Browsing by Author "Morquecho Salto, Edgar Gonzalo"

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AC transmission network expansion planning considering losses
(Institute of Electrical and Electronics Engineers Inc., 2018) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Espinoza Abad, Juan Leonardo; Lopez Quizhpi, Julio César; Quizhpe Huiracocha, Klever Leonardo; Sempertegui Álvarez, Rodrigo Efraín; Solano Quinde, Lizandro Damián; Espinoza Abad, Juan Leonardo
This paper proposes to solve the transmission network expansion planning problem (TNEP) using the AC model formulated with full non-linear load flow equations, incorporating the cost of losses in the transmission network. Additionally, the decomposed formulation finds the location and amount of the reactive compensation needed in the system. A comparison between Evolutionary Programming (EP) and a variation of EP with a Cultural Algorithm (CEP) is presented to solve this very complex optimization problem. The results are obtained using Garver's 6-bus test system and IEEE 24-bus test system. Index Terms-AC model, Cultural Algorithm, Evolutionary Programming, Optimization, Transmission network expansion planning.
An efficient hybrid metaheuristics optimization technique applied to the AC electric transmission network expansion planning
(2021) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Castro, Carlos A.
The transmission network expansion planning (TNEP) problem consists of determining the necessary infrastructure additions, within a planning horizon, to minimize an investment objective function while meeting some operational and physical constraints. Even using simplified models to represent the electric network, the TNEP becomes a very complex, combinatorial and non-convex optimization problem. In recent years, the full alternating current (AC) network model has been proposed to formulate the TNEP problem. Due to its complexity, more robust and efficient optimization techniques to solve the AC formulation are required. This paper proposes a new effcient hybrid metaheuristic technique to solve the TNEP problem. Additionally, it presents a comprehensive comparative study including different powerful conventional, emerging and hybrid optimization metaheuristics techniques applied to solve the static, long-term TNEP problem, using the AC model, considering both operating and reactive power compensation costs. Simulation results are shown for three test systems: Garver 6-bus system, IEEE 24-bus system and the IEEE 118-bus system.
Comparison of an Improved Metaheuristic and Mathematical Optimization Based Methods to Solve the Static AC TNEP Problem
(2023) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Astudillo Salinas, Darwin Fabián
The complexity of current and future electricity networks demands the use of more accurate models to solve the Transmission Network Expansion Planning (TNEP) problem. To deal with this issue, formulations based on AC network equations have been proposed by the research community. Although the AC formulations exist, they do not work with problems with a large number of candidate transmission paths, different planning scenarios due to convergence issues or infeasible solutions. Also, it has been difficult for the power system community to be aware of the real advantages and disadvantages of the existing approaches due to the lack of rigorous and fair comparisons among them. In this research work, a full non-convex AC formulation to solve the TNEP problem is proposed. It considers in an integrated fashion reactive power expansion, the contingency criterion and operational costs. The formulation is solved by an improved non-convex optimization algorithm in a two-stage approach. Also, a fair and rigorous quantitative and qualitative comparison among the proposed approach and other state-of-art metaheuristics and mathematical programming methods has been performed. Simulation results show that the proposed formulation and solution method are superior to other approaches with respect to reliability and suitability for cases with large search spaces and different scenarios. Results are shown for four test systems, namely the Garver 6-bus system, the IEEE 24-bus system, the IEEE 118-bus system, and a modified version of the IEEE 300-bus system. IEEE
Planeamiento de la expansión de sistemas de transmisión usando el modelo AC y algoritmos de estimación de distribución
(2017) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio
The Transmission Network Expansion Planning (TNEP) problem consists of determine the transmission network to be built to meet the future demand requirements for a long-term scenario, minimizing the cost of investment and meeting the technical criteria of the network. This research work thesis presents a methodology and a mathematical model to solve the long-term static Transmission Network Expansion Planning. The AC model with non-linear load flow equations is used to represent the transmission network, which represent a non-linear, mixed-integer problem (MINLP), combinatorial and non-convex problem to solve the TNEP. The objective function to be minimized allows to include both the cost per investment and the cost associated per active power losses. The Estimation of Distribution Algorithms (EDAs) are used as optimization technique to solve the TNEP. These algorithms are meta-heuristic techniques that base its search on generate a probabilistic model of the promising solutions to generate the next population. The proposed algorithms are tested on Garver 6-node systems and on the IEEE 24-node system.
Security constrained AC dynamic transmission expansion planning considering reactive power requirements
(2023) Astudillo Salinas, Darwin Fabián; Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio
The Transmission Network Expansion Planning problem (TNEP) can be modeled either as a static, a pseudo-dynamic, or a dynamic problem. Most of the existing formulations do not include reactive power planning within the TNEP problem, leading to sub-optimal designs leading to higher system costs in reality. This paper proposes a dynamic (multi-stage) non-convex formulation that optimizes the addition of transmission circuits and reactive power compensation devices, accounting for operational costs including losses. The planning is done considering security constraints using an AC model. As there are no similar research works to benchmark the outcomes, the results were compared with those obtained from the static and pseudo-dynamic approaches, showing that the proposed approach provides more economical solutions. It is also shown that better solutions are obtained when Reactive Power Planning (RPP) is considered in the problem formulation. An improved Differential Evolution (DE) and Continuous Population Based Incremental Learning (PBILc) hybrid solution method (IDE-PBILc) is proposed which drastically improves calculation time and robustness. Comparisons with two different state-of-the-art metaheuristics are performed for validation. The results were obtained for the Garver 6-bus, IEEE 24-bus, and the IEEE 118-bus systems. Even though in this work uncertainties are not considered, the proposed approach could be of particular use when studying systems with high renewable energy penetration scenarios, due to its computational efficiency.