Related papers: A Novel Demand Response Model and Method for Peak …
Mobile power sources (MPSs) have been gradually deployed in microgrids as critical resources to coordinate with repair crews (RCs) towards resilience enhancement owing to their flexibility and mobility in handling the complex coupled…
Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in order to balance net demand in smart grids, involving trillions…
As electricity consumption grows, reducing peak demand--the maximum load on the grid--has become critical for preventing infrastructure strain and blackouts. Pricing mechanisms that incentivize consumers with flexible loads to shift…
This paper proposes a distributed framework for demand response and user adaptation in smart grid networks. In particular, we borrow the concept of congestion pricing in Internet traffic control and show that pricing information is very…
Traditional power grid systems have become obsolete under more frequent and extreme natural disasters. Reinforcement learning (RL) has been a promising solution for resilience given its successful history of power grid control. However,…
The implementation of a multi-microgrid (MMG) system with multiple renewable energy sources enables the facilitation of electricity trading. To tackle the energy management problem of a MMG system, which consists of multiple renewable…
This paper addresses a critical challenge in the high-speed passenger railway industry: designing effective dynamic pricing strategies in the context of competing and cooperating operators. To address this, a multi-agent reinforcement…
We design an optimal contract between a demand response aggregator (DRA) and power grid customers for incentive-based demand response. We consider a setting in which the customers are asked to reduce their electricity consumption by the DRA…
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…
We present a novel feedback protocol for wireless broadcast networks that utilize linear network coding. We consider transmission of packets from one source to many receivers over a single-hop broadcast erasure channel. Our method utilizes…
As representation learning becomes a powerful technique to reduce sample complexity in reinforcement learning (RL) in practice, theoretical understanding of its advantage is still limited. In this paper, we theoretically characterize the…
Demand response (DR) has been demonstrated to be an effective method for reducing peak load and mitigating uncertainties on both the supply and demand sides of the electricity market. One critical question for DR research is how to…
We study how high charging rate demands from electric vehicles (EVs) in a power distribution grid may collectively cause poor dynamic performance, and propose a price incentivization strategy to steer customers to settle for lesser charging…
The electricity market is threatened by supply scarcity, which may lead to very sharp price spikes in the spot market. On the other hand, demand-side's activities could effectively mitigate the supply scarcity and absorb most of these…
In auction markets that are prone to market power abuse, preventive mitigation of bid prices can be applied through automated mitigation procedures (AMP). Despite the widespread application of AMP in US electricity markets, there exists…
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…
Demand response involves system operators using incentives to modulate electricity consumption during peak hours or when faced with an incidental supply shortage. However, system operators typically have imperfect information about their…
We study a demand response problem from utility (also referred to as operator)'s perspective with realistic settings, in which the utility faces uncertainty and limited communication. Specifically, the utility does not know the cost…
A significant portion of a consumer's annual electrical costs can be made up of coincident peak charges: a transmission surcharge for power consumed when the entire system is at peak demand. This charge occurs only a few times annually, but…
The increasing share of volatile renewable electricity production motivates demand response. Substantial potential for demand response is offered by flexible processes and their local multi-energy supply systems. Simultaneous optimization…