scholarly journals Predicting the Energy Consumption of Residential Buildings for Regional Electricity Supply-Side and Demand-Side Management

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 30386-30397 ◽  
Author(s):  
Huiling Cai ◽  
Shoupeng Shen ◽  
Qingcheng Lin ◽  
Xuefeng Li ◽  
Hui Xiao
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Demand Side Management ◽  
Electricity Supply ◽  
Supply Side ◽  
Demand Side

scholarly journals Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4539 ◽  
Author(s):  
Kumar ◽  
Brar ◽  
Singh ◽  
Nikolovski ◽  
Baghaee ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Management ◽  
Residential Buildings ◽  
Effective Means ◽  
Demand Side Management ◽  
Demand Side ◽  
Specific System ◽  
Energy Data ◽  
Energy Auditing

With the ever-growing power demand, the energy efficiency in commercial and residential buildings is a matter of great concern. Also, strategic energy auditing (SEA) and demand-side management (DSM) are cost-effective means to identify the requirements of power components and their operation in the energy management system. In a commercial or residential building, the major components are light sources and heating, ventilation, and air conditioning. The number of these components to be installed depends upon the technical and environmental standards. In this scenario, energy auditing (EA) allows identifying the methods, scope, and time for energy management, and it helps the costumers to manage their energy consumption wisely to reduce electricity bills. In the literature, most of the traditional strategies employed specific system techniques and algorithms, whereas, in recent years, load shifting-based DSM techniques were used under different operating scenarios. Considering these facts, the energy data in a year were collected under three different seasonal changes, i.e., severe cold, moderate, and severe heat for the variation in load demand under different environmental conditions. In this work, the energy data under three conditions were averaged, and the DSM schemes were developed for the operation of power components before energy auditing and after energy auditing. Moreover, the performance of the proposed DSM techniques was compared with the practical results in both scenarios, and, from the results, it was observed that the energy consumption reduced significantly in the proposed DSM approach.

scholarly journals Autonomous Fuzzy Controller Design for the Utilization of Hybrid PV-Wind Energy Resources in Demand Side Management Environment

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1618
Author(s):  
Mohanasundaram Anthony ◽  
Valsalal Prasad ◽  
Raju Kannadasan ◽  
Saad Mekhilef ◽  
Mohammed H. Alsharif ◽  
...  
Keyword(s):  
Wind Energy ◽  
Energy Cost ◽  
Fuzzy Controller ◽  
Residential Buildings ◽  
Peak Load ◽  
Demand Side Management ◽  
Consumption Pattern ◽  
Demand Side ◽  
Pv System ◽  
Inference System

This work describes an optimum utilization of hybrid photovoltaic (PV)—wind energy for residential buildings on its occurrence with a newly proposed autonomous fuzzy controller (AuFuCo). In this regard, a virtual model of a vertical axis wind turbine (VAWT) and PV system (each rated at 2 kW) are constructed in a MATLAB Simulink environment. An autonomous fuzzy inference system is applied to model primary units of the controller such as load forecasting (LF), grid power selection (GPS) switch, renewable energy management system (REMS), and fuzzy load switch (FLS). The residential load consumption pattern (4 kW of connected load) is allowed to consume energy from the grid and hybrid resources located at the demand side and classified as base, priority, short-term, and schedulable loads. The simulation results identify that the proposed controller manages the demand side management (DSM) techniques for peak load shifting and valley filling effectively with renewable sources. Also, energy costs and savings for the home environment are evaluated using the proposed controller. Further, the energy conservation technique is studied by increasing renewable conversion efficiency (18% to 23% for PV and 35% to 45% for the VAWT model), which reduces the spending of 0.5% in energy cost and a 1.25% reduction in grid demand for 24-time units/day of the simulation study. Additionally, the proposed controller is adapted for computing energy cost (considering the same load pattern) for future demand, and it is exposed that the PV-wind energy cost reduced to 6.9% but 30.6% increase of coal energy cost due to its rise in the Indian energy market by 2030.

Production Process Modeling for Demand Side Management

2017 ◽  
Vol 871 ◽  
pp. 77-86
Author(s):  
Stefanie Kabelitz ◽  
Sergii Kolomiichuk
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Supply And Demand ◽  
Demand Side Management ◽  
Mixed Integer ◽  
Mixed Integer Program ◽  
Business Practices ◽  
Demand Side ◽  
Manufacturing Companies ◽  
Consumption Data

The supply of electricity is growing increasingly dependent on the weather as the share of renewable energies increases. Different measures can nevertheless maintain grid reliability and quality. These include the use of storage technologies, upgrades of the grid and options for responsiveness to supply and demand. This paper focuses on demand side management and the use of flexibility in production processes. First, the framework of Germany’s energy policy is presented and direct and indirect incentives for businesses to seek as well as to provide flexibility capabilities are highlighted. Converting this framework into a mixed integer program leads to multi-objective optimization. The challenge inherent to this method is realistically mapping the different objectives that affect business practices directly and indirectly in a variety of laws. An example is introduced to demonstrate the complexity of the model and examine the energy flexibility. Second, manufacturing companies’ energy efficiency is assessed under the frequently occurring conditions of heavily aggregated energy consumption data and of information with insufficient depth of detail to perform certain analyses, formulate actions or optimize processes. The findings obtained from the energy assessment and energy consumption projections are used to model the production system’s energy efficiency and thus facilitate optimization. Methods of data mining and machine learning are employed to project energy consumption. Aggregated energy consumption data and different production and environmental parameters are used to assess indirectly measured consumers and link projections of energy consumption with the production schedule.

scholarly journals Supply Side Management vs. Demand Side Management of a Residential Microgrid Equipped with an Electric Vehicle in a Dual Tariff Scheme

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4351 ◽  
Author(s):  
Alain Aoun ◽  
Hussein Ibrahim ◽  
Mazen Ghandour ◽  
Adrian Ilinca
Keyword(s):  
Electric Vehicle ◽  
Storage System ◽  
Electric Energy ◽  
Demand Side Management ◽  
Industrial Applications ◽  
Energy Model ◽  
Supply Side ◽  
Demand Side ◽  
Pv System ◽  
Power Sources

Fundamentally, two main methodologies are used to reduce the electric energy bill in residential, commercial, and even industrial applications. The first method is to act on the supply side by integrating alternative means of power generation, such as renewable energy generators, having a relatively low levelized cost of energy. Whereas, the second methodology focuses on the management of the load to minimize the overall paid cost for energy. Thus, this article highlights the importance of demand side management by comparing it to the supply side management having, as criteria, the total achieved savings on the overall annual energy bill of a residential microgrid supplied by two power sources and equipped with an electric vehicle. The optimization takes into consideration the cost of kWh that is paid by the prosumer based on an economical model having as inputs the outcomes of the energy model. The adopted energy model integrates, on the demand side, an intelligent energy management system acting on secondary loads, and on the supply side, a photovoltaic (PV) system with and without battery energy storage system (BESS). The outcome of this work shows that, under the right circumstances, demand side management can be as valuable as supply side control.

scholarly journals Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

2010 ◽  
Vol 1 (3) ◽  
pp. 320-331 ◽  
Author(s):  
Amir-Hamed Mohsenian-Rad ◽  
Vincent W. S. Wong ◽  
Juri Jatskevich ◽  
Robert Schober ◽  
Alberto Leon-Garcia
Keyword(s):  
Energy Consumption ◽  
Smart Grid ◽  
Demand Side Management ◽  
Demand Side ◽  
The Future ◽  
Game Theoretic

scholarly journals Factors Driving Consumer Involvement in Energy Consumption and Energy-Efficient Purchasing Behavior: Evidence from Korean Residential Buildings

2020 ◽  
Vol 12 (14) ◽  
pp. 5573 ◽  
Author(s):  
Soyoung Yoo ◽  
Jiyong Eom ◽  
Ingoo Han
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Use ◽  
Residential Buildings ◽  
Cost Effective ◽  
Green Technology ◽  
Consumer Involvement ◽  
Demand Side ◽  
Factors Affecting ◽  
Technological Advances

The recent rapid transition in energy markets and technological advances in demand-side interventions has renewed attention on consumer behavior. A rich literature on potential factors affecting residential energy use or green technology adoption has highlighted the need to better understand the fundamental causes of consumer heterogeneity in buildings’ energy-related behavior. Unresolved questions such as which consumers are most likely to opt into demand-side management programs and what factors might explain the wide variation in behavioral responses to such programs make it difficult for policy-makers to develop cost-effective energy efficiency or demand response programs for residential buildings. This study extends the literature on involvement theory and energy-related behavior by proposing a holistic construct of household energy involvement (HEI) to represent consumers’ personal level of interest in energy services. Based on a survey of 5487 Korean households, it finds that HEI has a stronger association with consumer values, such as preferences for indoor thermal comfort and automation, than with socioeconomic or housing characteristics and demonstrates HEI’s potential as a reliable, integrated predictor of both energy consumption and energy-efficient purchases. The study illuminates the multifaceted influences that shape energy-related behavior in residential buildings and offers new tools to help utility regulators identify and profile viable market segments, improve the cost-effectiveness of their programs, and eventually promote urban sustainability.

Integration of Demand-Side Management Programs and Supply-Side Alternatives for Decentralized Energy Planning

2017 ◽  
pp. 252-270
Author(s):  
Masoud Rabbani ◽  
Mahdi Dolatkhah
Keyword(s):  
Mathematical Formulation ◽  
Demand Side Management ◽  
Green Energy ◽  
Energy Planning ◽  
Supply Side ◽  
Demand Side ◽  
Planning Decisions ◽  
Energy Technologies ◽  
Decentralized Energy ◽  
Load Shape

Optimally selection of an appropriate mix of renewable sources for supplying electricity of remote areas has been always an important challenge for policy makers. Also, in recent years, the great advantages of Demand Side Management (DSM) programs such as postponing investments in construction of new plants and/or desirably modification of electricity consumption pattern has turned great attention of energy planners to these programs. Moreover, the issue of global warming has caused the need for reduction of human use of fossil fuels and switching to employing green energy sources. To address the mentioned concerns, in this paper, an integrated mathematical formulation for selecting the best mix of renewable energy technologies is proposed. In this study, DSM considered as a competitive option against supply-side alternatives for making energy planning decisions. Additionally, by considering real data from a case in Iran, the effects of considering energy import and export has been taken into account. To validate the model, for smaller-scaled test problems the model has been solved by Lingo 8.0 software while for solving larger instances of problems (real scale of case study) a novel genetic algorithm (GA) is devised. The numerical results indicate that DSM policies have made use of their maximum capacity and resulted in significant improvements, especially in terms of reducing consumption and suitably changing the load shape.

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