A Weather-Based Optimal Storage Management Algorithm for PV Capacity Firming

Abdelrazek, Sherif; Kamalasadan, Sukumar

doi:10.1109/tia.2016.2598139

Cited by 28 publications

(8 citation statements)

References 14 publications

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“…In [16], distributed control using a consensus algorithm was used for voltage regulation, while localised control was used to maintain the battery energy storage systems (BESSs) state-of-charge (SoC) within the desired range. A dynamic programming algorithm was proposed in [17] to minimise output fluctuations in BESSs.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi‐objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

Hashemipour

Aghaei

Lotfi

et al. 2020

IET Renewable Power Generation

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The many well-established advantages of distributed generation (DG) make their usage in active distribution networks prevalent. However, uncontrolled operation of DG units can negatively interfere with the performance of other equipment, such as tap-changers, in addition to resulting in sub-optimal usage of their potential. Thus, adequate scheduling/ control of DG units is critical for operators of the distribution system to avoid those adverse effects. A linearised model of a multiobjective method for coordinating the operation of photovoltaics, battery storage systems, and tap-changers is proposed. Three objective functions are defined for simultaneously enhancing voltage profile, minimising power losses, and reducing peak load power. The formulated multi-objective problem is solved by means of the epsilon-constraint technique. A novel decision-making methodology is offered to find the Pareto optimality and select the preferred solution. To assess to proposed model's performance, it is tested using 33-bus IEEE test system. Consequently, tap-changers suffer lessened stress, the batteries stateof-charge is kept within adequate limits, and the DG units operation is at higher efficiency. The obtained results verify the effectiveness of this approach. P MPPT (t) maximum PV active power achievable using the MPPT algorithm P si solar irradiance (kW/m 2) f voltage deviation function u BESS binary variable (0-charging; 1-discharging)

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Section: Literature Reviewmentioning

confidence: 99%

Multi‐objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

Hashemipour

Aghaei

Lotfi

et al. 2020

IET Renewable Power Generation

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show abstract

“…[ 25 ] Therefore, the degradation of the batteries is a hot topic in this field and a key parameter in the profitability analyses of hybrid plants. Altogether, although references can be identified in the literature with titles specifically concerning the use of batteries to firm the production of large PV plants, [ 26,27 ] none of the works published so far analyzed the influence of the electricity market structure on the aging of the batteries used for PV firming. This is the main contribution successfully developed in this work.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Intraday Electricity Market Structure on the Degradation of Li‐Ion Batteries Used to Firm Photovoltaic Production

et al. 2022

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This article considers the introduction of Li‐ion batteries in photovoltaic power plants to firm their energy production and analyzes the dependence of their degradation on the structure of the electricity market where the power production is traded. The operation of the batteries is decided as a result of successive optimization problems that benefit from the use of deep‐learning‐based irradiance forecasting tools with low prediction error, which allows the batteries to keep a small size. In addition, state‐of‐the‐art battery aging models are handled to derive a realistic lifetime prognosis. The simulation results obtained by using real data from three European locations, which have different irradiance patterns and market structures, show how the proposed control strategy makes it possible to decouple the saturation rate of the batteries from the climatic conditions of the plant location. Furthermore, regarding the market structure, the results show that the shorter the energy block and the closer the lead time, the lower is the degradation of the batteries.

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“…However, these are not combined with BESS sizing problems. On the contrary, BESS sizing paper proposals which take into account some kind of RES uncertainty usually adopt very simple forecasting models [42,43].…”

Section: Introductionmentioning

confidence: 99%

“…This implies using accurate irradiance forecasting techniques such as those based on deep-neural networks (DNN) [46]. Then, although some of the works in the literature present titles engaging BESS and PV capacity firming [42,47,48] none of them nor any of the previously cited works proposes the use of any kind of DNN-based forecasting approach in order to profit the low prediction error achieved nowadays with such algorithms [49,50] to analyze the minimum energy requirements of the BESS introduced in a PV power plant to grant capacity firming while traded in different intraday electricity markets. This is the main proposal successfully developed in this work.…”

Section: Introductionmentioning

confidence: 99%

Battery size determination for photovoltaic capacity firming using deep learning irradiance forecasts

Beltrán

Cardo-Miota

Segarra-Tamarit

et al. 2021

Journal of Energy Storage

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A Weather-Based Optimal Storage Management Algorithm for PV Capacity Firming

Cited by 28 publications

References 14 publications

Multi‐objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

Multi‐objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

Influence of the Intraday Electricity Market Structure on the Degradation of Li‐Ion Batteries Used to Firm Photovoltaic Production

Battery size determination for photovoltaic capacity firming using deep learning irradiance forecasts

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