Towards A Definition For Zero Energy Districts In Panama: A Numerical Assessment Of Passive And Active Strategies

León, Lissette De; Cedeño, Miguel; Mora, Dafni; Austin, Miguel Chen

doi:10.18687/laccei2021.1.1.333

Cited by 5 publications

(3 citation statements)

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“…They proposed passive design measures and distributed power generation to achieve the zero energy target and demonstrated that passive design is a fundamental prerequisite for reducing building energy demand. De León et al [107] provided a solution for achieving zero energy targets in a residential district under a tropical climate in Panama. They reduced energy consumption through the optimization of bioclimatic and energy strategies, achieving savings of 31%, with the remaining demand met through the generation of solar electricity.…”

Section: Zero Energy Communities Of Buildings (Zecs)mentioning

confidence: 99%

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Chen,

Vand,

Baldi

2024

Buildings

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Achieving climate neutrality requires reducing energy consumption and CO2 emissions in the building sector, which has prompted increasing attention towards nearly zero energy, zero energy, and positive energy communities of buildings; there is a need to determine how individual buildings up to communities of buildings can become more energy efficient. This study addresses the scientific problem of optimizing energy efficiency strategies in building areas and identifies gaps in existing theories related to passive design strategies, active energy systems, and renewable energy integration. This study delineates boundaries at the building and community scales to examine the challenges of attaining energy efficiency goals and to emphasize the intricate processes of selecting, integrating, and optimizing energy systems in buildings. The four boundaries describe: (B1) energy flows through the building envelope; (B2) energy flows through heating, ventilation, air conditioning and energy systems; (B3) energy flows through individual buildings; (B4) energy flows through a community of buildings. Current theories often treat these elements in isolation, and significant gaps exist in interdisciplinary integration, scalable frameworks, and the consideration of behavioral and socioeconomic factors. Achieving nearly zero energy, zero energy, and positive energy communities requires seamless integration of renewable energy sources, energy storage systems, and energy management systems. The proposed boundaries B1–B4 can help not only in analyzing the various challenges for achieving high energy efficiency in building communities but also in defining and evaluating these communities and establishing fair methods for energy distribution within them. The results demonstrate that these boundaries provide a comprehensive framework for energy-efficient designs, constructions, and operational practices across multiple buildings, ensuring equitable energy distribution and optimized performance. In addition, the definition of boundaries as B1-B4 contributes to providing an interface for energy-efficient designs, constructions and operational practices across multiple buildings.

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Section: Zero Energy Communities Of Buildings (Zecs)mentioning

confidence: 99%

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Chen,

Vand,

Baldi

2024

Buildings

View full text Add to dashboard Cite

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“…The method used in the optimization analysis is based on the genetic algorithms (GAs). A GA allows identifying the adequate configurations, applying an iterative generational analysis process, including the following steps: encoding variables and design options, random generation of an initial population, file generation, simulation in EnergyPlus of the first solutions and analysis of results, classification of solutions, selection of "parents" (tournament), crossover and mutation, EnergyPlus simulation, the union of parents and offspring, repetition of the process, the established number of iterations, and finally the analysis of the best solutions shown on the Pareto front [28]. The settings applied were: maximum generations of 100, generation for convergence of 5, an initial population of 20, optimization Engine JEA [29], generation population size of 20, maximum population size of 10,000, and mutation rate of 0.40.…”

Section: Evaluation Of Different Building Envelope Layoutsmentioning

confidence: 99%

Numerical Assessment of Different Phase Change Materials as a Passive Strategy to Reduce Energy Consumption in Buildings under Tropical Climates

2022

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The building envelope design constrains how much HVAC systems must work to provide comfort. High thermal mass in walls is preferable to delay heat gain, as well as reduce it. Phase Change Materials (PCMs) seem to proportionate more thermal mass without increasing wall thickness because of their high latent heat. Thus, this work studies various PCM-based envelope layouts in four case studies, H060, H100, H200, and OB, under the tropical climate of Panama City, via building energy performance simulation. Energy and thermal comfort performance were used as criteria to determine an optimal PCM-based layout for such a climate through optimization analysis and to compare PCM-based and non-PCM-based envelope layouts. Results showed that among the considered combinations, PCM-based roof configurations provide more optimum solutions than PCM-based wall configurations. The PCM layout with a melting temperature of 27 °C allowed completion of the PCM cycle throughout the year. Although other PCM layouts did not present a complete charge/discharge cycle, such as the most frequent options at H060, H100, and H200, it suggests that PCM on liquid or solid phase provides better thermal performance than other considered combinations.

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“…It can be considered that the consumption per use of the equipment is similar in both models. (16). It should be noted that the representative houses were used in terms of behavior and consumption to perform the sensitivity and optimization analyses; minor characteristics of the fewer representative houses, which may influence the results, have been excluded.…”

Section: Multi-objective Optimization Approachmentioning

confidence: 99%

Decision-Making Approach based on Multi-objective Optimization to Achieve Net-Zero Energy Neighborhoods through Retrofit in a Tropical Climate

Chung-Camargo

Chacón

Austin

et al. 2022

J. Phys.: Conf. Ser.

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Among the main causes of environmental deterioration worldwide, buildings are among those responsible for a large percentage of energy-related CO2 emissions. Because of this, finding solutions to this problem is necessary. This research project involves building the energy model of a neighbourhood located in Panama, Herrera province. The main elements were classified and systematized using DesignBuilder and then implemented in an optimization analysis that seeks to approximate the NZED standard. The optimization’s main objectives were to maintain or improve thermal comfort, reducing energy consumption to the lowest possible. The best design options were those given by the method of essential design variables determined in the sensitivity analysis. It was possible to conclude that combining changes in occupant behavior with specific changes in the envelope leads to a more efficient reduction in electricity consumption. Because they lead to a significant reduction in consumption without involving the cost of the total modification of the envelope, with these modifications, a reduction in electricity consumption of 52,852 kWh/year was obtained at a renovation cost of B/.19,890.00 with a recovery period of seven years.

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Towards A Definition For Zero Energy Districts In Panama: A Numerical Assessment Of Passive And Active Strategies

Cited by 5 publications

References 0 publications

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Challenges and Strategies for Achieving High Energy Efficiency in Building Districts

Numerical Assessment of Different Phase Change Materials as a Passive Strategy to Reduce Energy Consumption in Buildings under Tropical Climates

Decision-Making Approach based on Multi-objective Optimization to Achieve Net-Zero Energy Neighborhoods through Retrofit in a Tropical Climate

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