Reduction of Energy Consumption in the Home Using Gamification in the Systems of Energy Management (HEM)

2018 ◽  
Author(s):  
Zurisaddai la Cruz Severiche de Maury ◽  
Ana Fernandez Vilas ◽  
Rebeca Diaz Redondo
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Reduction Of Energy Consumption

Energy Management Maturity Model: an organizational tool to foster the continuous reduction of energy consumption in companies

2014 ◽  
Vol 83 ◽  
pp. 108-117 ◽  
Author(s):  
Vito Introna ◽  
Vittorio Cesarotti ◽  
Miriam Benedetti ◽  
Sonia Biagiotti ◽  
Raffaele Rotunno
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Maturity Model ◽  
Reduction Of Energy Consumption

scholarly journals Industrial Facility Electricity Consumption Forecast Using Artificial Neural Networks and Incremental Learning

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4774
Author(s):  
Daniel Ramos ◽  
Pedro Faria ◽  
Zita Vale ◽  
João Mourinho ◽  
Regina Correia
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Incremental Learning ◽  
Forecast Accuracy ◽  
Electricity Consumption ◽  
Relevant Information ◽  
Industrial Facility ◽  
Artificial Neural ◽  
Reduction Of Energy Consumption ◽  
Artificial Neural Network Ann

Society’s concerns with electricity consumption have motivated researchers to improve on the way that energy consumption management is done. The reduction of energy consumption and the optimization of energy management are, therefore, two major aspects to be considered. Additionally, load forecast provides relevant information with the support of historical data allowing an enhanced energy management, allowing energy costs reduction. In this paper, the proposed consumption forecast methodology uses an Artificial Neural Network (ANN) and incremental learning to increase the forecast accuracy. The ANN is retrained daily, providing an updated forecasting model. The case study uses 16 months of data, split in 5-min periods, from a real industrial facility. The advantages of using the proposed method are illustrated with the numerical results.

SMART NETWORKS FOR DIGITALIZATION OF URBAN ECONOMY WITHIN THE FRAMEWORK OF THE “SMART CITY”

2020 ◽  
Vol 3 (8) ◽  
pp. 21-27
Author(s):  
S. V. PROKOPCHINA ◽  
Keyword(s):  
Energy Consumption ◽  
Internal Energy ◽  
Energy Management ◽  
Energy Security ◽  
Smart City ◽  
Urban Economy ◽  
Training Center ◽  
Energy Audit ◽  
Intelligent Networks ◽  
Industrial Energy

The article deals with methodological and practical issues of building Bayesian intelligent networks (BIS) for digitalization of urban economy based on the principles of the “Smart city” concept. The BIS complex as a whole corresponds to the architecture of urban household management complexes for construction and industrial energy purposes for solving the problems of internal energy audit, accounting for energy consumption, ensuring energy security of enterprises and territories, in Addition, the system can become the basis for the implementation of a training center for energy management and housing.

scholarly journals Multi-Objective Energy Management and Charging Strategy for Electric Bus Fleets in Cities Using Various ECO Strategies

2021 ◽  
Vol 13 (14) ◽  
pp. 7865
Author(s):  
Mohammed Mahedi Hasan ◽  
Nikos Avramis ◽  
Mikaela Ranta ◽  
Andoni Saez-de-Ibarra ◽  
Mohamed El Baghdadi ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Thermal Management ◽  
Energy Management ◽  
Management Strategy ◽  
Energy Requirement ◽  
Optimization Technique ◽  
Total Cost ◽  
Multi Objective ◽  
Battery Capacity ◽  
Eco Features

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.

scholarly journals Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3287
Author(s):  
Alireza Tabrizikahou ◽  
Piotr Nowotarski
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Structural Optimization ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Construction Materials ◽  
High Energy ◽  
Building Structures ◽  
Life Cycle Stages ◽  
Reduction Of Energy Consumption

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes’ performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works.

scholarly journals Traffic Light Priority for Trams in Warsaw as a Tool for Transport Policy and Reduction of Energy Consumption

2021 ◽  
Vol 13 (8) ◽  
pp. 4180
Author(s):  
Andrzej Czerepicki ◽  
Tomasz Krukowicz ◽  
Anna Górka ◽  
Jarosław Szustek
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Electric Energy ◽  
Fixed Time ◽  
Pollutant Emissions ◽  
Computer Simulation Model ◽  
Traffic Light ◽  
Electric Energy Consumption ◽  
Time Control ◽  
Reduction Of Energy Consumption

The article presents an analysis of priority solutions for trams at a selected sequence of intersections in Warsaw (Poland). An analysis of the literature has shown the topicality of this issue. A computer simulation model of a coordinated sequence of intersections was constructed. Three test scenarios were designed: the existing control system, the new coordinated fixed-time control system, and the adaptive control system with active priority. In the simulation process, detailed travel characteristics of trams and other traffic participants in a selected section were obtained for the three varying scenarios. Electric energy consumption for traction needs and pollutant emissions was then estimated for each of the variants. It was concluded that for the analyzed configuration, implementation of the adaptive priority will result in a reduction of tram time losses by up to 25%, a reduction in energy consumption by up to 23%, and a reduction in the emission of pollutants from individual vehicles by up to 3% in relation to the original variant. The conducted research may be the basis for a comprehensive method of assessing the effectiveness of applying the adaptative priority when designing new tramway lines and modernizing the existing ones.

scholarly journals Electrified Powertrain with Multiple Planetary Gears and Corresponding Energy Management Strategy

Vehicles ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 341-356
Author(s):  
Daizy Rajput ◽  
Jose M. Herreros ◽  
Mauro S. Innocente ◽  
Joschka Schaub ◽  
Arash M. Dizqah
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Mode Selection ◽  
Optimal Operation ◽  
Fourth Generation ◽  
Selection Strategy ◽  
Energy Management Strategy ◽  
Planetary Gears

Modern hybrid electric vehicles (HEVs) like the fourth generation of Toyota Prius incorporate multiple planetary gears (PG) to interconnect various power components. Previous studies reported that increasing the number of planetary gears from one to two reduces energy consumption. However, these studies did not compare one PG and two PGs topologies at their optimal operation. Moreover, the size of the powertrain components are not the same and hence the source of reduction in energy consumption is not clear. This paper investigates the effect of the number of planetary gears on energy consumption under optimal operation of the powertrain components. The powertrains with one and two PGs are considered and an optimal simultaneous torque distribution and mode selection strategy is proposed. The proposed energy management strategy (EMS) optimally distributes torque demands amongst the power components whilst also controlling clutches (i.e., mode selection). Results show that increasing from one to two PGs reduces energy consumption by 4%.

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