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Demand-side energy management, such as the real-time pricing (RTP) program, offers manufacturers opportunities to reduce energy costs by shifting production to low-price hours. However, this strategy is challenging to implement when machine…
New generation electricity network called Smart Grid is a recently conceived vision for a cleaner, more efficient and cheaper electricity system. One of the major challenges of electricity network is that generation and consumption should…
Mobile edge computing (MEC) is a promising technology for enhancing the computation capacities and features of mobile users by offloading complex computation tasks to the edge servers. However, mobility poses great challenges on delivering…
User scheduling, beamforming and energy coordination are investigated in smart-grid powered cellular networks (SGPCNs), where the base stations are powered by a smart grid and natural renewable energy sources. Heterogeneous energy…
Electricity usage is a major portion of utility bills and the best place to start lowering them. An effective home energy management approach is introduced to decrease customers' electricity bills by determining the optimal appliance…
In this paper, distributed energy management of interconnected microgrids, which is stated as a dynamic economic dispatch problem, is studied. Since the distributed approach requires cooperation of all local controllers, when some of them…
Renewables will soon dominate energy production in our electric power system. And yet, how to integrate renewable energy into the grid and the market is still a subject of major debate. Decentral Smart Grid Control (DSGC) was recently…
Smart grid technological advances present a recent class of complex interdisciplinary modeling and increasingly difficult simulation problems to solve using traditional computational methods. To simulate a smart grid requires a systemic…
The integration of machine learning into smart grid systems represents a transformative step in enhancing the efficiency, reliability, and sustainability of modern energy networks. By adding advanced data analytics, these systems can better…
This work presents a suite of two optimisation models for the short-term scheduling and redispatch of a virtual power plant (VPP) composed of a wind farm and a Li-ion battery, that participates in the day-ahead energy and secondary…
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…
In recent years, there has been a significant focus on advancing the next generation of power systems. Despite these efforts, persistent challenges revolve around addressing the operational impact of uncertainty on predicted data,…
This paper proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to…
This paper studies the problem of stochastic dynamic pricing and energy management policy for electric vehicle (EV) charging service providers. In the presence of renewable energy integration and energy storage system, EV charging service…
Motivated by demand-side management in smart grids, a decentralized controlled Markov chain formulation is proposed to model a homogeneous population of users with binary demands (i.e., off or on). The binary demands often arise in…
Increased uncertainty due to high penetration of renewables imposes significant costs to the system operators. The added costs depend on several factors including market design, performance of renewable generation forecasting and the…
A complex network can be characterized by patterns. Such frequently occurring significant patterns are called motifs and in a time dependent network, they are called temporal motifs. One of the temporal networks where temporal motifs are…
Emerging smart grid applications analyze large amounts of data collected from millions of meters and systems to facilitate distributed monitoring and real-time control tasks. However, current parallel data processing systems are designed…
Renewable-energy-based grids development needs new methods to maintain the balance between the load and generation using the efficient energy storages models. Most of the available energy storages models do not take into account such…
In this paper we introduce the problem of dynamic pricing of power for smart-grid networks. This is studied within a network utility maximization (NUM) framework in a deterministic setting with a single provider, multiple users and a finite…