A Near-Optimal Model-Based Control Algorithm for Households Equipped With Residential Photovoltaic Power Generation and Energy Storage Systems

2016 ◽  
Vol 7 (1) ◽  
pp. 77-86 ◽  
Author(s):  
Yanzhi Wang ◽  
Xue Lin ◽  
Massoud Pedram
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Control Algorithm ◽  
Storage Systems ◽  
Optimal Model ◽  
Energy Storage Systems ◽  
Model Based Control ◽  
Model Based ◽  
Photovoltaic Power

Application of battery energy storage systems in industrial facilities

2021 ◽  
Vol 61 (2) ◽  
pp. 563
Author(s):  
Hamed Sharafizad
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Spinning Reserve ◽  
Battery Energy Storage ◽  
Industrial Facilities ◽  
Battery Energy Storage Systems ◽  
Battery Energy ◽  
Storage Units

For any facility, reliability and availability of power are key. Traditional gas- or diesel-driven power generation designs for facilities rely on generated spinning reserve to achieve power system stability and availability for defined operational scenarios and expected transients. Spinning reserve is extra generating capacity that is usually introduced by running additional power generator(s). Battery energy storage systems (BESSs) as energy storage units provide for a virtual spinning reserve in a hot standby arrangement to achieve the same effect for a set period during operating scenarios and transient events. Use of BESS technology is becoming more frequent within electrical network systems, remote sites and industrial facilities on the back of improved battery technology. This lends itself to better BESS reliability, effectiveness and lower associated cost to procure and install. Many of Clough’s projects are remote and islanded where they need to be self-sufficient, generating and distributing their own power needs. BESS units are scalable energy storage systems that can be used as a part of power generation solutions for facilities installed onshore or offshore. In addition to supplementing the primary generation on a facility as static storage units, BESS units offer benefits such as reduced emissions on facilities by not burning fossil fuels to achieve spinning reserve; they also allow for power management of generation systems, store any excess power from primary generators, allow for integration of renewables, offer constructability benefits and reduced operational/maintenance costs. The commercial and environmental benefits of BESS units are key drivers in Clough’s decision to embrace their use on future projects.

scholarly journals Dimensioning Methodology of Energy Storage Systems for Power Smoothing in a Wave Energy Conversion Plant Considering Efficiency Maps and Filtering Control Techniques

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3380
Author(s):  
Jorge Torres ◽  
Marcos Blanco ◽  
Marcos Lafoz ◽  
Gustavo Navarro ◽  
Jorge Nájera ◽  
...  
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Energy Conversion ◽  
Wave Energy ◽  
Storage Systems ◽  
Wave Energy Conversion ◽  
Energy Storage Systems ◽  
Control Techniques ◽  
Power Oscillations ◽  
Selection Of

This paper aims at presenting and describing a dimensioning methodology for energy storage systems (ESS), in particular for one based on flywheels, applied for the specific application of reducing power oscillation in a wave energy conversion (WEC) plant. The dimensioning methodology takes into account the efficiency maps of the storage technology as well as the effect of the filtering control techniques. The methodology is applied to the case study of a WEC plant in operation in Spain, using real power generation profiles delivered into the electric grid. The paper firstly describes the calculation procedure of the efficiency maps for the particular technology of flywheels, although it could be extended to other storage technologies. Then, the influence of using future data values in the dimensioning process and the control of the ESS operation is analysed in depth. A moving average filter (MAF) is defined to compensate for power oscillations, studying the difference between considering prediction and not doing so. It is concluded that a filtering control using future values based on a number of samples equivalent to a 4-min time order provides an important reduction in the energy storage requirements for a power generation plant. Finally, and based on the selection of storage modules previously defined, the efficiency maps, and the MAF used for delivering the power into the grid, an optimal operation strategy is suggested for the storage modules, based on a stepped switching technique. The selection of four flywheel energy storage system (FESS) modules achieves a reduction of 50% in power oscillations, covering 85% of the frequency excursions at the grid.

scholarly journals Challenge from Transpower: Determining the effect of the aggregated behaviour of solar photovoltaic power generation and battery energy storage systems on grid exit point load in order to maintain an accurate load forecast

2020 ◽  
Vol 60 ◽  
pp. M1-M40
Author(s):  
Catherine Zoe Wollaston Hassell Sweatman ◽  
N. Wichitaksorn ◽  
A. Jiang ◽  
Troy Farrell ◽  
N. Bootland ◽  
...  
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Storage Systems ◽  
Exit Point ◽  
Solar Photovoltaic ◽  
Battery Energy Storage ◽  
Load Forecast ◽  
Photovoltaic Power ◽  
Battery Energy Storage Systems ◽  
Battery Energy

With limited data beyond the grid exit point (GXP) or substation level, how can Transpower determine the effect of the aggregated behaviour of solar photovoltaic power generation and battery energy storage systems on GXP load in order to maintain an accurate load forecast? In this initial study it is assumed that the GXP services a residential region. An algorithm based on non-linear programming, which minimises the financial cost to the consumer, is developed to model consumer behaviour. Input data comprises forecast energy requirements (load), solar irradiance, and pricing. Output includes both the load drawn from the grid and power returned to the grid. The algorithm presented is at the household level. The next step would be to combine the load drawn from the grid and the power returned to the grid from all the households serviced by a GXP, enabling Transpower to make load predictions. Various means of load forecasting are considered including the Holt--Winters methods which perform well for out-of-sample forecasts. Linear regression, which takes into account comparable days, solar radiation, and air temperature, yields even better performance.

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