Urban Resilience and Energy Demand in Tropical Climates: A Functional Zoning Approach for Emerging Cities

Abstract

The management of power supply and distribution is becoming increasingly challenging because of the significant increase in energy demand brought on by global population growth. Buildings are estimated to be accountable for 40% of the worldwide use of energy, which underlines how important accurate demand estimation is for the design and construction of electrical infrastructure. In this respect, transmission and distribution network planning must be adjusted to ensure a smooth transition to the National Interconnected System (NIS). A technical and analytical scientific approach to a modern neighbourhood in Ecuador called “the Nuevo Samborondón” case study (NSCS) is laid out in this article. Collecting geo-referenced data, evaluating the current electrical infrastructure, and forecasting energy demand constitute the first stages in this research procedure. The sector’s energy behaviour is accurately modelled using advanced programs such as 3D design software for modelling and drawing urban architecture along with a whole building energy simulation program and geographical information systems (GIS). For the purpose of recreating several operational situations and building the distribution infrastructure while giving priority to the current urban planning, an electrical system model is subsequently developed using power system analysis software at both levels of transmission and distribution. Furthermore, seamless digital substations are suggested as a component of the nation’s electrical infrastructure upgrade to provide redundancy and zero downtime. According to our findings, installing a 69 kV ring is a crucial step in electrifying NSCS and aligning electrical network innovations with urban planning. The system’s capacity to adjust and optimize power distribution would be strengthened provided the algorithms were given the freedom to react dynamically to changes or disruptions brought about by distributed generation sources.

1. Introduction

Urban growth is a crucial factor in the demand for available resources. The increase in global population has attracted interest from researchers and scholars on the tools for case scenarios of residential growth integrating renewables and mitigating sprawl process [1,2]. Population growth is closely linked to the essential resources for human well-being, such as drinking water, food, housing, health, sanitation, education, work, and energy. For example, within 25 years, population and economic growth in non-OECD countries is expected to result in a more than 30% increase in energy demand [3]. Additionally, it has been observed that 40% of global energy consumption comes from buildings [4]. In the Ecuadorian context, urbanization follows a similar trend.

In an important region of Ecuador, the NSCS is an exhaustive response to the increasing commercial, industrial, and urban development. In order to build a new city, currently referred to as the Nuevo Samborondón, the ambitious strategy to develop a Green City was started in 2020 by EDSA [5]. This plan included a land use solution and a zoning strategy. By minimizing current issues and congestion in the area, this sector intends to construct a planned and ordered town that will raise the standard of living for residents. Hospitals and urban developments are already being developed in the area. According to estimations, this sector will accommodate around 20,000 individuals by 2040 [6].

Sub-transmission electrical system planning and design requires an exhaustive understanding of future electrical demand and transmission strategies for growth. The “Transmission Expansion Plan” of Ecuador’s Ministry of Energy and Non-Renewable Natural Resources highlights the importance of adapting transmission and sub-transmission networks to meet present and future energy supply and demand scenarios. Additionally, it highlights the necessity of integrated planning that accounts for the anticipated growth and specific loads that Ecuador’s national electrical systems could gradually incorporate [7].

To optimize urban energy planning, recent studies have proposed replacing traditional political-administrative boundaries with functional geometries that reflect actual patterns of energy proximity, shared infrastructure, and community ties [8,9]. This approach enables more accurate demand estimation, strategic placement of transformers, and the design of resilient electrical corridors aligned with real land use and urban dynamics [8,10]. In doing so, it promotes a more efficient and context-sensitive energy planning process that is better adapted to the functional structure of the territory.

Similar projects that serve as guidelines for the development of 230/69 kV substations have been built in Ecuador. CELEC EP’s development of the Riobamba 230/69/13.8 kV substation in Chimborazo province in the Andeans, which involved both civil work and the substation’s electromechanical assembly, significantly improved the region’s electrical system’s transmission capacity and stability [11]. Similarly, Orquídeas 230/69 kV Substation, which was built as well by CELEC EP, shares similarities to the NSCS. Located also in the Guayas province, Orquídeas aims to increase the region’s transmission and distribution capacity while addressing comparable issues concerning system reliability and demand growth characteristics. As an integral part of a sub-transmission ring, the Orquídeas substation improves communication with other substations and contributes to the stability of the Guayaquil metropolitan, the most important load in the national interconnected electrical system [12]. However, this study supports LAs and stakeholders (e.g., built environment professionals such as planners, architects and civil engineers) to map and model energy demand in sub-city areas in several ways: first, with a flexible building-based framework to estimate the energy demand at different scales, that may not follow the traditional population-based administrative boundaries, and that does not match policy or intervention needs. Second, with a methodology to construct a detailed energy profile for individual and aggregated dwellings at these new geographies, for which data are not always available; therefore, there is a need to convert data from different plugins, e.g., ladybug and Honeybee. Third, to strengthen the available tools that policymakers and city energy planners may need to identify local priority neighbourhoods, to help assess the impact of interventions in these areas.

Several studies have made significant progress in estimating energy demand through tools such as EnergyPlus and OpenStudio, primarily applied to the thermal analysis of buildings in urban environments [13]. Complementarily, platforms like SketchUp have enabled the development of detailed parametric models that accurately represent the geometry, occupancy, and spatial characteristics of buildings [14]. At the territorial level, the use of Geographic Information Systems (GIS), particularly ArcGIS, has proven essential for mapping land use, classifying functional zones, and assessing infrastructure accessibility [10]. Likewise, specialized tools such as PowerFactory, CYME, and DLTCAD have been widely used to simulate the behaviour of electrical networks, calculate load flows, and design sub-transmission line configurations [15,16,17,18]. However, recent literature shows limited integration of these platforms into interoperable and multiscale methodological frameworks, particularly in rapidly urbanizing contexts within tropical regions. Critical gaps remain regarding (i) the estimation of energy demand based on functional territorial geometries rather than administrative boundaries, (ii) the generation of detailed energy profiles in data-scarce areas using three-dimensional parametric modelling and thermal simulation, and (iii) the design of sub-transmission networks adapted to climatic, topographic, and vertical growth conditions, incorporating reserve margins for expansion scenarios.

Given the rapid development of the construction industry, it is important to identify and estimate its energy demands to create methods that guarantee a consistent, effective, and sustainable supply that is consistent with the intended objectives of the National Interconnected System (NIS). In this context, how does the use of specialized software for calculating energy demand contribute to the accuracy and efficiency of transmission network design in expanding areas like NSCS? What is the projected impact of implementing a new transmission network on the NIS?

The goal of this study is to design an electrical transmission network for the NSCS by combining principles of territorial urban planning with the development of new technologies. This will ensure the coverage of future energy demand, optimizing the efficiency and reliability of the electrical system, and mitigating the risk of network collapse due to the projected population and urban growth.

This document is structured as follows: Section 1 introduces the research field and the related literature. Section 2 details the methodology used. Section 3 presents the results obtained. Section 4 analyzes and discusses the findings. Finally, Section 5 highlights the key conclusions.

2. Methodology

The suggested methodology follows a techno-analytical approach and is structured into four stages, as illustrated in Figure 1. First, the preliminary analysis and planning phase identifies the general criteria of the project. Then the demand study and the available resources are ascertained using advanced software tools and geospatial data. In the third phase, the electrical grid design, the key elements of substations, transmission lines, and medium voltage networks are designed. Finally, simulations are conducted to analyse system performance and its integration with the NIS, ensuring an efficient and feasible planning process.

The data used in this study were obtained from a combination of primary and secondary sources. Geospatial data, including land use, road networks, and administrative boundaries, were collected from official municipal databases and processed using ArcGIS Pro. Demographic and urban growth projections were extracted from the Samborondón Development Plan 2021–2035 and complemented with national census data from INEC Ecuador. Building typologies and occupancy patterns were defined based on architectural plans and reference data from recent developments in the region (e.g., Ciudad Celeste, La Puntilla). Energy consumption benchmarks for different building types were derived from regional utility records and validated against standardized profiles in the ASHRAE 90.1 and 189.1 standards.

For the simulation stage, these datasets were used to generate digital models in SketchUp, which were then imported into OpenStudio and EnergyPlus for dynamic thermal and electrical performance analysis. Climatic data inputs were sourced from the ASHRAE 169-2006-1A climate zone classification and weather files specific to the Guayas region. All data were cleaned, normalized, and georeferenced prior to integration into the simulation platforms to ensure consistency and replicability across zones. This multi-source data strategy supports the robustness of the demand projections and allows for accurate modelling of energy behaviour under different urban configurations.

2.1. Case Study

With temperatures ranging from 22 to 30 degrees Celsius, NSCS covers an area of approximately 2300 hectares in southwestern Ecuador, as shown in Figure 2. Under the guidelines of 15-minute cities [19], an urban planning paradigm that considers the temporal dimension into consideration, this development intends to combine housing, services, and spaces for recreation. Through active movement in close proximity to facilities, it combines time, space, and mobility with the objective of creating resilient, sustainable, and liveable communities.

2.2. Preliminary Analysis and Planning Phase

The study considered software such as EnergyPlus, OpenStudio, SketchUp, ArcGIS Pro, PowerFactory DIgSILENT, CYME, and DLTCAD based on their ability to perform high-fidelity, interoperable simulations across thermal, spatial, and electrical domains. EnergyPlus and OpenStudio were chosen due to their compliance with ASHRAE standards and their capacity to simulate detailed building energy performance under varying climate conditions, which is particularly critical in tropical environments with high cooling loads. SketchUp was selected for its compatibility with OpenStudio and its parametric modelling capabilities, which allowed for rapid and accurate reconstruction of diverse building typologies. ArcGIS Pro was employed for its advanced spatial analysis functions, necessary to define functional zones and georeferenced demand distribution beyond administrative boundaries. For electrical network analysis, PowerFactory DIgSILENT was selected due to its widespread use in high-voltage and transmission system studies, especially for load flow and contingency analysis in national grids. CYME was chosen for medium-voltage distribution network modelling and substation planning, given its strong integration with GIS data and flexibility in load assignment. DLTCAD complemented the toolset by enabling detailed sub-transmission line routing and optimization under topographic and infrastructural constraints. The design also complies with national and international rules, namely the National Electrical Code [20], National Regulatory Office standards [21,22,23], and IEEE and IEC guidelines [24,25], to guarantee the quality, safety, and sustainability of the power supply.

An evaluation of the existing substations (Milagro and Dos Cerritos) to identify their backup capacity, interconnection with the 230 kV network to reduce losses along with improve stability, and an impact analysis incorporating contingencies and demand growth into consideration were all elements of the coordination plan that was established to guarantee compatibility with the NIS. Protocols governing operation and monitoring have been developed to maximize the management of electricity flow. This approach secures NSCS’s smooth integration into the national electrical grid, enabling supply stability and operational resilience.

2.3. Demand Study and Available Resources Phase

2.3.1. Identification of Zones

The study area underwent a georeferenced assessment using the ArcGIS Pro 3.2.0 program, identifying zones of interest, which are related to the land use, as illustrated in Figure 3. There are eight zones throughout the area of interest, each having specific infrastructure and urban characteristics, as shown in Figure 2. The distribution of the road network and the location of residential areas were also taken into consideration while planning the electrical grid, ensuring both accessibility and effective infrastructure installation. A number of zones are being identified: Zone 1: This 300-hectare macrozone is a priority zone because it contains a hospital that is essential to the community; Zone 2: These 303 hectares combine residential sectors with commercial and community spaces; Zone 3: The Guayaquil Country Club, a premier sports and recreation complex, occupies most of the 314 hectares; Zone 4: These 345 hectares are exclusive; Zone 5: A logistic packing facility is located within this zone, which spans 364 hectares; Zone 6: This 323-hectare mixed-use property includes a residential neighbourhood and a building facility owned by the builder Geoforce; Zone 7: With an area of 328 hectares, this macrozone is under development, including the construction of the Punta Barranca urbanization, as well as the Bicentennial Park and a shopping centre; Zone 8: Spanning 261 hectares, this zone is of great educational and commercial significance, housing an educational institution and the companies Minutocorp S.A. and Dimaca.

2.3.2. Energy Demand Analysis

Building on the previously defined zones, each area has the potential for future usage expansion; that is, we classified these zones based on different land uses. This classification enables more efficient and realistic urban planning, ensuring that future growth will be consistent with the projected energy consumption.

Parametric design is utilized as objects are defined by a set of constituent parameters. An object could be defined by three parameters, position, orientation and length, all of which may be defined and redefined individually. In general, a computer interface allows intelligent use of these automated processes. EnergyPlus 9.6 [26], OpenStudio 3.4 [27], and SketchUp 2021 [28] enable us to model energy demand projections, incorporating consumption metrics based on real data from adjacent and recently developed urban areas. This process allows for precise estimates of energy consumption, considering thermal factors, climatic conditions, and specific usage patterns of the local area. The method includes: (i) the base template selection. SketchUp was selected due to its compatibility with two-story residential buildings. This choice is based on its adaptability to thermal zoning systems, flexibility in material parameterization, and integration with the ASHRAE 189.1-2009 standard [29], ensuring a structured analysis of energy requirements; (ii) the development of the three-dimensional geometric model was structured into several stages: importing architectural plans, defining levels and spaces, incorporating shading elements, and configuring openings (doors and windows). A differentiated thermal zoning system was established to optimize the simulation: the second level (guest-room—CZ1-3): Represents liveable areas with optimized configurations for thermal comfort, thermal load, and energy efficiency and first Level (staff lounge—CZ1-3): Designed for social and high-occupancy spaces, considering natural ventilation patterns and thermal gain control from equipment; (iii) the definition technical requirements for building materials were placed into effect to ensure that the model would behave realistically in terms of heat. This included exterior walls, roofs, slabs, and openings, all of which had specific orientations and thermal transmittance configurations Meteorological information from the ASHRAE 169-2006-1A standard was also used to adapt the simulation to the local climate [30]. Variables including temperature, humidity, solar radiation, and the prevalent wind patterns are all considered in these data. (iv) The energy analysis using EnergyPlus follows a comprehensive methodology, that includes several variables to evaluate the thermal and energy performance of the zone. The simulation includes monitoring of total electricity consumption (lighting, equipment, and HVAC systems), thermal load due to infiltration and ventilation, average indoor air temperature and estimated hourly occupancy, and the impact of energy efficiency strategies on consumption reduction.

2.4. Electrical Grid Design

In total, four primary feeders supply electricity to the eight zones, each of which is responsible for supplying electricity in two zones. The main substation converts energy from 230 kV to 69 kV, and each zone has its own distribution system, with a secondary substation supplying energy locally. The planning process identified the best locations for feeder routes and electrical poles based on the roadway and access routes in place. Using the data obtained from the electrical demand analysis for the NSCS, simulations were performed using EnergyPlus, OpenStudio, and SketchUp. These simulations were based on the urban development of Ciudad Celeste, allowing for a more accurate estimation of the electrical load in each zone. This facilitates the planning and dimensioning of the electrical infrastructure necessary to ensure an efficient energy supply in the area.

2.4.1. Design of Electrical Substations

To ensure efficiency, security, and scalability in power distribution, the NSCS’s electrical substation design is based on the deployment of digital substations, optimum configuration criteria, and the selection of modern technology. Siemens has interoperability, automation potential, and conformance to IEC 61850 to facilitate integration with various manufacturers, automation, and remote monitoring by enabling standardized communication between protection, control, and monitoring devices within an automated network [31,32].

2.4.2. 69 KV Transmission Line Design

The design of the sub-transmission electrical system for the NSCS, specifically the DLTCAD Transmission Line I, was developed through strategic planning and optimization. This approach enabled the identification of the most efficient routing for the 69 kV ring transmission lines and the distribution feeders supplying the eight zones. The methodology involved a comprehensive analysis of climatic, topographic, and infrastructural data. Historical temperature and precipitation records determine the most appropriate materials, ensuring mechanical resilience and durability. A detailed review of the topography and existing road networks was conducted to prevent interference with urbanized areas and ecologically sensitive zones, facilitating optimal routing decisions. Subsequently, the estimation of electrical demand was performed to align infrastructure development with projected consumption patterns. A baseline load density of 100 kW per hectare was established, resulting in an initial demand estimation of 30 MW per zone under standard conditions.

To enhance the accuracy of the projection, a coincidence factor of 0.7 was applied, reducing the effective demand to 21 MW per zone. This factor accounts for the probability that not all individual loads within a zone will reach their maximum consumption simultaneously. The value of 0.7 was selected based on common practices in sub-transmission system planning and is consistent with technical guidelines used in tropical urban environments with mixed land use. Similar factors are used in studies conducted by utilities such as CNEL and CELEC in Ecuador, as well as in design manuals from IEEE, where values between 0.65 and 0.75 are typically applied depending on diversity levels and building typologies. Additionally, future urban expansion scenarios were considered, accounting for potential vertical growth that could elevate demand to 50 MW per zone. In response, a 30% reserve margin was incorporated into the design to accommodate future increases in consumption. A 30% reserve margin was included in the projected load calculations to ensure the system’s ability to absorb future increases in consumption due to vertical densification, load growth, and technological changes. This value was defined based on Ecuador’s historical load growth rates (averaging 4–5% annually in urban areas) and recommendations from the electrification master plan and utility-level project evaluations. The 30% margin also considers the uncertainty inherent in planning for emerging cities, where user behaviour, electrification levels, and solar integration scenarios can rapidly shift overall demand patterns.

The next phase focused on the development of the 69 kV sub-transmission ring using DLTCAD. The optimization of transmission line routing prioritized minimizing disruptions to urban structures while maximizing system efficiency. The selection of feeder corridors was carefully performed to ensure effective load distribution, taking into consideration factors such as load conditions, distances to substations, and infrastructure constraints. The strategic placement of substations and feeders was a crucial aspect of the design. The locations of transformation substations were selected to minimize both electrical losses and installation costs, enhancing overall system efficiency. Additionally, the allocation of feeders per substation was systematically determined to ensure a balanced and uninterrupted power supply across the zones.

The final part of this phase involved an iterative optimization process for the routing of transmission lines and feeders. Multiple simulations and refinements were conducted within DLTCAD to enhance the performance of the network. Compliance with Ecuadorian electrical safety regulations and transmission standards was verified to guarantee that the proposed infrastructure meets national and international benchmarks for safety, reliability, and sustainability.

2.5. Evaluation and Optimization

2.5.1. Simulation and Technical Analysis

To analyse the NSCS electrical system, CYME 9.1 software was used as the primary tool for network simulation and evaluation. This process was structured into several phases to ensure a comprehensive assessment of system performance and optimization. Substation locations, distribution line characteristics, sector-specific electrical demand, and historical load records were all included in the comprehensive dataset on the current electrical infrastructure. The data came from a previously established geographic database that, each of which is roughly 300 hectares in size with an estimated electricity demand is 21 MW.

At the start, it was proposed that NSCS be supplied by an existing “Dos Cerritos” substation; however, further analysis indicated that this could overload the substation, compromising its future reliability. A new 230/69 kV substation, named was proposed, this substation will be integrated into the national electrical grid and connected to the “Milagro” substation. The system design includes a ring configuration between both substations to enhance operational stability and redundancy.

The one-line diagram of the new substation incorporates four primary feeders, designed to supply the macrozones within the proposed area. Through a detailed load analysis, transformer capacities and protective elements were dimensioned to ensure system security and efficiency. Furthermore, Zone 7′s substation is powered by both Zone 3 substation and Feeder 1, ensuring operational redundancy and increased system reliability. This choice was based on future projections, which indicate that Zone 7 will have higher energy consumption compared to other areas. To assess the electrical network’s performance under typical operating conditions, a load flow analysis was carried out, considering the voltages, currents, and power levels of each system component. Critical locations, such as overloaded components and voltage variations above allowable limits, were found by the simulation. The findings will be used as a basis for suggesting enhancements to the infrastructure, optimizing network operations, and guaranteeing a dependable and effective power source.

2.5.2. Integration Analysis with the NIS

Using DigSILENT PowerFactory 2021 SP2 software, a detailed model of the electrical system was developed, incorporating the country substations, transmission lines, transformers, and the proposed feeders. This model enabled the simulation of various operational scenarios, including power flow analysis and contingency evaluation, optimizing the reliability of the network. To accurately represent system loads, the team chose a static load model due to its practicality in simulation, eliminating the need for additional data required by dynamic models. They also considered demand calculations obtained from EnergyPlus. To further refine the model and ensure a realistic representation, they used ArcGIS to analyze the study area and identify the distribution of residential units, commercial zones, and service centres. This information allowed them to adjust the model to align with the actual distribution of consumers.

3. Results

3.1. Energy Demand

Some of the results indicate a slightly higher-than-average consumption; however, it is important to emphasize that these figures are approximate, as the calculation is based on estimations that consider population growth and supply capacity in each area. This analysis allowed us to obtain a formal estimate of the energy stress in the scenarios that follow.

3.1.1. Hospital Load

Figure 4 shows the modelling of the hospital, according to the conditions of the site where it would be built. Due to this facility’s high electricity demand and importance in the community, its expected yearly energy consumption is 24,692.88 GJ, or 6859.14 MWh, as seen in

Table 1. Results of site and source energy—hospital.

	Total Energy GJ	Energy per Total Building Area MJ/m2	Energy per Conditioned Building Area MJ/m2
Total Site Energy	24,692.88	1100.58	1100.58
Net Site Energy	24,363.87	1085.92	1085.92
Total Source Energy	68,615.78	3058.27	3058.27
Net Source Energy	67,573.84	3011.83	3011.83

. This estimated amount is within an appropriate range whenever a hospital with 200–400 beds and modern facilities and medical equipment is taken into consideration. The region’s temperature is characterized by a warm, humid climate that raises the need for cooling.

3.1.2. High-Rise Apartment Load

Based on calculations derived from the EnergyPlus simulation, the estimated annual energy consumption for the high-rise apartment building (as illustrated in Figure 5) is approximately 3592.27 GJ, which is equivalent to 997.85 MWh, as shown in

Table 2. Results of site and source energy—high-rise apartment.

	Total Energy GJ	Energy per Total Building Area MJ/m2	Energy per Conditioned Building Area MJ/m2
Total Site Energy	3592.27	458.40	508.83
Net Site Energy	3515.03	448.55	497.89
Total Source Energy	9351.18	1193.29	1324.55
Net Source Energy	9106.57	1162.07	1289.90

. This value represents the total site consumption, including lighting systems, electrical equipment, and climate control. The apartment building consists of multiple residential units, each with different occupancy patterns and energy consumption behaviours. Electricity demand is influenced by various factors, such as the use of air conditioning due to the warm and humid climate of the region, artificial lighting required in common areas, and the presence of household appliances in each residential unit. Additionally, the per capita energy consumption in these types of buildings tends to be high due to the concentration of people within a vertically distributed space, which increases thermal loads and cooling requirements. These factors contribute to the total energy demand of the building.

3.1.3. Primary School Load

An approximate yearly consumption of 3739.82 GJ, or 1038.84 MWh, has been estimated by the energy demand study for the primary school building, as shown in Figure 6 and

Table 3. Results of site and source energy—primary school.

	Total Energy GJ	Energy per Total Building Area MJ/m2	Energy per Conditioned Building Area MJ/m2
Total Site Energy	3739.82	544.29	544.29
Net Site Energy	3567.00	519.14	519.14
Total Source Energy	10,756.10	1565.43	1565.43
Net Source Energy	10,208.78	1485.78	1485.78

. This includes energy use in laboratories, classrooms, and recreational spaces. Since educational facilities are typically occupied during the day, their occupancy profiles are very different from those of other types of buildings. Classroom computer equipment, ventilation, and lighting are responsible for most of the energy use. Air conditioning systems are important for preserving thermal comfort in classrooms in warm, humid regions, especially during hot weather.

3.1.4. Load Modelling

The energy demand estimation for houses was conducted considering a standard dwelling with a 500 m² construction area. The results obtained from EnergyPlus are shown in

Table 4. Zones load modelling results.

Zone	Number of Houses	Demand for Home (kW)	Total Demand (MWh/Month)	Total Demand for Home (MW)
1	8720	1.64	10,271.80	14.388
2	8820	1.64	10,362.97	14.520
3	9120	1.64	10,742.08	15.048
4	10,040	1.64	11,818.28	16.536
5	10,600	1.64	12,481.67	17.490
6	11,000	1.64	12,953.70	18.150
7	9160	1.64	10,798.16	15.114
8	7200	1.64	8476.79	11.880

for each zone, including the approximate number of houses projected in the sector. Like previous models, this analysis also incorporated the climatic and geographical conditions of the area of interest.

3.2. Substations

For the residential load and Hospital, an estimated capacity of 40 MVA is considered due to the high demand of the hospital, which requires an uninterrupted power supply, alongside the surrounding residential load. Substations 2, 3, and 4 are all residential loads with an estimated capacity of 25 MVA each, based on population growth projections and average residential consumption. Substations 5 and 6 are all industrial and residential loads with an estimated capacity of 50 MVA, considering the need for a stable energy supply for industries with fluctuating loads. Finally, Substations 7 and 8 are Mixed Loads with an estimated capacity of 35 MVA, balancing residential demand with hospital and commercial consumption.

3.3. 69 kV Ring

According to the load study, the expected total demand for NSCS, considering typical growth, is 168 MW. The necessary transformation capacity rises to 218.4 MW with a 30% reserve. It is suggested that 225 MVA transformers be used at 69 kV, in accordance with Ecuador’s transmission rules. The design, carried out using the Transmission Line design package DLTCAD, identified the optimal route for one of the feeders, ensuring even load distribution, as illustrated in Figure 7. Eight zones, each covering an approximately 300-hectare area, served as the basis for the planned strategy, which was then further divided into residential housing developments of 15 hectares each.

3.4. Integration with the National Transmission Network

3.4.1. Ecuador’s 230 kV Network Modelled in PowerFactory DIgSILENT

The primary substations and transmission lines located throughout the nation are highlighted in Figure 8, which shows the NIS at 230 kV. This diagram shows how existing substations interact within the main grid to guarantee energy transmission over different areas. The connections highlight how important it is to have a solid framework that ensures the power supply’s stability and reliability. The NSCS substation’s future connection is shown below; it will be incorporated into the Milagro substation’s 230 kV busbar. By improving redundancy and facilitating an efficient response to emergencies, this strategic site reinforces the NIS’s ability to satisfy the region’s increasing electricity needs.

3.4.2. Molino-Milagro Zone

Figure 9 provides a detailed view of the Molino-Milagro region, where critical substations and transmission lines distribute energy to the zones. This schematic highlights the existing infrastructure and how the regional system supports the current load in the area. The integration of the NSCS substation in this area will optimize energy flow, reducing the load on existing substations. Additionally, its direct connection to Milagro and Dos Cerritos will enable a balanced and efficient distribution, ensuring the system’s ability to handle the projected increase in demand.

3.4.3. Milagro 230/69 kV Substation

Figure 10 shows a detailed view of the Milagro substation, an essential part of the NIS electrical network. Transformers that reduce voltage from 230 kV to 69 kV are highlighted because they are important to powering substations and local distribution networks. Figure 9 also highlights how the Milagro substation will be the main point of connection for the NSCS substation, supplying a consistent and suitable energy supply to fulfil the growing demand of the macrozones.

3.4.4. Dos Cerritos Substation

The Dos Cerritos subsistence is another essential component of the regional system. Figure 11 shows the 230 kV and 69 kV busbar configurations, as well as the transformers and connection lines that enabled the supply of energy to local networks. Within the project’s parameters, operational redundancy is provided via the ring connecting Dos Cerritos and NSCS. In addition, the suggested transfer busbar guarantees that the system will continue to operate even in the event of faults or emergencies.

3.4.5. Sitting of the Nuevo Samborondón Substation

Figure 12 shows the location of the NSCS substation and its integration with the NIS. It connects directly to the 230 kV busbar at the Milagro substation, improving system stability and redundancy while also increasing transmission capacity to the zones. In addition, a reliable and uninterrupted power supply is ensured by its connection to Dos Cerritos through transfer busbars. This site was chosen with consideration to maximizing operational efficiency and infrastructure costs.

3.4.6. High-Voltage Section of the Nuevo Samborondón Substation

The design of the high-voltage section of the Nuevo Samborondón substation, as seen in Figure 13 includes 230 kV connection equipment, main transformers, and protection devices. This configuration enables the management of large power flows while ensuring system stability. The designed section meets international standards, providing operational flexibility and redundancy in energy transmission to local networks.

3.4.7. Low-Voltage Section of the Nuevo Samborondón Substation

The low-voltage diagram illustrates the 69 kV, as seen in Figure 14, includes feeders for energy distribution to the zones. This section also incorporates secondary transformers and protection devices necessary to ensure system safety. The design ensures that the feeders are optimized to handle projected demands, maintaining supply quality and reducing energy losses.

3.4.8. Modelling of Feeder Loads

Each feeder is designed to supply two zones, ensuring efficient and sufficient distribution. The parameters for each feeder include active and reactive power, power factor, and load scaling. These configurations allow for the evaluation and optimization of system performance across various operational scenarios.

Table 5. Feeders load modelling results.

Feeder	Active Power MW	Power Factor Ind.	Voltage p.u.	Scaling Factor
1	45.19	0.9382855	1	1
2	30.288	0.9416115	1	1
3	32.974	0.9530739	1	1
4	31.314	0.9626101	1	1

shows the load modelling results.

3.4.9. Load Flow

The 230 kV busbars’ operational behaviour under actual and simulated load levels is shown in the load flow of Figure 15 at the Milagro substation. Grid stability is ensured by the recorded voltage values on the busbars staying within a suitable operating range. Furthermore, the transmission lines’ currents are within allowable bounds, ensuring effective operation free from overloading hazards. The active and reactive power flows toward the associated substations, including the upcoming NSCS substation, are also included in the diagram. This flow highlights Milagro’s vital function as a primary node in the regional power system and guarantees dependable energy transfer. The substation’s ability to accommodate the anticipated increase is confirmed by the simulated load circumstances.

The energy distribution to the primary feeders supplying the macrozones is reflected in the load flow at the Nuevo Samborondón substation’s 69 kV busbar. A high-quality power supply is ensured by the voltage levels being within allowed ranges.

The feeders are sized to handle the projected zone loads, guaranteeing service continuity even under high-demand conditions as seen in Figure 15. The analysis also demonstrates effective coordination between protection devices and connection points, minimizing the impact of system faults. The results confirm that the substation can operate efficiently under various load scenarios.

The load flow of Figure 14 shows a balanced input–output power distribution in the NSCS substation’s 230 kV section. Stable voltage levels at the high-voltage busbars guarantee a steady supply to the secondary feeders and distribution networks. The results also show the importance of the ring layout for facilitating load transfer between interconnected substations like Dos Cerritos and Milagro. This operational redundancy maximizes system efficiency and reduces energy losses by ensuring service continuity in the event of emergencies.

4. Discussion

This article has demonstrated that urban planning projections can be used for the efficient design of energy networks, considering current demands and the construction plans of real estate companies in the region. The modelling framework uses a green city design, aiming to avoid conflicting issues with the increase in carbon in the environment. The development of sustainable urban infrastructure and the integration of efficient electrical systems in growing tropical cities represent key challenges in transmission planning in a comprehensive manner.

The use of specialized software for calculating energy demand significantly enhances the accuracy and efficiency of transmission network design in expanding areas like NSCS by integrating real-time data analysis, predictive modelling, and spatial mapping. Tools such as EnergyPlus, OpenStudio, and ArcGIS enable precise estimations of electricity consumption patterns, considering climatic conditions, occupancy behaviours, and urban zoning parameters. These software solutions facilitate dynamic load forecasting, ensuring that infrastructure planning aligns with projected growth while optimizing resource allocation. Additionally, simulations using PowerFactory DIgSILENT provide validation against transmission network behaviour during outage scenarios, reducing the probability of risk related to system overloading and voltage instability. These techniques allow for greater precision in modelling grid behaviour under varying conditions and can also account for uncertainties and variabilities in energy production and consumption, leading to more resilient and scalable solutions for urbanization.

Urbanization in various areas of Ecuador follows global patterns, which represents an increase in energy demand mainly driven by residential and commercial zones. The results indicate that the total projected demand for NSCS is 168 MW. This is a significant figure, which is not oversized for the considered growth, given that the analysis area also represents a high potential for renewable energy (with an emphasis on solar energy) in residences that should be considered over time with the construction to be carried out. The study revealed that high-consumption areas, such as hospitals, educational institutions, shopping centres, and high-rise apartment buildings, require specialized solutions. Therefore, simulations with programs like EnergyPlus and OpenStudio allowed for accurate estimates, reinforcing the importance of urban energy planning based on data. Some of the simulation results indicate energy consumption values that are moderately higher than typical averages. For example, the hospital model showed an annual energy consumption of approximately 6859 MWh, which is about 25–30% higher than the national average for similar-sized facilities. This increase is primarily due to 24/7 operations, high cooling demand in tropical climates, and the presence of specialized medical equipment. Similarly, the high-rise apartment building exhibited a total demand of 997.85 MWh per year, exceeding baseline estimates for residential buildings by 15–20%, largely due to higher occupancy density, increased cooling needs, and continuous use of domestic appliances and lighting. These elevated results are consistent with the projected urban profile of NSCS, which includes dense, service-oriented zones with limited passive cooling. Therefore, the demand values derived from the simulations are not anomalies but reflect the anticipated energy stress that could emerge from the specific spatial and functional configuration of the area. This reinforces the importance of using detailed energy modelling in early planning phases, particularly in rapidly developing tropical cities.

The high energy consumption for high-rise apartment residences indicates the lifestyle of many upper-middle-class consumers who currently dominate the area. Such buildings have high consumption as there are numerous residential units inside, along with the usage of air conditioners, world-class household appliances, and high-performance lighting systems. This factor is also highlighted due to the warm and humid climate of Samborondón, which generates a greater dependence on artificial cooling, increasing the load on electrical systems, especially during peak consumption hours. Meanwhile, the hospital sector also exhibits high energy consumption due to the required medical equipment, constant use of air conditioning, and the need to ensure an uninterrupted energy supply.

The analysis of the results reveals that certain areas within the NSCS exhibit significantly higher energy demands, particularly those containing hospitals, high-rise residential buildings, and industrial facilities. Two zones stand out as critical: Zone 5, which registers the highest projected monthly energy demand in the entire urban area, with 12,481.67 MWh/month and a peak load of 17.49 MW, driven by a high-density residential sector and the presence of a logistics packing facility; and Zone 1, which combines residential load with a high-complexity hospital that alone accounts for an estimated 6859 MWh/year, exceeding national benchmarks for similar facilities by more than 25% due to 24/7 operation, medical equipment loads, and intensive cooling demand. In addition, zones characterized by vertical residential development display elevated energy consumption, caused by high occupant density, internal heat gains, and reliance on air conditioning and artificial lighting. These high-demand profiles underscore the need for differentiated infrastructure design, including higher-capacity transformers, dedicated feeders, and enhanced redundancy schemes. From an urban planning perspective, understanding these consumption patterns is essential to ensure system reliability, prevent overload risks, and allocate resources efficiently in mixed-use developments.

On the other hand, the integration of urban planning principles, such as the 15-min city model, requires urban electrical infrastructure that adapts to a sustainable design. The incorporation of renewable energy sources within the NSCS energy matrix remains a critical aspect that should be further explored. Energy efficiency strategies, including demand-side management (DSM) initiatives, could further reduce peak demand and optimize resource use.

The 15-min city approach, as applied to the development of NSCS, indirectly influences energy consumption patterns, although its impact varies depending on land use types and local climatic conditions. By encouraging proximity between housing, services, employment, and recreation, this urban model tends to reduce the need for motorized transport and promote active mobility solutions, which lowers energy consumption associated with the transport sector. However, the study area’s tropical climate, characterized by high temperatures, creates a strong demand for cooling. As a result, the potential energy savings from reduced travel may be offset—or even exceeded—by the thermal loads of densely occupied buildings. In this context, although the 15-min city design supports more efficient infrastructure distribution and shorter functional distances, its direct impact on overall energy consumption depends on factors such as the thermal performance of buildings, natural ventilation, and the type of lighting systems used. The findings of this study indicate that, without the implementation of additional energy efficiency measures at the building level, the 15-min city model alone does not ensure a significant reduction in total energy consumption, particularly in a region with such demanding climatic conditions.

The study demonstrated that a ring configuration for the 69 kV transmission network improves the system’s resilience and efficiency in energy distribution. Considering this, the main substations are available in Milagros and Dos Cerritos. Likewise, the iterative optimization process in DLTCAD allowed for the identification of the best routes for the 69 kV lines, minimizing interruptions to the existing infrastructure while respecting road areas and ecological zones. The integration of digital substations using IEC 61850 standards [33,34,35,36,37,38,39,40,41] enhances automation and remote monitoring, following methodologies applied by Siemens and aligning with modern trends in smart grid development.

The comparison with similar projects, such as the Orquídeas 230/69 kV substation, highlights the need to design substations capable of handling urban growth without compromising system stability. The approach adopted in NSCS integrates energy-efficient designs and thermal zoning methods, providing a replicable model for other rapidly expanding urban areas.

In terms of energy efficiency, digital substations offer better energy utilization by minimizing losses in transmission and distribution. Likewise, the flexibility and scalability of these substations also play a key role, as their modular design and ability to integrate with new technologies allow adaptations without the need for significant structural changes. Meanwhile, from a security and protection perspective, digital substations ensure operational continuity even in emergency scenarios.

The findings from the PowerFactory simulations indicate that the voltage levels of NSCS in all load scenarios remain stable, ensuring proper alignment with the NIS. Thus, the Milagro substation plays a fundamental role alongside the Dos Cerritos substation, guaranteeing redundancy and mitigating the risks of localized blackouts.

The proposed framework not only addresses technical challenges but also aligns with Ecuador’s national policy instruments, such as the National Development Plan (PND and the National Sustainable Energy Agenda.

The results of this study align closely with Ecuador’s national energy policy framework, particularly the PND 2024–2025 and the National Energy Transition Strategy. For instance, the proposed resilient energy infrastructure planning for the NSCS directly supports Policy 7.1 of the PND, which aims to ensure uninterrupted energy supply through optimal use of renewable resources and strengthening of the distribution system with a focus on efficiency, quality, and resilience [42]. The NSCS model reflects strategic priorities such as distributed generation, integration of renewable sources (especially solar energy), and the incorporation of storage systems to mitigate risks associated with Ecuador’s high reliance on hydropower and vulnerability to prolonged droughts. In addition, the approach adopted in this study responds to recommendations by international institutions such as IRENA, which emphasize the need for stronger alignment between electricity planning, preferential regulatory mechanisms, technology deployment, and regional energy integration. Despite renewable sources comprising over 60% of installed capacity, Ecuador’s power system faces critical challenges due to a lack of diversification and delays in renewable project execution. The NSCS design—with strategic reserve margins, multiscale simulations, and technical planning adapted to scenarios of vertical urban growth—offers a replicable framework that addresses the national deficit of 200 MW of new generation capacity needed annually.

Likewise, it is important to highlight how the results align with the Sustainable Development Goals (SDGs), specifically SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). The study contributes to ensuring access to modern, reliable, and sustainable energy systems by promoting a flexible, simulation-based approach to energy infrastructure planning in tropical urban contexts (SDG 7). The integration of territorial planning principles, such as the 15-min city model, supports the development of compact, efficient, and inclusive urban environments (SDG 11). Furthermore, the emphasis on reducing transmission losses, enabling solar integration, and preparing for demand-side management strategies contributes to national decarbonization efforts, directly supporting climate mitigation objectives (SDG 13). In this way, the methodological framework and policy-oriented findings of this study aim to serve as a valuable reference for integrating sustainable development priorities into local energy and urban planning.

Beyond the local case, the methodology applied to NSCS can serve as a replicable model for other emerging tropical cities facing similar challenges of urban expansion, energy vulnerability, and infrastructure strain. Cities with comparable climatic and demographic conditions, such as Guayaquil, Barranquilla, or Fortaleza, could adapt the planning workflow to design tailored energy solutions that combine functional urban layouts with dynamic energy simulations. In terms of socio-economic benefits, implementing the proposed infrastructure could generate skilled employment in the energy and construction sectors, reduce energy poverty through more efficient systems, and improve quality of life by reducing energy losses and ensuring more reliable access.

5. Conclusions

The development of NSCS represents a strategic integration of energy infrastructure and urban planning to support Ecuador’s ongoing urban expansion. The findings emphasize that data-driven decision-making, advanced simulation tools, and optimized transmission design are essential for ensuring reliability and efficiency in energy distribution. Lessons learned from this study can be applied to other tropical cities facing similar challenges in real estate expansion, infrastructure planning, and carbon urbanization.

Moreover, the implementation of the NSCS substation reinforces the stability of the NIS by ensuring a reliable and resilient power supply. The interconnection with Milagro and Dos Cerritos substations, structured in a ring configuration, enhances redundancy and minimizes the impact of potential faults, securing uninterrupted service for residential, commercial, and industrial users. Additionally, the system’s capacity to accommodate expanding macrozones without compromising efficiency highlights the importance of proactive infrastructure planning. Beyond technical feasibility, the project contributes to the socio-economic development of Samborondón, fostering investment opportunities and aligning with Ecuador’s long-term energy objectives. By integrating strategic urban planning with optimized electrical infrastructure, the NSCS project serves as a model for balancing urban expansion with sustainable energy solutions in rapidly developing regions.

Furthermore, this study demonstrates the benefits and necessities of including a geographic and spatial focus to measure energy demands, identify land use, select optimal feeder routes, consider the region’s topography, and maintain a georeferenced record of the project. Likewise, it should be noted that the analysis does not account for energy demand variations due to specific building characteristics, nor does it consider potential impacts on property valuation [43,44], which are subject to uncertainties and risk perceptions that are difficult to model in the early planning stages.

Finally, while the study confirms that the proposed substation and 69 kV transmission network can meet projected demand, future research should focus on enhancing renewable integration, DSM strategies, and AI-driven load forecasting. In this regard, it is recommended to conduct simulations of solar generation potential at both the building and urban zone levels, complemented by analyses of energy storage requirements that account for daily and seasonal demand variations. For DSM strategies, it would be appropriate to apply user behaviour modelling, evaluate load-shifting potential, and incorporate technologies such as smart meters and time-of-use tariffs. Regarding demand forecasting, it is relevant to explore the use of advanced AI algorithms, including Long Short-Term Memory (LSTM) neural networks, gradient boosting techniques, and both supervised and unsupervised learning approaches, which can enhance the accuracy of load estimation based on historical consumption data, climatic conditions, and occupancy patterns. Therefore, the ability to anticipate urban energy needs and design resilient systems will be key to achieving sustainable and scalable urban growth in Ecuador and beyond.