Short-Term Demand Forecast Using Fourier Series

Cruz, Laura M.; Álvarez, David; Rivera, Sergio; Herrera, Fernando A.

doi:10.1109/pepqa.2019.8851533

Cited by 8 publications

(7 citation statements)

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“…These are considered as the days with a higher difference in the load patterns. The load profiles were approximated using Fourier series, such as addressed in [23]. The loading of the transformers and lines as well as the voltages of the buses were computed using the pandapower tool [24] by running load flows at each hour.…”

Section: System Descriptionmentioning

confidence: 99%

Optimal Decision Making in Electrical Systems Using an Asset Risk Management Framework

et al. 2021

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In this paper, a methodology for optimal decision making for electrical systems is addressed. This methodology seeks to identify and to prioritize the replacement and maintenance of a power asset fleet optimizing the return of investment. It fulfills this objective by considering the risk index, the replacement and maintenance costs, and the company revenue. The risk index is estimated and predicted for each asset using both its condition records and by evaluating the consequence of its failure. The condition is quantified as the probability of failure of the asset, and the consequence is determined by the impact of the asset failure on the whole system. Failure probability is estimated using the health index as scoring of asset condition. The consequence is evaluated considering a failure impact on the objectives of reliability (energy not supplied -ENS), environment, legality, and finance using Monte Carlo simulations for an assumed period of planning. Finally, the methodology was implemented in an open-source library called PywerAPM for assessing optimal decisions, where the proposed mathematical optimization problem is solved. As a benchmark, the power transformer fleet of the New England IEEE 39 Bus System was used. Condition records were provided by a local utility to compute the health index of each transformer. Subsequently, a Monte Carlo contingency simulation was performed to estimate the energy not supplied for a period of analysis of 10 years. As a result, the fleet is ranked according to risk index, and the optimal replacement and maintenance are estimated for the entire fleet.

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Section: System Descriptionmentioning

confidence: 99%

Optimal Decision Making in Electrical Systems Using an Asset Risk Management Framework

et al. 2021

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“…On the one hand, the procedure begins with net data input to model the system in order to run load flows. On the other hand, load values are estimated by fitting historical data through Fourier series [33]. Using network and load forecasting model, contingencies are simulated disconnecting assets and running load flows to estimate both overloads and voltages outside the security margins.…”

Section: Proposed Procedures For Load Shedding Optimizationmentioning

confidence: 99%

“…To summarize, Figure 2 shows the proposed algorithm for load curtailment optimization considering the operating security margins, where t k is the hour to assess and x k is the vector with the load factor to cut off. load_forecast ← Fourier_Fit(t k , Day) [33] 3:…”

Section: Proposed Procedures For Load Shedding Optimizationmentioning

confidence: 99%

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Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks

et al. 2020

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Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curtailment optimization problem. Best performances regarding optimal value and processing time were obtained using a PSO algorithm, qualifying the technique as the most appropriate for this study. To assess the methodology, the CIGRE MV distribution network benchmark was used, assuming dynamic load profiles during an entire week. Results show that it is possible to determine the optimal unattended power of the system. This way, improvements in the minimization of the expected energy not supplied (ENS) as well as the System Average Interruption Frequency Index (SAIDI) at specific hours of the day were made.

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“…In recent years, LA countries have contributed novel proposals in Demand Side Management, forecasting models, and theoretical studies for forecasting optimization (Cruz, Alvarez, Al-Sumaiti, & Rivera, 2020;Cruz, Alvarez, Rivera, & Herrera, 2019;Diaz, Vuelvas, Ruiz, & Patino, 2019;Garcia-Guarin et al, 2019;J. Garcia, Alvarez, & Rivera, 2020; J. R. Garcia, Zambrano P, & Duarte, 2018;Henríquez & Kristjanpoller, 2019;Hernandez & Baeza, 2019;Jiménez, Pertuz, Quintero, & Montaña, 2019;Marrero, García-Santander, Carrizo, & Ulloa, 2019;Moret, Babonneau, Bierlaire, & Maréchal, 2020;Paredes, Vargas, & Maldonado, 2020;Ramirez, Cruz, & Gutierrez, 2019;Rocha, Silvestre, Celeste, Coura, & Rigo, 2018;Romero-Quete & Canizares, 2019;Sanhueza & Freitas, 2018;Zavadzki, Kleina, Drozda, & Marques, 2020;Zuniga-Garcia, Santamaría-Bonfil, Arroyo-Figueroa, & Batres, 2019).…”

Section: Smart Buildings Forecasting Techniquesmentioning

confidence: 99%

Mejoras al desempeño energético en edificaciones abordando los desafíos actuales del demand-side: Una revisión de contribuciones de Latinoamérica

2020

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Debido a la actual crisis energética mundial y como resultado de los acuerdos de las naciones participantes, se han establecido medidas por las Naciones Unidas para superar los desafíos relacionados. A pesar de los esfuerzos para incluir a los países subdesarrollados en dicho proceso de decisión, la mayoría de las contribuciones continúan estando inclinadas al hemisferio norte. Así, este trabajo se enfoca en destacar los esfuerzos realizados por los países Latinoamericanos (LA), entre 2018-2020, para contribuir específicamente en las mejoras en el desempeño energético en edificaciones para abordar los desafíos actuales del lado de la demanda. Dichos desafíos están relacionados con la gestión de la demanda: (i) picos de demanda no controlados y (ii) capacidad de transmisión y distribución insuficiente en la red eléctrica. Las contribuciones de LA se clasifican en independientes, colaboración y aplicación. Los estudios también se clasificaron en teóricos, experimentales, ambos y revisiones. La metodología de filtrado de dos etapas implementada dio como resultado un total de 176 documentos como lista inicial. Al centrarse sólo en los aspectos relacionados con los ocupantes, las soluciones pasivas y de bajo consumo y las técnicas de previsión para edificios inteligentes, la lista procesada dio como resultado un total de 73 estudios. Los resultados mostraron que los esfuerzos realizados por los países LA residen en su mayoría en la implementación de estrategias previamente desarrolladas y propuestas por países desarrollados, para realizar estudios de caso como independiente o en colaboración. Finalmente, se presenta un análisis FODA para analizar más los resultados.

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Short-Term Demand Forecast Using Fourier Series

Cited by 8 publications

References 8 publications

Optimal Decision Making in Electrical Systems Using an Asset Risk Management Framework

Optimal Decision Making in Electrical Systems Using an Asset Risk Management Framework

Load Curtailment Optimization Using the PSO Algorithm for Enhancing the Reliability of Distribution Networks

Mejoras al desempeño energético en edificaciones abordando los desafíos actuales del demand-side: Una revisión de contribuciones de Latinoamérica

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