The combined value of wind and solar power forecasting improvements and electricity storage

Hodge, B. M.; Kumler, Andrew; Wang, Qin; Chartan, Erol Kevin; Florita, Anthony; Kiviluoma, Juha

doi:10.1016/j.apenergy.2017.12.120

Cited by 91 publications

(31 citation statements)

References 29 publications

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“…Improved and/or integrated forecasts of wind, solar, and water (for hydropower and pumped storage) support decision-making and optimization of power generation and storage (charging and discharging), as well as energy market operations (Hodge et al 2018). Improved forecasting of temperature, irradiance, and wind speed and direction can support dynamic transmission line rating.…”

Section: Innovations To Increase System Valuementioning

confidence: 99%

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

Dykes

Veers

Lantz

et al. 2019

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Research advanced erosion-resistant composite materials for use on the leading edge of wind turbine blades Research, development, and scale-up of thermoplastic resin systems to reduce wind turbine blade manufacturing cycle times, reduce blade costs, enable thermal welding of bond lines, increase recyclability, and enable advanced in-field blade repair techniques Research advanced thermoset materials that can be recovered and reused Research metals and other noncomposite materials for development of lightweight, high-strength, and high-stiffness turbine components Grand Challenge 2: Automation Develop comprehensive techno-economic models for automation and a virtual factory (or digital twin of a factory) to understand advantages and disadvantages of targeted automation for both wind turbine blade molding and finishing operations Identify and quantify all cost inputs for wind turbine component manufacturing (e.g., blades, towers) to identify production steps that would benefit from automation Develop automated production methods for the continuous manufacturing of one-piece wind turbine towers for on-site manufacturing Develop advanced design tools to optimize blade and tower design with respect to manufacturing with automation Research and develop automation technology able to locate complex wind turbine blade geometry in space to allow for effective automated finishing operations, such as sanding, drilling, and cutting Develop methods to automate the delivery, placement, and inspection of core material into blade skin molds during the composite laminate skin lay-up Integrate real-time inspection and quality control into automated production steps for wind turbine blades, towers, and other components Develop large-scale, low-cost, high-throughput, high-performance automated additive manufacturing technologies (e.g., 3D printing, automated fiber placement and tape layup, filament winding) for the production of towers, blade skins, blade spars, and other turbine components Develop embedded metrology and out-of-mold indexing technologies Grand Challenge 3: On-Site Manufacturing Develop robust composite materials for use in broad on-site environmental conditions Research the chemistry and processing of in-situ thermoplastic resin systems to enable thermally welded joints in an on-site manufacturing environment Develop targeted wind turbine blade finishing automation techniques designed to reduce the overall footprint of on-site finishing operations and minimize production facility floor space Research additive manufacturing to print wind turbine blade molds and tooling at on-site manufacturing locations IEA Wind TCP Task 11

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Section: Innovations To Increase System Valuementioning

confidence: 99%

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

Dykes

Veers

Lantz

et al. 2019

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“…PV p (t) + WT p (t) + P ds b (t) − P ch b (t) = PL(t) for case 1 (15) where PL is the load demand, P ds b (t) and P ch b (t) is the BESS discharging and charging power.…”

Section: Constraintsmentioning

confidence: 99%

“…A precise outlook of the expected generated power profile helped the system operator to achieve an efficient flexibility option for reliable operation planning by the utilities [13,14]. This involves intelligently scheduling the BESS operation to charge during peak generation periods and supplement the grid deficiencies during low power generation hours [15].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Techno-Economic Benefits of Flexible Demand Resources Scheduling for Renewable Energy–Based Smart Microgrid Planning

et al. 2019

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The need for innovative pathways for future zero-emission and sustainable power development has recently accelerated the uptake of variable renewable energy resources (VREs). However, integration of VREs such as photovoltaic and wind generators requires the right approaches to design and operational planning towards coping with the fluctuating outputs. This paper investigates the technical and economic prospects of scheduling flexible demand resources (FDRs) in optimal configuration planning of VRE-based microgrids. The proposed demand-side management (DSM) strategy considers short-term power generation forecast to efficiently schedule the FDRs ahead of time in order to minimize the gap between generation and load demand. The objective is to determine the optimal size of the battery energy storage, photovoltaic and wind systems at minimum total investment costs. Two simulation scenarios, without and with the consideration of DSM, were investigated. The random forest algorithm implemented on scikit-learn python environment is utilized for short-term power prediction, and mixed integer linear programming (MILP) on MATLAB® is used for optimum configuration optimization. From the simulation results obtained here, the application of FDR scheduling resulted in a significant cost saving of investment costs. Moreover, the proposed approach demonstrated the effectiveness of the FDR in minimizing the mismatch between the generation and load demand.

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“…This is an optimisation exercise which minimises total system costs by incorporating all relevant technical and financial operational characteristics of the supply and demand-side resources present in the power system. The approach taken is similar to that in (Hodge et al, 2018;Wang et al, 2016). The production-cost model applies a two-step sequential approach to quantify the value of the VRE forecast initially.…”

Section: Modelling Approach 31 System Level Valuation Of Improved Vrementioning

confidence: 99%

Assessing the value of improved variable renewable energy forecasting accuracy in the South African power system

Wright

Landwehr²,

Chartan

2019

J. energy South. Afr.

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The value associated with an improved variable renewable energy (VRE) forecast has been quantified in this research. The value of improved VRE forecasts can increase with increasing VRE penetration levels as well as the range of this value becoming wider. This value also saturates with high levels of improved VRE forecasts as there is relatively lower impact of improving VRE forecasts further. This paper discusses how the improvement of VRE forecasting could impact the South African power system and representative United States power system jurisdictions.

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The combined value of wind and solar power forecasting improvements and electricity storage

Cited by 91 publications

References 29 publications

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

Assessing the Techno-Economic Benefits of Flexible Demand Resources Scheduling for Renewable Energy–Based Smart Microgrid Planning

Assessing the value of improved variable renewable energy forecasting accuracy in the South African power system

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