Add to ORKGTo implement demand response in residential sector and facilitate the integration of renewable resources and plug-in electric vehicles in future smart grid, this paper proposes a framework of home energy management system (HEMS) and a optimization algorithm for it based on improved artificial bee colony. The algorithm schedules the operations of schedulable home appliances according to electricity price, forecasted outdoor temperature and renewable power output, and user preferences to minimize user's electricity cost. The effectiveness of the algorithm is verified by simulations, and the electricity cost can be reduced by 47.76%
This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorit...
The main problem for both the utility companies and the end-used is to efficiently schedule the home...
[EN] The connection of devices in a smart home should be done optimally, this helps save energy and ...
Demand response (DR) is an effective method to lower peak-to-average ratio of demand, facilitate the...
Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly fo...
Small scale intermittent renewable energy consisting of roof-mounted photovoltaic generators and mic...
The traditional power grid is inadequate to overcome modern day challenges. As the modern era demand...
In this paper, we comparatively evaluate the performance of home energy management controller which ...
Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme...
Smart grid enables consumers to control and schedule the consumption pattern of their appliances, mi...
Smart grid technology has given users the ability to regulate their home energy use more efficiently...
In a Smart Grid (SG) scenario, domestic consumers can gain cost reduction benefit by scheduling thei...
This paper presents an optimization-based home energy management system, by taking advantages of ren...
Home energy management system (HEMS) is essential for residential electricity consumers to participa...
This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorit...
This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorit...
The main problem for both the utility companies and the end-used is to efficiently schedule the home...
[EN] The connection of devices in a smart home should be done optimally, this helps save energy and ...
Demand response (DR) is an effective method to lower peak-to-average ratio of demand, facilitate the...
Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly fo...
Small scale intermittent renewable energy consisting of roof-mounted photovoltaic generators and mic...
The traditional power grid is inadequate to overcome modern day challenges. As the modern era demand...
In this paper, we comparatively evaluate the performance of home energy management controller which ...
Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme...
Smart grid enables consumers to control and schedule the consumption pattern of their appliances, mi...
Smart grid technology has given users the ability to regulate their home energy use more efficiently...
In a Smart Grid (SG) scenario, domestic consumers can gain cost reduction benefit by scheduling thei...
This paper presents an optimization-based home energy management system, by taking advantages of ren...
Home energy management system (HEMS) is essential for residential electricity consumers to participa...
This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorit...
This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorit...
The main problem for both the utility companies and the end-used is to efficiently schedule the home...
[EN] The connection of devices in a smart home should be done optimally, this helps save energy and ...