Technical and economic design of photovoltaic and battery energy storage system

Bortolini, Marco; Gamberi, Mauro; Graziani, Augusto

doi:10.1016/j.enconman.2014.04.089

Cited by 241 publications

(114 citation statements)

References 49 publications

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“…This technology has advantages, such as high energy density, long service life, low operating cost, cleanness, and environmental friendliness. Furthermore, dynamic response characteristics of hydrogen storage systems are much better than traditional energy storage systems [22,23]. In this study, the hydrogen storage technology is applied to wind turbines for the virtual inertia control of wind farms, while maintaining the original operating state of wind power generators.…”

Section: Introductionmentioning

confidence: 99%

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

et al. 2018

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This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid's stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network.

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Section: Introductionmentioning

confidence: 99%

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

et al. 2018

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“…Based on prior studies, a number of approaches to optimizing the capacity of BESS are reported from several aspects, such as better utilization of PV [5] and reduction of generation costs [6]. The technical and economic model of the PV-battery [7] and lifecycle-based cost modeling for batteries [8] are also investigated. In the field of operation control, a power management mechanism for grid PV with BESS is designed [9].…”

Section: Introductionmentioning

confidence: 99%

Typical Daily Power Curve Mining for Energy Storage Systems under Smoothing Power Fluctuation Scenarios

Yang

Ren

et al. 2018

Mathematical Problems in Engineering

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Under the application scenario of smoothing photovoltaic (PV) power fluctuation, a novel typical daily power curve mining method is developed for a battery energy storage system (BESS) that utilizes the power probability distribution and Bloch spherical quantum genetic algorithm. The charging/discharging of BESS is analyzed by applying fuzzy-means clustering techniques. In the mining approach, at any sample time, those distribution intervals containing concentrated power points are individually located by using probability distribution information and Bloch spherical quantum genetic algorithm. Character power for the specified interval can also be determined using Bloch spherical quantum genetic algorithm. Next, a roulette principal is employed, to determine one value from the character power data as a typical value of the mined power curve at the sample time. By connecting the typical power at each sample time, the typical daily power curve for BESS is achieved. Based on typical power curve, decision-maker can master the important operating parameters of BESS and analyze optimal capacity allocation. By error evaluation indexes between the mined typical daily power curve and power curve under different weather patterns, the simulation results verify that the mined power curve can address the operating power of the BESS under different weather patterns.

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“…As such, an accurate prediction of PV power output is required to make better generation plans, support the spatial and temporal compensation, and achieve coordinated power control, so that the need for energy storage capacity and operating costs can be reduced [4]. Moreover, better prediction of PV power also helps to enhance system security and stability, as well as optimize the operation of the power system [5].…”

Section: Introductionmentioning

confidence: 99%

A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm

2017

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Abstract:With the increasing proportion of photovoltaic (PV) power in power systems, the problem of its fluctuation and intermittency has become more prominent. To reduce the negative influence of the use of PV power, we propose a short-term PV power prediction model based on the online sequential extreme learning machine with forgetting mechanism (FOS-ELM), which can constantly replace outdated data with new data. We use historical weather data and historical PV power data to predict the PV power in the next period of time. The simulation result shows that this model has the advantages of a short training time and high accuracy. This model can help the power dispatch department schedule generation plans as well as support spatial and temporal compensation and coordinated power control, which is important for the security and stability as well as the optimal operation of power systems.

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Technical and economic design of photovoltaic and battery energy storage system

Cited by 241 publications

References 49 publications

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

Typical Daily Power Curve Mining for Energy Storage Systems under Smoothing Power Fluctuation Scenarios

A Short-Term Photovoltaic Power Prediction Model Based on an FOS-ELM Algorithm

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