Economic Evaluation of Wind Farms Based on Cost of Energy Optimization

2010 ◽  
Author(s):  
Jie Zhang ◽  
Achille Messac ◽  
Souma Chowdhury ◽  
Luciano Castillo
Keyword(s):  
Economic Evaluation ◽  
Energy Optimization ◽  
Wind Farms ◽  
Cost Of Energy

Levelised cost of energy analysis for offshore wind farms – A case study of the New York State development

2021 ◽  
Vol 239 ◽  
pp. 109923
Author(s):  
Yibo Liang ◽  
Yu Ma ◽  
Haibin Wang ◽  
Ana Mesbahi ◽  
Byongug Jeong ◽  
...  
Keyword(s):  
New York ◽  
Energy Analysis ◽  
New York State ◽  
Wind Farms ◽  
Offshore Wind ◽  
State Development ◽  
Offshore Wind Farms ◽  
York State ◽  
Cost Of Energy

A Levelized Cost of Energy (LCOE) Model for Wind Farms That Includes Power Purchase Agreement (PPA) Energy Delivery Limits

2016 ◽  
Author(s):  
Maira Bruck ◽  
Navid Goudarzi ◽  
Peter Sandborn
Keyword(s):  
Wind Farm ◽  
Cost Model ◽  
Wind Farms ◽  
Cost Models ◽  
Renewable Energy Resources ◽  
Supply Source ◽  
Levelized Cost ◽  
Cost Of Energy ◽  
Expected Performance ◽  
The Cost

The cost of energy is an increasingly important issue in the world as renewable energy resources are growing in demand. Performance-based energy contracts are designed to keep the price of energy as low as possible while controlling the risk for both parties (i.e., the Buyer and the Seller). Price and risk are often balanced using complex Power Purchase Agreements (PPAs). Since wind is not a constant supply source, to keep risk low, wind PPAs contain clauses that require the purchase and sale of energy to fall within reasonable limits. However, the existence of those limits also creates pressure on prices causing increases in the Levelized Cost of Energy (LCOE). Depending on the variation in capacity factor (CF), the power generator (the Seller) may find that the limitations on power purchasing given by the utility (the Buyer) are not favorable and will result in higher costs of energy than predicted. Existing cost models do not take into account energy purchase limitations or variations in energy production when calculating an LCOE. A new cost model is developed to evaluate the price of electricity from wind energy under a PPA contract. This study develops a method that an energy Seller can use to negotiate delivery penalties within their PPA. This model has been tested on a controlled wind farm and with real wind farm data. The results show that LCOE depends on the limitations on energy purchase within a PPA contract as well as the expected performance characteristics associated with wind farms.

scholarly journals Sensitivity analysis on the levelized cost of energy for floating offshore wind farms

2018 ◽  
Vol 30 ◽  
pp. 77-90 ◽  
Author(s):  
Markus Lerch ◽  
Mikel De-Prada-Gil ◽  
Climent Molins ◽  
Gabriela Benveniste
Keyword(s):  
Sensitivity Analysis ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Levelized Cost ◽  
Cost Of Energy

scholarly journals Wind Farm Layout Upgrade Optimization

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2465 ◽  
Author(s):  
Mamdouh Abdulrahman ◽  
David Wood
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Lower Cost ◽  
Wind Farms ◽  
Offshore Wind ◽  
General Representation ◽  
Thrust Coefficient ◽  
Wind Farm Layout ◽  
Cost Of Energy ◽  
Wide Range

The problem of optimally increasing the size of existing wind farms has not been investigated in the literature. In this paper, a proposed wind farm layout upgrade by adding different (in type and/or hub height) commercial turbines to an existing farm is introduced and optimized. Three proposed upgraded layouts are considered: internal grid, external grid, and external unstructured. The manufacturer’s power curve and a general representation for thrust coefficient are used in power and wake calculations, respectively. A simple field-based model is implemented and both offshore and onshore conditions are considered. A genetic algorithm is used for the optimization. The trade-off range between energy production and cost of energy is investigated by considering three objective functions, individually: (1) annual energy production; (2) cost of added energy; and (3) cost of total energy. The proposed upgraded layouts are determined for the Horns Rev 1 offshore wind farm. The results showed a wide range of suitable upgrade scenarios depending on the upgraded layout and the optimization objective. The farm energy production is increased by 190–336% with a corresponding increase in the total cost by 147–720%. The external upgrade offers more energy production but with much more cost. The unstructured layouts showed clear superiority over the grid ones by providing much lower cost of energy.

scholarly journals Complementarity Roses Evaluating Spatial Complementarity in Time between Energy Resources

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1918 ◽  
Author(s):  
Alfonso Risso ◽  
Alexandre Beluco ◽  
Rita Marques Alves
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Wind Farms ◽  
Renewable Resource ◽  
Energy Resources ◽  
Complete Evaluation ◽  
Hybrid Energy ◽  
Available Energy ◽  
Cost Of Energy ◽  
The Cost

Hybrid energy systems have higher initial costs than systems that are based on only one renewable resource, but allow for the fulfillment of the demands of consumer loads with lower values for the cost of energy. The possible complementarity between the resources used can contribute to a better use of the available energy. On a large scale, complementarity between power plants can serve as a tool for the management of energy resources. A complete evaluation of complementarity needs to consider three components: time complementarity, energy complementarity, and complementarity between amplitudes of variation. Complementarity can also be assessed between energy resources in one place (which may be termed temporal complementarity) and between resources at different sites (termed spatial complementarity). This paper proposes a method for quantifying spatial complementarity over time and for its expression through maps. The method suggests the establishment of a hexagonal network of cells and the determination of complementary roses for each cell that contains power plants. This article also applies the method proposed to some hydroelectric plants and wind farms in the State of Rio Grande do Sul, in southern Brazil, and present the map of spatial complementarity in time obtained.

scholarly journals Floating Offshore Wind Farms in Italy beyond 2030 and beyond 2060: Preliminary Results of a Techno-Economic Assessment

2020 ◽  
Vol 10 (24) ◽  
pp. 8899
Author(s):  
Laura Serri ◽  
Lisa Colle ◽  
Bruno Vitali ◽  
Tullia Bonomi
Keyword(s):  
Wind Turbines ◽  
Weighted Average ◽  
Wind Farms ◽  
Economic Assessment ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Cost Of Energy ◽  
Cost Reductions ◽  
Marine Areas ◽  
Wind Resource

At the end of 2019, 10.5 GW of wind capacity was installed in Italy, all onshore. The National Integrated Climate and Energy Plan sets a target of 18.4 GW of onshore wind capacity and 0.9 GW of offshore wind capacity by 2030. Significant exploitation of offshore wind resources in Italy is expected after 2030, using floating wind turbines, suitable for water depths greater than 50 m. This technology is at the demonstration phase at present. Results of a preliminary techno-economic assessment of floating wind plants in Italian marine areas in a medium (2030) and long-term (2060) scenario are presented. In 2030, a reference park with 10 MW wind turbines will be defined, and parametric costs, depending on distance from shore, were assessed. In 2060, possible wind resource variations due to climate change, and cost reductions due to large diffusion of the technology were considered in three case studies. The economic model used was the simple Levelized Cost of Energy (sLCoE). Different values of Weighted Average Cost of Capital (WACC) were considered too. The results show LCoEs comparable to the ones expected for the sector in 2030. In 2060, even in the more pessimistic scenario, wind resource decreases will be abundantly compensated by expected cost reductions.

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