Related papers: Day-Ahead Offering for Virtual Power Plants: A Sto…
We investigate the problem of serving deferrable and nondeferrable electric demands with colocated stochastic supply and grid-imported electricity. Deferrable demands arrive randomly and can be delayed within their service deadlines.…
This paper proposes a novel reserve-minimizing and allocation strategy for virtual power plants (VPPs) to deliver optimal frequency support. The proposed strategy enables VPPs, acting as aggregators for inverter-based resources (IBRs), to…
With the proliferation of distributed energy resources (DERs) in the distribution grid, it is a challenge to effectively control a large number of DERs resilient to the communication and security disruptions, as well as to provide the…
This paper addresses a central challenge of jointly considering shorter-term (e.g. hourly) and longer-term (e.g. yearly) uncertainties in power system planning with increasing penetration of renewable and storage resources. In conventional…
The increasing penetration of variable renewable energy (VRE) has brought significant challenges for power systems planning and operation. These highly variable sources are typically distributed in the grid; therefore, a detailed…
Several approaches have been proposed to forecast day-ahead locational marginal price (daLMP) in deregulated energy markets. The rise of deep learning has motivated its use in energy price forecasts but most deep learning approaches fail to…
Strategic bidding problems in electricity markets are widely studied in power systems, often by formulating complex bi-level optimization problems that are hard to solve. The state-of-the-art approach to solve such problems is to…
The increasing penetration of distributed energy resources has sparked interests in participating in power markets. Here, we consider two settings where Virtual Power Plants (VPPs) with some flexible resources participate in the electricity…
Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With the new FERC 2222 order, DER aggregations are allowed to…
Resource-constrained project scheduling problems (RCPSP) are at the heart of many production planning problems across a plethora of applications. Although the problem has been studied since the early 1960s, most developments and test…
During the last years, European intraday power markets have gained importance for balancing forecast errors due to the rising volumes of intermittent renewable generation. However, compared to day-ahead markets, the drivers for the intraday…
This paper presents a method to handle renewable source and load uncertainties in Dynamic Day-ahead Optimal Power Flow (DA-OPF) using post-optimal analysis of linear programming problem. The method does not require the uncertainty…
The establishment of a single European day-ahead market has accomplished the integration of the regional day-ahead markets. However, the reserves provision and activation remain an exclusive responsibility of regional operators. This…
The implementation of electricity markets based on locational marginal pricing in a multi-settlement process has allowed wholesale competition, with pricing mechanisms that incentivize the optimal allocation of generation, transmission, and…
The growing importance of intraday electricity trading in Europe calls for improved price forecasting and tailored decision-support tools. In this paper, we propose a novel generative neural network model to generate probabilistic path…
This paper presents a flexible and modular control scheme based on distributed model predictive control (DMPC) to achieve optimal operation of decentralized energy systems in smart grids. The proposed approach is used to coordinate multiple…
We address the problem of controlling the reactive power setpoints of a set of distributed energy resources (DERs) in a power distribution network so as to mitigate the impact of variability in uncontrolled power injections associated with,…
We introduce a general, simple, and computationally efficient framework for predicting day-ahead supply and demand merit-order curves, from which both point and probabilistic electricity price forecasts can be derived. We conduct a rigorous…
This paper proposes an optimal strategy for a Renewable Energy Community participating in the Italian pay-as-bid ancillary service market. The community is composed by a group of residential customers sharing a common facility equipped with…
There has been widespread interest in the use of grid-level storage to handle the variability from increasing penetrations of wind and solar energy. This problem setting requires optimizing energy storage and release decisions for anywhere…