U.S. State and Community Energy Policy and Planning

Randolph, John; Masters, Gilbert M.

doi:10.5822/978-1-61091-821-3_18

Cited by 2 publications

(2 citation statements)

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“…23,24 These data permit calculation of the thermal index of construction options using established methods, which involves calculating the R -values for all windows, doors, walls, ceilings/roofs, and floors comprising the building envelope, as well as using blower door test data to calculate infiltration. 25,26 The unimproved South West Asia (SWA) Hut serves as the baseline structure and the model calculates the cost of additional lumber and insulation for improved SWA Huts as well as the cost of specialty panels for SIP Huts.…”

Section: Methodsmentioning

confidence: 99%

Renewable energy and energy storage to offset diesel generators at expeditionary contingency bases

Katalenich

Jacobson

2021

Journal of Defense Modeling & Simulation

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Expeditionary contingency bases (non-permanent, rapidly built, and often remote outposts) for military and non-military applications represent a unique opportunity for renewable energy. Conventional applications rely upon diesel generators to provide electricity. However, the potential exists for renewable energy, improved efficiency, and energy storage to largely offset the diesel consumed by generators. This paper introduces a new methodology for planners to incorporate meteorological data for any location worldwide into a planning tool in order to minimize air pollution and carbon emissions while simultaneously improving the energy security and energy resilience of contingency bases. Benefits of the model apply not just to the military, but also to any organization building an expeditionary base—whether for humanitarian assistance, disaster relief, scientific research, or remote community development. Modeling results demonstrate that contingency bases using energy efficient buildings with batteries, rooftop solar photovoltaics, and vertical axis wind turbines can decrease annual generator diesel consumption by upward of 75% in all major climate zones worldwide, while simultaneously reducing air pollution, carbon emissions, and the risk of combat casualties from resupply missions.

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Section: Methodsmentioning

confidence: 99%

Renewable energy and energy storage to offset diesel generators at expeditionary contingency bases

Katalenich

Jacobson

2021

Journal of Defense Modeling & Simulation

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“…The main influencing factors and their weights of architecture energy consumption are discussed from different perspectives, and some scientific research results have been obtained [ 2 ]. Based on the perspective of thermal engineering, Marty et al conducted a comprehensive analysis of fuel dynamic factors such as architecture area, envelope thermal performance, and heating and cooling equipment systems that affect energy consumption during architecture operation and predicted the changing trend of architecture energy consumption in the short term of the future [ 3 ]. The research results show that in addition to being limited by most climatic conditions and the current status of existing building renovations, the energy consumption load generated by the HVAC system operating under normal operating conditions will fluctuate accordingly due to the dynamic changes in the population composition of users for the building space [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Optimization Method for Energy Saving of Rural Architectures in Hot Summer and Cold Winter Areas Based on Artificial Neural Network

Yong

Liu

Tian

2022

Computational Intelligence and Neuroscience

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With the phased spatial planning of the rural revitalization strategy, the proportion of architecture energy consumption in the overall social energy consumption is also increasing year by year. Considering the hot summer and cold winter areas, the proportion of architecture energy consumption in the total energy consumption is very large. The ecological environment and natural resources have been greatly threatened, and the issue of energy conservation and environmental protection is imminent. Energy consumption prediction and analysis is an important branch of building energy conservation in the field of building technology and science. Aiming at the energy consumption characteristics of rural architectures in areas with hot summer and cold winter, this paper proposes a method for constructing a neural network model. When building a neural network, the dataset is called and the function is applied randomly to training samples. The data are used for simulation tests to analyze the fit between the predicted results and the calculated results. Flexible forecasting of specific target building energy consumption is achieved, which can provide optimization strategies for updating and adjusting architecture energy efficiency design. The experimental analysis benchmark parameters and the output value in the dataset are compared with the target simulation value. The relative error is less than 4%, and the average relative error value (mean) and the root mean square error (RMSE) value are both controlled within 2%. It is proved that the method in this paper can directly reflect the evaluation of energy consumption by the neural network and realize the high-speed conversion of the generalized model to the concrete goal, which has a certain value and research significance.

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U.S. State and Community Energy Policy and Planning

Cited by 2 publications

References 0 publications

Renewable energy and energy storage to offset diesel generators at expeditionary contingency bases

Renewable energy and energy storage to offset diesel generators at expeditionary contingency bases

Optimization Method for Energy Saving of Rural Architectures in Hot Summer and Cold Winter Areas Based on Artificial Neural Network

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