scispace - formally typeset
Search or ask a question

What is the energy consumption pattern for office buildings? 


Best insight from top research papers

The energy consumption pattern for office buildings is influenced by various factors such as meteorological parameters, human-driven behaviors, and building operations. Studies have shown that energy demand in office buildings correlates positively with irradiation and temperature, and negatively with humidity . Additionally, human factors play a significant role in energy consumption patterns, with adjustments in occupants' behaviors potentially leading to energy savings of 9% to 18% without complex technology interfaces or building upgrades . Furthermore, real-time data collection and analysis can help establish energy consumption models, identify energy consumption patterns, and detect outliers to achieve energy-saving goals in green office buildings. Understanding these patterns is crucial for developing effective strategies to reduce energy consumption and achieve sustainability goals in the building sector.

Answers from top 4 papers

More filters
Papers (4)Insight
Energy consumption patterns in office buildings can be adjusted by modifying human behaviors, leading to potential energy savings of 9% to 18% without complex technology or building upgrades.
Book ChapterDOI
Weiyan Li, Minnan Piao, Botao Huang, Chenfei Qu 
01 Jan 2018
1 Citations
The energy consumption pattern for office buildings is identified through clustering and classification analysis of historical data, enabling outlier detection and rational energy consumption assessment for energy savings.
Energy consumption patterns in office buildings show correlations with meteorological parameters like temperature and irradiation. Three distinct daily demand patterns were identified, aiding in forecasting and sustainability assessments.
The energy consumption pattern for office buildings includes data on active/reactive power, voltage, current, weather, and indoor climate measurements, aiding load prediction algorithms and energy disaggregation research.

Related Questions

How to relate energy efficiency with cost strategi in green office building?5 answersEnergy efficiency in green office buildings is closely tied to cost-saving strategies. Implementing green building design, such as utilizing energy-saving technologies like heat pumps, can significantly reduce energy consumption and operational costs. Strategies like retrofitting chiller systems, recycling waste water, and replacing conventional lighting with energy-efficient LEDs can lead to substantial energy savings and cost reductions. Moreover, incorporating renewable energy sources like solar and wind power can further enhance energy efficiency and decrease electricity consumption in office buildings. While green buildings are expected to lower energy bills, studies have shown that eco-certification may not always result in the anticipated cost savings, highlighting the complexity of the relationship between energy efficiency and cost strategies in green office buildings.
What type of buildings are the major energy consumers?4 answersResidential, office, and commercial buildings are major energy consumers, contributing approximately 30%–40% of total energy consumption. The building sector accounts for the largest share of global final energy use (35%) and energy-related CO2 emissions (38%). Space heating is a significant end-use in buildings, comprising 33% of final energy consumption, followed by energy for cooking (18%), electrical appliances, and domestic hot water. The operational phase of buildings has the most substantial impact on global greenhouse gas emissions, with energy efficiency through high-performance, low-embodied-energy envelope technologies being crucial for reducing energy consumption in the sector. Retrofit strategies like envelope retrofitting and lighting improvement can significantly impact energy consumption in different building types.
How to analyze energy consumption patterns for a housing project?4 answersTo analyze energy consumption patterns for a housing project, a mixed method bottom-up approach can be used to detail and extrapolate energy consumption within households. This approach involves using room-by-room occupancy and activity logs, questionnaires, data loggers, and experimental footfall studies to collect data on energy consumption and occupancy trends. The collected data can then be digitized and analyzed using statistical techniques, such as modeling daily consumption patterns in households using a mixture of Gaussian distributions. Hierarchical clustering can be used to extract typical consumption patterns from the modeled data. Additionally, machine learning algorithms can be employed to predict occupant behavior based on energy use data, using features such as frequency, timestamp, power, and appliance information. These methods provide insights into energy consumption patterns and can guide energy-saving designs for housing projects.
Doing well by doing good? Green office buildings4 answersGreen office buildings have been found to have economic value, as they command higher rents and selling prices compared to non-green buildings. The premium for green office buildings is related to their energy-saving characteristics, with an increase in energy efficiency leading to a substantial increase in selling price. Additionally, the intangible effects of the green label itself may also play a role in determining the value of green buildings in the marketplace. These findings suggest that investing in green office buildings can be financially beneficial, as they not only provide cost savings in terms of energy consumption but also command higher prices in the market.
What is the building type that consumes a lot of energy consumption?3 answersResidential buildings are the type of buildings that consume a lot of energy. They account for one third of global energy consumption and one quarter of CO2 emissions. HVAC systems in buildings concentrate 38% of the energy consumption, highlighting the need for strengthened standards and incentives for retrofitting.
What is the best solution to optimize the energy consumption of the building that has been built?5 answersThe best solution to optimize the energy consumption of a building is to implement simple and practical measures such as using innovative materials, products, and construction methods, as well as improving the thermal reinforcement of the building. These measures include using alternative roofing and facade materials, double glazed windows, vertical awnings, and balconies. By simulating a residential building in Ahvaz, Iran, it was found that using rockwool and aluminum composite panels for the facade, pumice concrete roofing, double glazed windows, a vertical awning of a 70 cm height, and a balcony of 50 cm depth resulted in the highest energy efficiency and thermal comfort. Additionally, implementing a predictive control approach combined with an energy optimization approach based on intrinsic system parameters can achieve desired performances and energy efficiency in building management. Furthermore, digitizing the heat and electrical energy flexibility of buildings using blockchain technology and ERC-1155 tokens can optimize energy consumption and enable buildings to trade heat and electricity within community-level marketplaces.

See what other people are reading

What are the topmost topics for research that includes power system and machine learning?
5 answers
The topmost topics for research involving power systems and machine learning include dynamic stability analysis, power flow analysis, security guarantee in power systems, and challenges in adapting ML techniques for modern electric power systems. These topics address critical issues such as adapting to changing power system structures, enhancing observability and efficiency, predicting transient stability, load forecasting, network attack detection, and addressing operational challenges in power distribution systems. The research emphasizes the integration of machine learning techniques to handle massive data, improve system reliability, and facilitate decision-making processes in power system operation and maintenance. This interdisciplinary approach aims to bridge the gap between research advancements and practical applications in the field of power systems and machine learning.
What are some common customer questions related to factual information?
4 answers
Common customer questions related to factual information often revolve around understanding the nutritional content of products like alcohol beverages. Additionally, customers may inquire about the specifics of new technologies, such as smart grid technologies, to better grasp their benefits and functionalities. In the realm of services marketing, customers may seek factual information to mitigate the perceived risks associated with intangible service products. Furthermore, customers may inquire about the authenticity, clarity, and relevance of information provided by companies, as these attributes play a crucial role in building trust and loyalty. Lastly, customers may inquire about product details such as manufacturing dates, expiry dates, and any associated discount systems, especially in sectors like food and pharmaceuticals.
What is smart grid?
4 answers
A smart grid is an advanced digital system that integrates various components like distributed generation sources, energy storage systems, and advanced metering infrastructure to efficiently manage electricity supply and demand. It utilizes high technology devices to enable two-way power flow, adaptability, sustainability, self-healing capabilities, and flexibility in handling uncertainties. Smart grids leverage technologies such as IoT, Wireless Sensor Networks, and blockchain to optimize energy production, consumption, and distribution, leading to cost-efficiency, enhanced performance, and better energy utilization. By incorporating renewable energy sources and implementing intelligent systems for monitoring and communication, smart grids facilitate energy trading, peer-to-peer transactions, and improved energy management. The concept of smart grids is crucial for addressing the challenges of rising energy demand, unpredictable load patterns, and the need for efficient energy conservation.
What a meaning of Touch step?
5 answers
A "Touch step" refers to a method or action related to touch-sensitive devices or touchscreens. It involves interacting with a device through touch gestures or actions. In the context of the provided research papers, touch steps are crucial in various applications. For instance, a touch method is described for accurate touch operations on mobile terminal screens, enhancing user experience. Additionally, a one-touch step pedestal for a telephone pole is designed to provide stability and efficiency in high-place work by allowing quick locking and releasing of a stepping foothold portion. Furthermore, touch and step voltages are monitored in substations through a sensor network to ensure grounding grid performance, enhancing safety and preventing equipment damage. Overall, touch steps play a significant role in user interaction, safety monitoring, and operational efficiency in different technological settings.
What is the introduction of research paper on school high room temperature?
5 answers
The introduction of the research paper on high room temperature in schools highlights the inadequacy of cooling systems in classrooms, leading to discomfort and poor thermal conditions for students. Studies emphasize the impact of increased air velocity and improved ventilation rates on students' performance and comfort. Additionally, the importance of maintaining optimal indoor environmental quality (IEQ) in schools is underscored, as poor IEQ can significantly affect students' learning abilities and overall well-being. Furthermore, the need for energy-efficient cooling methods in school environments is emphasized, with a focus on the potential benefits of implementing innovative cooling strategies to enhance student performance and comfort. Overall, the research aims to address the challenges posed by high room temperatures in schools and explore effective solutions to create conducive learning environments.
How does the implementation of an intelligent switching system affect the efficiency of hybrid RF/FSO terrestrial links?
5 answers
The implementation of an intelligent switching system in hybrid RF/FSO terrestrial links significantly enhances efficiency. By utilizing technologies like gated recurrent unit (GRU) neural networks with time attention mechanisms, Time-Hysteresis (TH) assisted switching, and machine learning methods for predicting RSSI parameters, these systems can reduce link switching frequency, interruption duration, and improve Bit Error Rate (BER) during transitions. The intelligent systems accurately predict FSO channel fading, achieving high precision with low Absolute Percentage Error (APE) values. Additionally, the use of cooperative communication, MIMO techniques, and DF relaying methods further enhance performance, leading to improved Symbol Error Rate (SER) and overall system efficiency. Overall, these advancements in intelligent switching systems optimize the utilization of RF/FSO links for high-data-rate transmission in terrestrial networks.
How does spatial configuration affect indoor air quality and ventilation?
5 answers
Spatial configuration plays a crucial role in indoor air quality and ventilation. Studies show that factors like room geometry, inlet/outlet positions, and heat sources significantly impact ventilation performance. Spatial indicators like connectivity and integration correlate positively with airflow rates, indicating the potential for natural ventilation in different configurations. Additionally, the horizontal position of vents relative to each other influences airflow patterns within a room, affecting pollutant dispersion and occupant exposure. Implementing spatial analytic methods, such as IoT and object detection, can optimize ventilation system operation based on indoor occupancy, reducing energy waste and maintaining indoor air quality below critical CO2 levels. Therefore, understanding and optimizing spatial configurations are essential for efficient ventilation design and ensuring high indoor air quality.
Are transformers effective for time series forecasting?
5 answers
Transformers have been widely adopted for time series forecasting tasks, but recent research questions their effectiveness. While Transformers excel at capturing semantic correlations in sequences, they may struggle with extracting temporal relations crucial for time series modeling. Surprisingly, simple linear models have outperformed sophisticated Transformer-based models in long-term time series forecasting experiments, indicating potential limitations of Transformers in this domain. However, in the context of load forecasting in data-rich domains like the smart grid, Transformers have shown effectiveness when trained with appropriate strategies, outperforming linear models and multi-layer perceptrons. Therefore, the effectiveness of Transformers for time series forecasting appears to depend on the specific task and training strategies employed.
What are the core competencies of a delivery or logistics coordinator?
5 answers
The core competencies of a delivery or logistics coordinator encompass a range of skills crucial for efficient supply chain management. These competencies include expertise in information flow management, coordination skills for managing interfaces and designing supply systems, the ability to centrally plan vehicle routes and schedule dock time slots for deliveries, a deep understanding of logistics competence allocation and coordination mechanisms within the Logistics Service Supply Chain (LSSC), and the effective exploitation of logistics competences for sustained competitive advantage creation. Overall, a logistics coordinator must excel in information flow management, interface coordination, route planning, competence allocation, and competitive advantage creation to ensure the smooth functioning and optimization of the supply chain system.
How do different rating scales and methodologies for assessing attack feasibility impact the allocation of resources for cybersecurity?
5 answers
Different rating scales and methodologies for assessing attack feasibility play a crucial role in optimizing the allocation of cybersecurity resources. The use of attack-defense trees and game theory aids in analyzing cyber-attack paths and defense strategies within systems like the Smart Grid, enabling the optimal allocation of resources for cybersecurity infrastructure. Additionally, the implementation of quantitative simulation models, such as the AnyLogic model, enhances the accuracy of measuring the probability of success of threat actors, guiding decision-makers on resource allocation for cybersecurity controls. Moreover, the Markov Decision Process framework offers an approach for allocating limited cybersecurity resources between different layers of defense, such as agility and recovery, ensuring a comprehensive defense-in-depth strategy.
Double-Edged Defense: Thwarting Cyber Attacks and Adversarial Machine Learning in IEC 60870-5-104 Smart Grids
5 answers
In the realm of IEC 60870-5-104 Smart Grids, the integration of machine learning techniques, particularly deep learning, poses a double-edged defense against cyber attacks. While machine learning methods like deep neural networks are effective in detecting anomalies and potential cyber threats, they are also susceptible to adversarial perturbations, highlighting the need for robust security measures. Studies emphasize the significance of monitoring and detecting cyberattacks in smart grids using advanced technologies like phasor measurement units (PMUs) and robust feature engineering to enhance accuracy and resilience against manipulations. Machine learning algorithms such as Perceptron, Logistic Regression, Support Vector Machine, and K-Nearest Neighbors are employed to differentiate between secure and attacked environments, aiming to predict erroneous data injections and enhance the security of smart grid communication networks.