A AGREGAÇÃO OTIMIZADA DA PRODUÇÃO RENOVÁVEL DISTRIBUÍDA

Funder

Organizational Unit

Publications

From Wind to Hybrid: A Contribution to the Optimal Design of Utility-Scale Hybrid Power Plants

Publication . Silva, Ana Rita; Estanqueiro, Ana

ABSTRACT: When a substantial number of wind parks are approaching the end of their lifespan, and developers of renewables are facing decisions about what to do with their assets, concepts such as hybrid power plants are emerging as a promising solution to enable renewable integration in a cost-effective and robust manner. This work proposes a decision-aid algorithm to perform a comprehensive analysis of hybrid power plants, focusing on the energetic contribution and economic feasibility of converting existing wind power plants into hybrid power plants (i.e., installing photovoltaic panels and a storage system). The analysis was performed by comparing the option of converting existing wind plants into hybrid plants with a pure repowering exercise or overplanting using wind technology only. The obtained results unequivocally demonstrate the added value of hybrid power plants as they promote: (i) a higher installed capacity and yearly capacity factor (up to 50%); (ii) an increased efficiency of existing electric infrastructures; and (iii) a positive contribution to a sustainable energy system with the ability to generate economic value.

2022-04Journal article

Open access

A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets

Publication . Silva, Ana Rita; Pousinho, H. M. I.; Estanqueiro, Ana

ABSTRACT: Market agents with renewable resources face amplified uncertainty when forecasting energy production to securely place bids in electricity markets. To deal with uncertainties, stochastic modelling has been applied to optimize the bidding strategy of these market agents. However, studies found in the literature usually focus on day-ahead and balancing markets, leaving aside intraday markets that could be used to correct bidding positions as uncertainty gets resolved. This paper proposes a multistage stochastic decision-aid algorithm based on linear programming to optimize the bidding strategy of market agents in three different electricity markets -day-ahead, intraday, and balance markets. The market agent represents a Virtual Power Plant with wind, solar PV, and storage technologies, and its participation in three electricity markets was compared to the participation in DA and BM markets only. Results show that participating in all three markets increased the profit achieved by the VPP agent by 10.1% while also decreasing the incurred imbalances by 63.8%. The results demonstrate that having accurate tools to deal with the multi-settlement framework of electricity markets while considering the uncertainties of daily operations is key to a successful integration of renewable energy resources into electricity markets and power systems.

2022-11Journal article

Open access