Optimization of Wind Power Producer Participation in Electricity Markets with Energy Storage in a Way of Energy 4.0

This 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.

[1]  Paul Denholm,et al.  Role of Energy Storage with Renewable Electricity Generation , 2010 .

[2]  Víctor Manuel Fernandes Mendes,et al.  Bidding and optimization strategies for wind-PV systems in electricity markets assisted by CPS , 2016 .

[3]  Rui Laia,et al.  Optimal Bidding Strategies of Wind-Thermal Power Producers , 2016, DoCEIS.

[4]  Víctor Manuel Fernandes Mendes,et al.  Layered Smart Grid architecture approach and field tests by ZigBee technology , 2014 .

[5]  K. C. Divya,et al.  Battery Energy Storage Technology for power systems-An overview , 2009 .

[6]  K. Keramidas,et al.  A global stocktake of the Paris pledges: Implications for energy systems and economy , 2016 .

[7]  Víctor Manuel Fernandes Mendes,et al.  Services enabler architecture for smart grid and smart living services providers under industry 4.0 , 2017 .

[8]  Thijs Van de Graaf,et al.  Is OPEC dead? Oil exporters, the Paris agreement and the transition to a post-carbon world , 2017 .

[9]  Julio Usaola,et al.  Combined hydro-wind generation bids in a pool-based electricity market , 2009 .

[10]  A.M. Gonzalez,et al.  Stochastic Joint Optimization of Wind Generation and Pumped-Storage Units in an Electricity Market , 2008, IEEE Transactions on Power Systems.

[11]  Manfred Glesner,et al.  Embedded systems design for smart system integration , 2013, 2013 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).

[12]  G. Sheblé,et al.  Comparing Hedging Methods for Wind Power: Using Pumped Storage Hydro Units vs. Options Purchasing , 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.

[13]  Taner Arsan.  Smart Systems: From design to implementation of embedded Smart Systems , 2016, 2016 HONET-ICT.

[14]  Víctor Manuel Fernandes Mendes,et al.  Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market , 2017 .

[15]  Francisco Martínez-Álvarez,et al.  A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting , 2015 .

[16]  Hamidreza Zareipour,et al.  Energy storage for mitigating the variability of renewable electricity sources: An updated review , 2010 .

[17]  Víctor Manuel Fernandes Mendes,et al.  Self-scheduling and bidding strategies of thermal units with stochastic emission constraints , 2015 .

[18]  Víctor Manuel Fernandes Mendes,et al.  Bidding strategy of wind-thermal energy producers , 2016 .

[19]  Víctor Manuel Fernandes Mendes,et al.  Vanadium Redox Flow Battery Storage System Linked to the Electric Grid , 2016 .

[20]  Gail Rajgor.  Greater acceleration of renewables required to meet COP21 goal , 2016 .

[21]  Erin Baker,et al.  Evaluating energy storage technologies for wind power integration , 2012 .