Related papers: Learning Large Electrical Loads via Flexible Contr…
Buildings represent a promising flexibility source to support the integration of renewable energy sources, as they may shift their heating energy consumption over time without impacting users' comfort. However, a building's predicted…
Understanding and predicting the electricity demand responses to prices are critical activities for system operators, retailers, and regulators. While conventional machine learning and time series analyses have been adequate for the routine…
In this paper, a novel economic approach, based on the framework of contract theory, is proposed for providing incentives for LTE over unlicensed channels (LTE-U) in cellular-networks. In this model, a mobile network operator (MNO) designs…
Demand flexibility can offset some of the variability introduced on the supply-side by variable renewable generation. However, most efforts (e.g. control of residential vehicle charging) focus on short durations -- typically on the scale of…
We study the optimal contract problem in the \emph{combinatorial actions} framework of D\"utting et al.~[FOCS'21], where a principal delegates a project to an agent who chooses a subset of hidden, costly actions, and the resulting reward is…
Context: Smart contracts are computerized self-executing contracts that contain clauses, which are enforced once certain conditions are met. Smart contracts are immutable by design and cannot be modified once deployed, which ensures…
Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to…
Smart contracts are a new paradigm that emerged with the rise of the blockchain technology. They allow untrusting parties to arrange agreements. These agreements are encoded as a programming language code and deployed on a blockchain…
The rise of smart contract systems such as Ethereum has resulted in a proliferation of blockchain-based decentralized applications including applications that store and manage a wide range of data. Current smart contracts are designed to be…
Demand flexibility is increasingly important for power grids, in light of growing penetration of renewable generation. Careful coordination of thermostatically controlled loads (TCLs) can potentially modulate energy demand, decrease…
Electricity market operators worldwide use mixed-integer linear programming to solve the allocation problem in wholesale electricity markets. Prices are typically determined based on the duals of relaxed versions of this optimization…
Compensation mechanisms are used to counterbalance the discomfort suffered by users due to quality service issues. Such mechanisms are currently used for different purposes in the electrical power and energy sector, e.g., power quality and…
Energy storage resources must consider both price uncertainties and their physical operating characteristics when participating in wholesale electricity markets. This is a challenging problem as electricity prices are highly volatile, and…
Edge computing allows Service Providers (SPs) to enhance user experience by placing their services closer to the network edge. Determining the optimal provisioning of edge resources to meet the varying and uncertain demand cost-effectively…
Recently, the mobile network operators (MNOs) are exploring more time flexibility with the rollover data plan, which allows the unused data from the previous month to be used in the current month. Motivated by this industry trend, we…
The deepening penetration of renewable energy is challenging how power system operators cope with the associated variability and uncertainty in the unit commitment problem. Given its computational complexity, several optimization-based…
In recent years, there is an emerging trend that some computing services are moving from cloud to the edge of the networks. Compared to cloud computing, edge computing can provide services with faster response, lower expense, and more…
Motivated by applications where a system must remain operational via continual procurement of contracts, we study two online contract selection problems under uncertain prices. At each time step, a price drawn from a known distribution is…
The integration of renewable energy resources (RES) in the power grid can reduce carbon intensity, but also presents certain challenges. The uncertainty and intermittent nature of RES emphasize the need for flexibility in power systems.…
A robust power scheduling algorithm is proposed to schedule power flow between the main electricity grid and a microgird with solar energy generation and battery energy storage subject to uncertainty in solar energy production. To avoid…