A promising approach to hedge against the inherent uncertainty of renewable generation is to equip the renewable plants with energy storage systems. This paper focuses on designing profit maximization offering strategies, i.e., the strategies that determine the offering price and volume, for a storage-assisted renewable power producer that participates in hour-ahead electricity market. Designin...

The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL’s Derivatives Market is the existence of physical futures contracts; they imply the obligation to settle physically the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of t...

Price estimation is becoming increasingly relevant to producers and consumersin the new competitive electric power markets. Both for spot markets and short termcontracts, price forecasts are necessary to develop bidding strategies in order to maximizetheir benefits and utilities, respectively. Price estimation has become a very valuable toolin the current upheaval of electricity market deregula...

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Numerical results from a case study are presented to illustrate the performance of the proposed...

The integration of a high number of plug-in electric (PEV) vehicles could lead to overloads in the systems assets and demand peaks if the charge of the fleet is left uncontrolled. However, with the use of smart-charging strategies these problems could be avoided. In this work the development of a smartcharging strategy is presented. The goal of each electric vehicle, modeled as an agent, is to ...

Large-scale renewable energy suppliers and electric vehicles (EVs) are expected to become dominated participants in future electricity market. In this article, a competitive bidding strategy is formulated for wind power plants (WPPs) EV aggregators pool-based day-ahead A bilevel multiagent based model proposed study their behaviors, with market clearing completion the lower level revenue maximi...

Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional plants, storages, and demands. This paper proposes novel stochastic adaptive robust optimization (SARO) model for determining the optimal self-scheduling plan VPP’s participation in day-ahead energy-reserve market. We consider exogenou...

The market clearing pricing (MCP) model is used to operate electricity, gas, and heating networks (EGHNs) with flexible energy hubs (EHs) in the day-ahead market. It's two-level optimization. Its higher level refers EHs' participation their profit maximization bound by operational of power sources, storage devices, responsive loads form EHs flexibility limit. In lower-level problem, MCP calcula...

Within the framework of multi-stage mixed-integer linear stochastic programming we develop a short-term production plan for a price-taking hydropower plant operating under uncertainty. Current production must comply with the day-ahead commitments of the previous day which makes short-term production planning a matter of spatial distribution among the reservoirs of the plant. Day-ahead market pr...

This paper presents a day-ahead economic optimization scheduling model for Regional Electricity–Hydrogen Integrated Energy System (REHIES) with high penetration of renewable energies. The electricity–hydrogen coupling devices are modelled energy storage units and Insensitive Electrical Load (ISEL). proposed objective function is able to capture the maximum benefits REHIES in terms can be summar...