Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market

This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of...

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Vydané v:Energy (Oxford) Ročník 124; s. 310 - 320
Hlavní autori: Gomes, I.L.R., Pousinho, H.M.I., Melício, R., Mendes, V.M.F.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 01.04.2017
Elsevier BV
Predmet:
Batteries
case studies
Day-ahead market
Electric power systems
Electricity
Electricity pricing
Energy conversion
Energy flow
Energy storage
Joint operation
market prices
Markets
Photovoltaic cells
Photovoltaics
PV power
Rechargeable batteries
Renewable energy
renewable energy sources
solar collectors
Stochastic linear programming
uncertainty
Wind
Wind power
Wind power generation
Joint operation
Day-ahead market
PV power
Stochastic linear programming
Wind power
Energy storage
ISSN:0360-5442, 1873-6785
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Shrnutí:This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed. •Joint wind and PV systems with energy storage.•Electricity markets.•Stochastic optimization.•Day-ahead market.
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ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2017.02.080