PMPablo Alejandro Mendez-Santos
Pablo Alejandro Mendez-Santos
*This is an algorithmically generated author record based on publicly available information.
Research Subjects
Pablo Alejandro Mendez-Santos has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Jorge Osmani Ordonez-Ordonez
Universidad Politécnica Salesiana
1 shared publication - Luis Fernando Guerrero Vasquez
Universidad Politécnica Salesiana
1 shared publication - Nathalia Alexandra Chacón-Reino
Universidad Politécnica Salesiana
1 shared publication - Paul Andrés Chasi-Pesantez
Universidad Politécnica Salesiana
1 shared publication
Latest Publications
- Open Access
Estimation and Forecasting of the Average Unit Cost of Energy Supply in a Distribution System Using Multiple Linear Regression and ARIMAX Modeling in Ecuador
The accurate estimation of electricity supply costs has become increasingly relevant due to growing demand, variable generation sources, and regulatory changes in emerging power systems. This study models the average unit cost of electricity supply (USD/kWh) in Ecuador using multiple linear regression techniques and ARIMAX forecasting, based on monthly data from 2018 to 2024. The regression models incorporate variables such as energy demand, generation mix, transmission costs, and regulatory indices. To enhance model robustness, we apply three variable selection strategies: correlation analysis, PCA, and expert-driven selection. Results show that all models explain over 70% of price variability, with the highest-performing regression model achieving . ARIMAX models were subsequently implemented using regression-based forecasts as exogenous inputs. The ARIMAX model based on highly correlated variables achieved a MAPE below 5%, showing high predictive accuracy. These findings support the use of hybrid statistical models for informed policy-making, tariff planning, and operational cost forecasting in structurally constrained energy markets.Open AccessEstimation and Forecasting of the Average Unit Cost of Energy Supply in a Distribution System Using Multiple Linear Regression and ARIMAX Modeling in Ecuador
The accurate estimation of electricity supply costs has become increasingly relevant due to growing demand, variable generation sources, and regulatory changes in emerging power systems. This study models the average unit cost of electricity supply (USD/kWh) in Ecuador using multiple linear regression techniques and ARIMAX forecasting, based on monthly data from 2018 to 2024. The regression models incorporate variables such as energy demand, generation mix, transmission costs, and regulatory indices. To enhance model robustness, we apply three variable selection strategies: correlation analysis, PCA, and expert-driven selection. Results show that all models explain over 70% of price variability, with the highest-performing regression model achieving . ARIMAX models were subsequently implemented using regression-based forecasts as exogenous inputs. The ARIMAX model based on highly correlated variables achieved a MAPE below 5%, showing high predictive accuracy. These findings support the use of hybrid statistical models for informed policy-making, tariff planning, and operational cost forecasting in structurally constrained energy markets.