastic nature of equipment failures, the accurate assessment of power system reliability is a complex task. Consequently, the optimal selection of new network infrastructure to improve reliability is even harder. In this paper, an optimization via simulation approach is proposed to find the optimal set of network assets to improve system reliability. Particularly, an Industrial Strength COMPASS algorithm is implemented to find the optimal set of new transmission lines that maximizes system reliability subject to a budget constraint. This algorithm iteratively proposes, in a first stage, a set of new transmission lines that are then tested, in a second stage, via simulation of the system operation, including impact of various network failures. In the second stage, the sequence day-ahead unit commitment plus real-time operation is modeled along with a sequential Monte Carlo simulation to determine highly detailed system operation under network outages and thus calculate the associated expected energy not supplied.
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    Seismic resilience assessment and adaptation of the Northern Chilean power system
    (IEEE, 2017) Espinoza Lara, Sebastián Andres; Poulos Campbell, Alan John; Rudnick Van de Wyngard, Hugh; Llera Martin, Juan Carlos de la; Panteli, Mathaios; Mancarella, Pierluigi; Sacaan, Rafael; Navarro, Alejandro; Moreno, Rodrigo
    Even though the concept of resilience is becoming widely used in electric power systems, there is no consensus on how to systematically model or quantify it. This article begins by proposing a classification for different types of system risk analyses, associating them to the concept of power systems resilience. Thereafter, it describes and applies a resilience assessment and adaptation framework to the Northern Chilean electric power system in the context of its exposure to seismic events. This time-dependent analysis is evaluated throughout the disaster's impact and the network's operation and restoration timeframes with two indices: Energy not Supplied and Energy Index of Unreliability. Finally, the article compares a base case with three resilience adaptation strategies, namely, robust, redundant and responsive cases, in terms of their expected energy annual loss and the return period of different levels of network performance.