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Demand side management (DSM) is a key solution for reducing the peak-time power consumption in smart grids. To provide incentives for consumers to shift their consumption to off-peak times, the utility company charges consumers differential…
With the widely used smart meters in the energy sector, anomaly detection becomes a crucial mean to study the unusual consumption behaviors of customers, and to discover unexpected events of using energy promptly. Detecting consumption…
Demand response (DR) for smart grids, which intends to balance the required power demand with the available supply resources, has been gaining widespread attention. The growing demand for electricity has presented new opportunities for…
LoRaWAN enables massive connectivity for Internet-of-Things applications. Many published works employ stochastic geometry to derive outage models of LoRaWAN over fading channels assuming fixed transmit power and distance-based spreading…
Distribution grids across the world are undergoing profound changes due to advances in energy technologies. Electrification of the transportation sector and the integration of Distributed Energy Resources (DERs), such as photo-voltaic…
The increase of electric demand and the progressive integration of renewable sources threatens the stability of the power grid. To solve this issue, several methods have been proposed to control the demand side instead of increasing the…
This study proposes a real-time distributed energy resource (DER) coordination model that can exploit flexibility from the DERs to solve voltage and overloading issues using both active and reactive power. The model considers time-coupling…
Demand side participation is now widely recognized as being extremely critical for satisfying the growing electricity demand in the US. The primary mechanism for demand management in the US is demand response (DR) programs that attempt to…
In order to efficiently provide demand side management (DSM) in smart grid, carrying out pricing on the basis of real-time energy usage is considered to be the most vital tool because it is directly linked with the finances associated with…
We consider demand-side primary frequency control in the power grid provided by smart and flexible loads: loads change consumption to match generation and help the grid while minimizing disutility for consumers incurred by consumption…
The large-scale integration of Distributed Energy Resources (DERs) into the electric power system offers new opportunities to ensure stability. For example, Active Distribution Networks (ADNs) can be used in (sub-)transmission systems in…
Electric vehicles (EVs) are finally making their way onto the roads. However, the challenges concerning their long charging times and their impact on congestion of the power distribution grid are still waiting to be resolved. With…
A number of governments and organizations around the world agree that the first step to address national and international problems such as energy independence, global warming or emergency resilience, is the redesign of electricity…
Residential consumers can use the demand response program (DRP) if they can utilize the home energy management system (HEMS), which reduces consumer costs by automatically adjusting air conditioning (AC) setpoints and shifting some…
In this paper, we adopt constrastive explanations within an end-user application for temporal planning of smart homes. In this application, users have requirements on the execution of appliance tasks, pay for energy according to dynamic…
With the ongoing integration of Renewable Energy Sources (RES), the complexity of power grids is increasing. Due to the fluctuating nature of RES, ensuring the reliability of power grids can be challenging. One possible approach for…
The Internet of Things (IoT) paradigm brings an opportunity for advanced Demand Response (DR) solutions. It enables visibility and control on the various appliances that may consume, store or generate energy within a home. It has been shown…
In this work, we present a survey of residential load controlling techniques to implement demand side management in future smart grid. Power generation sector facing important challenges both in quality and quantity to meet the increasing…
This paper presents a multi-agent Deep Reinforcement Learning (DRL) framework for autonomous control and integration of renewable energy resources into smart power grid systems. In particular, the proposed framework jointly considers demand…
We propose and solve a stochastic dynamic programming (DP) problem addressing the optimal provision of regulation service reserves (RSR) by controlling dynamic demand preferences in smart buildings. A major contribution over past dynamic…