• Energy Research

[EN] Many governments are pushing for cleaner transportation. In particular, public transportation allows massive transportation of passengers, but it remains highly polluting, especially in high elevation cities. Thus, the progressive introduction of electric buses (EBS) will allow mitigating these environmental concerns. However, some technological problems must be addressed considering the massive penetration of EBs. The lack of flexibility and the time connection of scheduling for public transit make EBS harder than internal combustion ones. This work studies the impact of charging EBs at the bus station and suggests a new way to take EB aggregators into account to reduce energy costs while fulfilling grid restrictions. In addition, to find a different number of charging spots to be installed, a scheduling analysis is conducted. This works belongs to the projects IEA.JCG.20.01 and SIS.MGR.21.01 from Universidad de las Americas - Ecuador. The authors would like to thank Paulo Guerra-Teran from Universidad de las Americas - Ecuador for the fruitful discussion.

Industries in different sectors are addressing the emission reductions of their processes. Several energy efficiency proposals have been developed by researchers. However, the complexity of most industrial sectors makes it difficult for modelers, businesses, and policymakers to appreciate and realize the full potential for efficiency-driven energy savings in specific industries. Thus, this paper studies the energy efficiency potentials within a vehicle store in Quito, Ecuador. Data on power consumption, operating hours, and consumption were recorded for each inventory item. The workshop was identified as a problem area when the data were analyzed by agency action areas. It is the part of the company with the most machinery and the most operational hours. Finally, proposals for energy efficiency were developed and examined using the internal rate of return and net present value. The proposals with the best applicability were specified using these two indications, resulting in the changing of lights, the use of a timer for the compressor, and the reduction of pump usage time, and lastly, the energy performance indicator and the energy use intensity of the building were calculated.

[EN] Islands located far away from the mainland and remote communities depend on isolated microgrids based on diesel fuel, which results in significant environmental and cost issues. This is currently being addressed by integrating renewable energy sources (RESs). Thus, this paper discusses the generation planning problem in diesel-based island microgrids with RES, considering the electrification of transportation and cooking to reduce their environmental impact, and applied to the communities of Santa Cruz and Baltra in the Galapagos Islands in Ecuador. A baseline model is developed in HOMER for the existing system with diesel generation and RES, while the demand of electric vehicles and induction stoves is calculated from vehicle driving data and cooking habits in the islands, respectively. The integration of these new loads into the island microgrid is studied to determine its costs and environmental impacts, based on diesel cost sensitivity studies to account for its uncertainty. The results demonstrate the economic and environmental benefits of investing in RES for Galapagos' microgrid, to electrify the local transportation and cooking system. J.-M. Clairand would like to thank Universidad de las Americas for funding his visit to the University of Waterloo. The authors would like to thank W. Mendieta, F. Calero, and E. Vera from the University of Waterloo for their valuable comments and helpful suggestions.

Abstract Electric vehicles have attracted increasing interest in recent years owing to their reduced environmental impact. This is particularly so in the case of vehicles for public transportation, such as buses. However, the transition from internal combustion engine buses to electric buses (EBs) is accompanied by new challenges for the power grid, particularly in developed countries. This paper proposes a new methodology to address the transition of urban public transportation from conventional buses to EBs by route prioritization. The scores of each criterion are weighted using a multi-criteria technique. The case study of Cuenca, Ecuador, which is an intermediate Andean city, is considered. The results indicate that the proposed methodology enables the establishment of route prioritization for the transition toward electric mobility. The replacement to EBs of the three best-performing bus lines (50 buses) avoids using 1328 gallons of diesel each day and, thereby, over 13.3 metric tons of CO2 and other polluting gases into the atmosphere. The economic savings reach 83% with respect the diesel consumption. The methodology is suitable for aiding municipalities in identifying adequate bus lines to start this shift. Its application is feasible in any city since it requires as input data: the technical characteristics of electric and combustion buses, operational details of existing routes, and the number of passengers per route. Furthermore, this tool provides a means to calculate the present fuel costs, emission of CO2 for each bus line, and the estimated electricity costs.

As power generation systems with increasingly higher capacities are interconnected with distribution networks, a pressing need arises for a thorough analysis of their integration and the subsequent impacts on medium-voltage lines. This study conducts a comprehensive evaluation, encompassing both steady-state and transient behaviours, leading to a holistic assessment of a real-world biogas generation system integrated into a medium-voltage network. Although the methodology does not introduce revolutionary concepts, its detailed application on a real feeder under various operating conditions adds practical value to the existing body of knowledge. The methodology explores various aspects, including voltage profiles, load capacity, power losses, short-circuit currents, and protection coordination in steady-state conditions. Additionally, a transient analysis is performed to examine the system’s response under fault conditions. This systematic approach provides a deep understanding of the system’s behaviour across diverse operational scenarios, enriching the field with practical insights. The key contributions of this study include identifying the effects of distributed generation systems (DGSs) on short-circuit currents, protection coordination, and defining voltage levels that briefly exceed the CBEMA quality curve. The benefits of incorporating a generation system into a distribution network are discussed from various technical perspectives. In a peak demand scenario, with a 1.72 MW generation capacity, the phase current experiences a notable reduction of 35.78%. Concurrently, the minimum peak demand voltage increases from 12.62 to 12.83 kV compared to a nominal voltage of 12.7 kV. Furthermore, the contribution of the generation system to the short-circuit current remains minimal, staying below 4% even under the most adverse conditions. However, our findings reveal that voltage levels exceed the upper limit of the CBEMA quality curve briefly during a single-phase fault with generation, which could potentially damage electronic equipment connected to the grid. Nonetheless, the likelihood of encountering a single-phase grounding fault with zero resistance remains low.

Isolated microgrids, such as islands, rely on fossil fuels for electricity generation and include vehicle fleets, which poses significant environmental challenges. To address this, distributed energy resources based on renewable energy and electric vehicles (EVs) have been deployed in several places. However, they present operational and planning concerns. Hence, the aim of this paper is to propose a two-level microgrid problem. The first problem considers an EV charging strategy that minimizes charging costs and maximizes the renewable energy use. The second level evaluates the impact of this charging strategy on the power generation planning of Santa Cruz Island, Galapagos, Ecuador. This planning model is simulated in HOMER Energy. The results demonstrate the economic and environmental benefits of investing in additional photovoltaic (PV) generation and in the EV charging strategy. Investing in PV and smart charging for EVs could reduce the N P C by 13.58%, but a reduction in the N P C of the EV charging strategy would result in up to 3.12%.

[EN] Demand prediction has been playing an increasingly important role for electricity management, and is fundamental to the corresponding decision-making. Due to the high variability of the increasing electrical load, and of the new renewable energy technologies, power systems are facing technical challenges. Thus, short-term forecasting has crucial utility for generating dispatching commands, managing the spot market, and detecting anomalies. The techniques associated with machine learning are those currently preferred by researchers for making predictions. However, there are concerns regarding limiting the uncertainty of the obtained results. In this work, a statistical methodology with a simple implementation is presented for obtaining a prediction interval with a time horizon of seven days (15-min time steps), thereby limiting the uncertainty. The methodology is based on pattern recognition and inferential statistics. The predictions made differ from those from a classical approach which predicts point values by trying to minimize the error. In this study, 96 intervals of absorbed active power are predicted for each day, one for every 15 min, along with a previously defined probability associated with the real values being within each obtained interval. To validate the effectiveness of the predictions, the results are compared with those from techniques with the best recent results, such as artificial neural network (ANN) long short-term memory (LSTM) models. A case study in Ecuador is analyzed, resulting in a prediction interval coverage probability (PICP) of 81.1% and prediction interval normalized average width (PINAW) of 10.13%, with a confidence interval of 80%.

[EN] The increase in global electricity consumption has made energy efficiency a priority for governments. Consequently, there has been a focus on the efficient integration of a massive penetration of electric vehicles (EVs) into energy markets. This study presents an assessment of various strategies for EV aggregators. In this analysis, the smart charging methodology proposed in a previous study is considered. The smart charging technique employs charging power rate modulation and considers user preferences. To adopt several strategies, this study simulates the effect of these actions in a case study of a distribution system from the city of Quito, Ecuador. Different actions are simulated, and the EV aggregator costs and technical conditions are evaluated. All the authors wish to thank Manuel Alcázar Ortega and José Francisco Carbonell Carretero from Universitat Politècnica de València for their contributions to this paper. We also thank the Ministry of Electricity and Renewable Energy of Ecuador (MEER) and Empresa Eléctrica Quito (EEQ) for providing important information for this study.