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Hector Beltran
Department of Industrial Systems Engineering and Design, Universitat Jaume I, Castelló de la Plana, Spain

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Journal article
Published: 12 November 2020 in Journal of Energy Storage
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Large photovoltaic (PV) power plants benefit from the introduction of batteries to increase their dispatchability. Among other services, batteries enable PV plants to firm their hourly energy production and avoid in this way the economic penalties associated with deviations between the contracted commitment made by the renewable generator to the grid and the final energy delivered. Due to the increase in the cost of the plant derived from the storage integration, the size of these batteries must be minimized. This work analyses the minimum battery capacity required for such a service when using a new deep-learning irradiance forecasting methodology. The low prediction error of the developed forecasting tool supports the optimized operation of large PV plants under different European intraday electricity markets with no deviations and reduced battery sizes. Results obtained for a whole year analysis using actual data at three different locations with varying irradiance patterns prove that 1-hour capacity batteries grant PV capacity firming in most intraday continuous market structures regardless of their lead times.

ACS Style

Hector Beltran; Javier Cardo-Miota; Jorge Segarra-Tamarit; Emilio Pérez. Battery size determination for photovoltaic capacity firming using deep learning irradiance forecasts. Journal of Energy Storage 2020, 33, 102036 .

AMA Style

Hector Beltran, Javier Cardo-Miota, Jorge Segarra-Tamarit, Emilio Pérez. Battery size determination for photovoltaic capacity firming using deep learning irradiance forecasts. Journal of Energy Storage. 2020; 33 ():102036.

Chicago/Turabian Style

Hector Beltran; Javier Cardo-Miota; Jorge Segarra-Tamarit; Emilio Pérez. 2020. "Battery size determination for photovoltaic capacity firming using deep learning irradiance forecasts." Journal of Energy Storage 33, no. : 102036.

Conference paper
Published: 01 September 2020 in 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES)
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This paper introduces an aggregated demand short-medium-term forecasting methodology based on calendar and temperature corrections that returns a very low relative error prediction when tested against actual demand values in the Iberian Electricity Market. The work introduces the market structure and the revealed importance of the demand on the electricity price, according to past correlations. Then, it introduces some of the most extended metrics in the literature being used for comparison among methodologies, as well as the databases consulted to obtain the required information. The performance of the proposed forecasting method is analysed against real data and compared with other simple proposal providing good results.

ACS Style

J. Segarra-Tamarit; E. Perez; E. Belenguer; J. Cardo-Miota; H. Beltran. Aggregated demand analysis and forescasting methodology for the Iberian Electricity Market. 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES) 2020, 1, 255 -260.

AMA Style

J. Segarra-Tamarit, E. Perez, E. Belenguer, J. Cardo-Miota, H. Beltran. Aggregated demand analysis and forescasting methodology for the Iberian Electricity Market. 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). 2020; 1 ():255-260.

Chicago/Turabian Style

J. Segarra-Tamarit; E. Perez; E. Belenguer; J. Cardo-Miota; H. Beltran. 2020. "Aggregated demand analysis and forescasting methodology for the Iberian Electricity Market." 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES) 1, no. : 255-260.

Journal article
Published: 02 July 2020 in Energies
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This paper provides the result of a techno-economic study of potential energy storage technologies deployable at wind farms to provide short-term ancillary services such as inertia response and frequency support. Two different scenarios are considered including a single energy storage system for the whole wind farm and individual energy storage for each wind turbine (located at either the dc or the ac side of its grid-side converter). Simulations are introduced to check the technical viability of the proposal with different control strategies. Power and energy capability requirements demanded by both specific services are defined for each studied case based on present and future grid code needs. Based on these requirements, the study compares a wide range of energy storage technologies in terms of present-day technical readiness and properties and identifies potential candidate solutions. These are flywheels, supercapacitors, and three chemistries out of the Li-ion battery family. Finally, the results of a techno-economic assessment (mainly based on weight, volume, lifetime, and industry-confirmed costings) detail the advantages and disadvantages of the proposed solutions for the different scenarios under consideration. The main conclusion is that none of the candidates are found to be clearly superior to the others over the whole range of scenarios. Commercially available solutions have to be tailored to the different requirements depending on the amount of inertia, maximum Rate of Change of Frequency and maximum frequency deviation to be allowed.

ACS Style

Hector Beltran; Sam Harrison; Agustí Egea-Àlvarez; Lie Xu. Techno-Economic Assessment of Energy Storage Technologies for Inertia Response and Frequency Support from Wind Farms. Energies 2020, 13, 3421 .

AMA Style

Hector Beltran, Sam Harrison, Agustí Egea-Àlvarez, Lie Xu. Techno-Economic Assessment of Energy Storage Technologies for Inertia Response and Frequency Support from Wind Farms. Energies. 2020; 13 (13):3421.

Chicago/Turabian Style

Hector Beltran; Sam Harrison; Agustí Egea-Àlvarez; Lie Xu. 2020. "Techno-Economic Assessment of Energy Storage Technologies for Inertia Response and Frequency Support from Wind Farms." Energies 13, no. 13: 3421.

Journal article
Published: 28 February 2020 in Mathematics and Computers in Simulation
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This paper analyses the economic profitability provided by different types of Li-ion batteries when used in residential solar applications under a Model Predictive Control that optimizes the operation of the system. The control methodology takes profit of actually commercial time-of-use rates to minimize the operation costs. Also, the analysis takes into account the progressive degradation of the batteries involved by using state-of-the-art semi-empirical ageing models. The study is performed by means of annual simulations that use actual consumption curves for three different households and real PV production batteries, with extended lifetime warranties and prices below 600 €/kWh, under optimized operation and use even when only energy arbitrage and peak shaving services are considered.

ACS Style

Pablo Ayuso; Hector Beltran; Jorge Segarra-Tamarit; Emilio Pérez. Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications. Mathematics and Computers in Simulation 2020, 183, 97 -115.

AMA Style

Pablo Ayuso, Hector Beltran, Jorge Segarra-Tamarit, Emilio Pérez. Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications. Mathematics and Computers in Simulation. 2020; 183 ():97-115.

Chicago/Turabian Style

Pablo Ayuso; Hector Beltran; Jorge Segarra-Tamarit; Emilio Pérez. 2020. "Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications." Mathematics and Computers in Simulation 183, no. : 97-115.

Journal article
Published: 24 January 2020 in Energies
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This paper analyses the degradation that is experienced by different types of Li-ion batteries when used as home solar storage systems controlled to minimize the electricity bill of the corresponding household. Simulating the annual operation of photovoltaic (PV) residential systems with batteries at different locations was undertaken to perform the study and it uses actual consumption values and real PV production profiles, as well as validated semi-empirical ageing models of the batteries. Therefore, the work provides a realistic prognosis around the lifetime expectancies for the different Li-ion chemistries.

ACS Style

Hector Beltran; Pablo Ayuso; Emilio Pérez. Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage. Energies 2020, 13, 568 .

AMA Style

Hector Beltran, Pablo Ayuso, Emilio Pérez. Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage. Energies. 2020; 13 (3):568.

Chicago/Turabian Style

Hector Beltran; Pablo Ayuso; Emilio Pérez. 2020. "Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage." Energies 13, no. 3: 568.

Conference paper
Published: 01 October 2019 in IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
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This work analyses the minimum energy capacity requirements to be demanded to battery energy storage systems used in megawatt-range merchant solar PV plants to grant capacity firming. The operation of such a plant is simulated (with a 2-minute time step, at three different locations of the Iberian Peninsula, and for different battery sizes) after solving a quadratic programming optimization problem. The control algorithm takes into account the irradiance forecast and the intraday electricity market configuration, which presents certain peculiarities in the Iberian region with regard to other European markets. The analysis has been performed in an annual basis and current irradiance measured values have been used.

ACS Style

J. Cardo-Miota; H. Beltran; P. Ayuso; J. Segarra-Tamarit; E. Perez. Optimized battery sizing for merchant solar PV capacity firming in different electricity markets. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 2019, 1, 2446 -2451.

AMA Style

J. Cardo-Miota, H. Beltran, P. Ayuso, J. Segarra-Tamarit, E. Perez. Optimized battery sizing for merchant solar PV capacity firming in different electricity markets. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. 2019; 1 ():2446-2451.

Chicago/Turabian Style

J. Cardo-Miota; H. Beltran; P. Ayuso; J. Segarra-Tamarit; E. Perez. 2019. "Optimized battery sizing for merchant solar PV capacity firming in different electricity markets." IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 1, no. : 2446-2451.

Journal article
Published: 09 January 2019 in IEEE Transactions on Energy Conversion
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ACS Style

Hector Beltran; Ivan Tomas Garcia; Jose Carlos Alfonso-Gil; Emilio Perez; Jose Carlos Alfonso. Levelized Cost of Storage for Li-Ion Batteries Used in PV Power Plants for Ramp-Rate Control. IEEE Transactions on Energy Conversion 2019, 34, 554 -561.

AMA Style

Hector Beltran, Ivan Tomas Garcia, Jose Carlos Alfonso-Gil, Emilio Perez, Jose Carlos Alfonso. Levelized Cost of Storage for Li-Ion Batteries Used in PV Power Plants for Ramp-Rate Control. IEEE Transactions on Energy Conversion. 2019; 34 (1):554-561.

Chicago/Turabian Style

Hector Beltran; Ivan Tomas Garcia; Jose Carlos Alfonso-Gil; Emilio Perez; Jose Carlos Alfonso. 2019. "Levelized Cost of Storage for Li-Ion Batteries Used in PV Power Plants for Ramp-Rate Control." IEEE Transactions on Energy Conversion 34, no. 1: 554-561.