Loading...
4 results
Search Results
Now showing 1 - 4 of 4
- Wind power with energy storage arbitrage in day-ahead market by a stochastic MILP approachPublication . Gomes, Isaías; Melício, R.; Mendes, Victor; Pousinho, H. M. I.This paper is about a support information management system for a wind power (WP) producer having an energy storage system (ESS) and participating in a day-ahead electricity market. Energy storage can play not only a leading role in mitigation of the effect of uncertainty faced by a WP producer, but also allow for conversion of wind energy into electric energy to be stored and then released at favourable hours. This storage provides capability for arbitrage, allowing an increase on profit of a WP producer, but must be supported by a convenient problem formulation. The formulation proposed for the support information management system is based on an approach of stochasticity written as a mixed integer linear programming problem. WP and market prices are considered as stochastic processes represented by a set of scenarios. The charging/discharging of the ESS are considered dependent on scenarios of market prices and on scenarios of WP. The effectiveness of the proposed formulation is tested by comparison of case studies using data from the Iberian Electricity Market. The comparison is in favour of the proposed consideration of stochasticity.
- Optimization of wind power producer participation in electricity markets with energy storage in a way of energy 4.0Publication . Gomes, Isaías; Pousinho, Hugo M. I.; Melicio, Rui; Mendes, VictorThis paper proposes a problem formulation to aid as a support information management system of a wind power producer having energy storage devices and participating in electricity markets. Energy storage can play an important role in the reduction of uncertainties faced by a wind power producer. Excess of conversion of wind energy into electric energy can be stored and then released at favorable hours. Energy storage provides capability for arbitrage and increases the revenue of the wind power producers participating in electricity markets. The formulation models the wind power and the market prices as stochastic processes represented by a set of convenient scenarios. The problem is solved by a powerful stochastic mixed integer linear programming problem. A case study using data from the Iberian Electricity Market is presented to show the aid of the formulation.
- A novel microgrid support management system based on stochastic mixed-integer linear programmingPublication . Gomes, Isaías; Melício, R.; Mendes, VictorThis paper focuses on a support management system for the management and operation planning of a microgrid by the new electricity market agent, the microgrid aggregator. The aggregator performs the management of microturbines, wind and photovoltaic systems, energy storage, electric vehicles, and usage of energy aiming at having the best participation in the market. Nowadays, the electricity market participation entails making decisions aided by a support and information system, which is an important part of a microgrid support management system. The microgrid support management system developed in this paper has a formulation based on a stochastic mixed-integer linear programming problem that depends on knowledge of the stochastic processes that describe the uncertain parameters. A set of plausible scenarios computed by Kernel Density Estimation sets the characterization of the random variables. But as commonly happen, a scenario reduction is necessary to avoid the need to have significant computational requirements due to the high degree of uncertainty. The scenario reduction carried out is a two-tier procedure, following a K-means clustering technique and a fast backward scenario reduction method. The case studies reveal the performance of the microgrid and validate the methodology basis conceived for the microgrid support management system.
- Dust effect impact on PV in an aggregation with wind and thermal powersPublication . Gomes, Isaías; Melicio, Rui; Mendes, VictorThis paper is about the dust effect impact on photovoltaic systems on the profit of an electricity market agent acting as an aggregator of photovoltaic power, wind power, thermal power, and an energy storage system. Energy storage ensures arbitrage and smoothing of the variability of photovoltaic power and wind power. The market agent intends to derive bids for submission in a day-ahead market, having consideration of the dust effect impact on the photovoltaic power. A formulation is proposed for a support decision system by a profit-based unit commitment problem solved by a stochastic programming approach, considering the operating characteristics of the virtual power plant. The photovoltaic power, wind power, and market price uncertainties are input data derived from scenarios of historical data. Case studies addressed show the advantages of the stochastic programming approach and insights concerned with the integration of uncertainties within the modeling for the schedule of the energy storage system and the dust effect impact on profit.