home energy management
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2022 ◽  
Vol 85 ◽  
pp. 102347
Sonja Oliveira ◽  
Lidia Badarnah ◽  
Merate Barakat ◽  
Anna Chatzimichali ◽  
Ed Atkins

2022 ◽  
Vol 8 ◽  
pp. 560-566
Ejaz Ul Haq ◽  
Cheng Lyu ◽  
Peng Xie ◽  
Shuo Yan ◽  
Fiaz Ahmad ◽  

Nishi Singh ◽  
M.P.S. Chawla ◽  
Sandeep Bhongade ◽  

HEMS (home energy management systems) are controllers that manage and coordinate a home's generation, storage, and loads. These controllers are becoming increasingly important. To ensure that distributed energy penetration continues to grow resources are appropriately utilized and the process is not disrupted within the grid[1]. An approach to hems design based on behavioural control approaches is discussed in this paper which do not require accurate models or forecasts and are particularly responsive to changing situations, in this study. In this study, the role of the customer as well as the micro grid in intelligent demand management is demonstrated using MATLAB 2018 Fuzzy tool.[3]

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 537
Rittichai Liemthong ◽  
Chitchai Srithapon ◽  
Prasanta K. Ghosh ◽  
Rongrit Chatthaworn

It is well documented that both solar photovoltaic (PV) systems and electric vehicles (EVs) positively impact the global environment. However, the integration of high PV resources into distribution networks creates new challenges because of the uncertainty of PV power generation. Additionally, high power consumption during many EV charging operations at a certain time of the day can be stressful for the distribution network. Stresses on the distribution network influence higher electricity tariffs, which negatively impact consumers. Therefore, a home energy management system is one of the solutions to control electricity consumption to reduce electrical energy costs. In this paper, a meta-heuristic-based optimization of a home energy management strategy is presented with the goal of electrical energy cost minimization for the consumer under the time-of-use (TOU) tariffs. The proposed strategy manages the operations of the plug-in electric vehicle (PEV) and the energy storage system (ESS) charging and discharging in a home. The meta-heuristic optimization, namely a genetic algorithm (GA), was applied to the home energy management strategy for minimizing the daily electrical energy cost for the consumer through optimal scheduling of ESS and PEV operations. To confirm the effectiveness of the proposed methodology, the load profile of a household in Udonthani, Thailand, and the TOU tariffs of the provincial electricity authority (PEA) of Thailand were applied in the simulation. The simulation results show that the proposed strategy with GA optimization provides the minimum daily or net electrical energy cost for the consumer. The daily electrical energy cost for the consumer is equal to 0.3847 USD when the methodology without GA optimization is used, whereas the electrical energy cost is equal to 0.3577 USD when the proposed methodology with GA optimization is used. Therefore, the proposed optimal home energy management strategy with GA optimization can decrease the daily electrical energy cost for the consumer up to 7.0185% compared to the electrical energy cost obtained from the methodology without GA optimization.

2022 ◽  
Vol 305 ◽  
pp. 117753
Seyyed Reza Ebrahimi ◽  
Morteza Rahimiyan ◽  
Mohsen Assili ◽  
Amin Hajizadeh

2022 ◽  
pp. 1132-1147
Tesfahun Molla

With the development of smart grid technology, residents can schedule their power consumption pattern in their home to minimize electricity expense, reducing peak-to-average ratio (PAR) and peak load demand. The two-way flow of information between electric utilities and consumers in smart grid opened new areas of applications. In this chapter, the general architectures of the home energy management systems (HEMS) are introduced in a home area network (HAN) based on the smart grid scenario. Efficient scheduling methods for home power usage are discussed. The energy management controller (EMC) receives the demand response (DR) information indicating the Time-of use electricity price (TOUP) through the home gateway (HG). With the DR signal, the EMC achieves an optimal power scheduling scheme that can be delivered to each electric appliance by the HG.

IoT ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 73-90
Yann Stephen Mandza ◽  
Atanda Raji

In developing countries today, population growth and the penetration of higher standard of living appliances in homes has resulted in a rapidly increasing residential load. In South Africa, the recent rolling blackouts and electricity price increase only highlighted this reality, calling for sustainable measures to reduce overall consumption and peak load. The dawn of the smart grid concept, embedded systems, and ICTs have paved the way for novel Home Energy Management Systems (HEMS) design. In this regard, the Internet of Things (IoT), an enabler for intelligent and efficient energy management systems, is the subject of increasing attention for optimizing HEMS design and mitigating its deployment cost constraints. In this work, we propose an IoT platform for residential energy management applications focusing on interoperability, low cost, technology availability, and scalability. We addressed the backend complexities of IoT Home Area Networks (HAN) using the Open Consortium Foundation (OCF) IoTivity-Lite middleware. To augment the quality, servicing, reduce the cost, and the development complexities, this work leverages open-source cloud technologies from Back4App as Backend-as-a-Service (BaaS) to provide consumers and utilities with a data communication platform within an experimental study illustrating time and space agnostic “mind-changing” energy feedback, Demand Response Management (DRM) under a peak shaving algorithm yielded peak load reduction around 15% of the based load, and appliance operation control using a HEM App via an Android smartphone.

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8572
Kazui Yoshida ◽  
Hom B. Rijal ◽  
Kazuaki Bogaki ◽  
Ayako Mikami ◽  
Hiroto Abe

In the international movement to combat the threat of climate change, the timely implementation of residential energy-saving practises is becoming an urgent issue. Because the number of apartments is increasing, we analysed data from home energy management systems (HEMSs) and data from questionnaire surveys of 309 households in a condominium. We focused on the seasonal variation in air-conditioning (AC) use in living-dining rooms to determine the tendency of energy use for heating/cooling related to the characteristics of flats, the profiles of residents, and energy-saving behaviours. In winter, 80% of residents mainly used gas floor heating rather than AC and 24% did not use AC in winter. In households where someone stays home for long hours, they prefer gas floor heating rather than AC in winter. These households also tend to engage in energy-saving behaviours to adjust the indoor thermal environment. There are several types of energy-saving lifestyles; therefore, effective energy-saving measures should be considered for both energy efficiency and the thermal comfort of residents.

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