© 2017 IEEE. Offering strategy of a price-maker demand response aggregator (DRA) in a two-settlement market is presented in this paper. The aggregator minimizes its cost by offering energy and price bids in the day-ahead market and energy bids in the balancing market. On the other hand, DRA optimally manages the aggregated demands of a large number of electric vehicles and properly distributes them through the time. The problem is formulated as a stochastic mixed-integer nonlinear optimization problem. The risk of the problem is managed by conditional value-at-risk measure and finally, the proposed approach is numerically evaluated through a detailed case study
This paper proposes a new trading framework which allows demand response (DR) aggregators to procure...
This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggrega...
This paper presents a methodology for determining the optimal portfolio allocation for a demand resp...
This paper evaluates the optimal bidding strategy for demand response (DR) aggregator in day-ahead (...
This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. T...
Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significan...
The penetration of distributed energy resources (DER), including distributed generators, storage dev...
This paper analyzes the bidding strategy problem of an electric vehicle aggregator that participate...
Abstract—In this paper, we consider the operation optimization for a microgrid (MG) aggregator which...
A risk-aware electricity retailer may alleviate concern about wholesale pool-price volatility throug...
An aggregator acts as a middleman between the small customers and the system operator (SO) offering ...
Recent years have witnessed a growing trend in the participation of renewable energy on the generati...
This paper proposes the problem of decision making of an electric vehicle (EV) aggregator in a compe...
Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, depart...
In power systems, demand and supply always have to be balanced. This is becoming more challenging du...
This paper proposes a new trading framework which allows demand response (DR) aggregators to procure...
This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggrega...
This paper presents a methodology for determining the optimal portfolio allocation for a demand resp...
This paper evaluates the optimal bidding strategy for demand response (DR) aggregator in day-ahead (...
This paper proposes a bottom-up model for demand response (DR) aggregators in electricity markets. T...
Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significan...
The penetration of distributed energy resources (DER), including distributed generators, storage dev...
This paper analyzes the bidding strategy problem of an electric vehicle aggregator that participate...
Abstract—In this paper, we consider the operation optimization for a microgrid (MG) aggregator which...
A risk-aware electricity retailer may alleviate concern about wholesale pool-price volatility throug...
An aggregator acts as a middleman between the small customers and the system operator (SO) offering ...
Recent years have witnessed a growing trend in the participation of renewable energy on the generati...
This paper proposes the problem of decision making of an electric vehicle (EV) aggregator in a compe...
Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, depart...
In power systems, demand and supply always have to be balanced. This is becoming more challenging du...
This paper proposes a new trading framework which allows demand response (DR) aggregators to procure...
This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggrega...
This paper presents a methodology for determining the optimal portfolio allocation for a demand resp...