Assessment of the apparent performance characterization along with levelized cost of energy of wind power plants considering real data

Hulio, Zahid Hussain; Jiang, Wei

doi:10.1177/0144598718767596

Cited by 13 publications

(10 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 11 shows the cumulative cost of solar generation and battery storage versus FR. From the results, it is observed that as FR increases from 60 to 77%, capital cost reduces with the cost of storage and solar generation using Equations (10), (11), and (15). It implies that with a smaller population, storage and solar generation can satisfy prosumers' load demands within a blockchain-based decentralized infrastructure.…”

Section: Variation Of Load Demand With Respect To Frmentioning

confidence: 93%

“…However, the performance of photovoltaic (PV) technology for short and long term range with reliable information is not provided by the study in Mauritius. In Pakistan [15], LCOE is used to determine the performance of wind farms in terms of the average capacity of 34.50%, real availability of 90% and 97% of technical performance. The costs of 0.113 $/kWh and 0.040 $/kWh for 1-10 and 11-20 years are estimated from LCOE.…”

Section: Least-cost Evaluation For Decentralized Electrification In Sgmentioning

confidence: 99%

“…Results of Figures 5-8 show that prosumers can achieve low energy costs, if the proposed mechanism is implemented. Additionally, low reliability premium is achieved with minimum BLCOE for prosumers with less variability in the component cost using Equation (15). Furthermore, using Equations (14), (16), and (17), countries can decide which models best suit their energy needs.…”

Section: Research Implicationsmentioning

confidence: 99%

“…A cost-effective energy planning model is used to compare the energy generation capacity of a CES with the options of DES that often consider solar with battery storage [2]. brown Several energy planning models were proposed in the literature to provide cost-effective solutions to classes of DES for different countries [12][13][14][15][16][17][18]; however, their focus was on isolated geographical locations. Although, the authors of [19] have proposed a model for energy planning for multiple SSA locations.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Leveraging Blockchain Technology for Secure Energy Trading and Least-Cost Evaluation of Decentralized Contributions to Electrification in Sub-Saharan Africa

Dahunsi

Almogren

Javaid

et al. 2020

Entropy

View full text Add to dashboard Cite

The International Energy Agency has projected that the total energy demand for electricity in sub-Saharan Africa (SSA) is expected to rise by an average of 4% per year up to 2040. It implies that~620 million people are living without electricity in SSA. Going with the 2030 vision of the United Nations that electricity should be accessible to all, it is important that new technology and methods are provided. In comparison to other nations worldwide, smart grid (SG) is an emerging technology in SSA. SG is an information technology-enhanced power grid, which provides a two-way communication network between energy producers and customers. Also, it includes renewable energy, smart meters, and smart devices that help to manage energy demands and reduce energy generation costs. However, SG is facing inherent difficulties, such as energy theft, lack of trust, security, and privacy issues. Therefore, this paper proposes a blockchain-based decentralized energy system (BDES) to accelerate rural and urban electrification by improving service delivery while minimizing the cost of generation and addressing historical antipathy and cybersecurity risk within SSA. Additionally, energy insufficiency and fixed pricing schemes may raise concerns in SG, such as the imbalance of order. The paper also introduces a blockchain-based energy trading system, which includes price negotiation and incentive mechanisms to address the imbalance of order. Moreover, existing models for energy planning do not consider the effect of fill rate (FR) and service level (SL). A blockchain levelized cost of energy (BLCOE) is proposed as the least-cost solution that measures the impact of energy reliability on generation cost using FR and SL. Simulation results are presented to show the performance of the proposed model and the least-cost option varies with relative energy generation cost of centralized, decentralized and BDES infrastructure. Case studies of Burkina Faso, Cote d'Ivoire, Gambia, Liberia, Mali, and Senegal illustrate situations that are more suitable for BDES. For other SSA countries, BDES can cost-effectively service a large population and regions. Additionally, BLCOE reduces energy costs by approximately 95% for battery and 75% for the solar modules. The future BLCOE varies across SSA on an average of about 0.049 $/kWh as compared to 0.15 $/kWh of an existing system in the literature.

show abstract

Section: Variation Of Load Demand With Respect To Frmentioning

confidence: 93%

Section: Least-cost Evaluation For Decentralized Electrification In Sgmentioning

confidence: 99%

Section: Research Implicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Leveraging Blockchain Technology for Secure Energy Trading and Least-Cost Evaluation of Decentralized Contributions to Electrification in Sub-Saharan Africa

Dahunsi

Almogren

Javaid

et al. 2020

Entropy

View full text Add to dashboard Cite

show abstract

“…The maximum likelihood method is used to evaluate k and c parameters as given in (Hulio and Jiang, 2018a): …”

Section: Methodology and Datamentioning

confidence: 99%

Does wind speed effects performance and cost of energy? A case study of wind farm

Hulio

Jiang

2020

IJESM

Self Cite

View full text Add to dashboard Cite

Purpose The rapid rising of renewable energy sources particularly wind energy cannot be ignored. The numerical increase in wind energy farms throughout the world is the best example. The purpose of this paper is to assess the basic question of whether wind characteristics affect the performance and cost of energy. The importance of this question cannot be ruled out while comparing renewable energy to a conventional form of energy more specifically especially for the developing country where the cost of energy is very high. Design/methodology/approach The research design of this paper is consists of an assessment of local wind characteristics of the wind farm site using Weibull k and c parameters. The performance model is used to assess the performance of the wind turbine (WT) corresponding to local wind characteristics. The wind correlation with WT in terms of changing wind speed has been assessed to quantify the effects of wind speed on the WT behavior and failure of WT components. Similarly, the power curve of WT is assessed and compared with the International Electrotechnical Commission standards 61400-12-2. The WT power coefficient and tip speed ratio corresponding to wind speed is also investigated. The energy volume and cost of energy lost model is used to determine the cost and volume loss of energy/kWh of the wind farm. Findings The findings of practical wind farms showed that the wind conditions of the site are showing a strong tendency that can be determined from the results of Weibull k and c parameters. The k and c parameters are observed to be 3.44 and 9.16 m/s, respectively, for a period of a year. The standard deviation is observed to be 2.56 for a period of a year. WT shows the efficient behavior can be obtained from the power coefficient and tip speed of WT at different wind speeds. Also, wind farm observation showed that to be some increasing wind speed cause of based WT component failures. The results of energy volume and cost/kWh assessment showed that the major portion of energy volume and cost of energy is lost owing to network, voltage dip and frequency surge, electrical and mechanical components failures. Originality/value Generally, it can be concluded that the WTs are now able to cope with variable wind speeds. However, the results of this paper are showing that WT performance and availability decreased due to increased wind speeds. It can also be a reason to decreased volume and increase the cost of energy/kWh.

show abstract

Cost, environmental impact, and resilience of renewable energy under a changing climate: a review

et al. 2022

View full text Add to dashboard Cite

Energy derived from fossil fuels contributes significantly to global climate change, accounting for more than 75% of global greenhouse gas emissions and approximately 90% of all carbon dioxide emissions. Alternative energy from renewable sources must be utilized to decarbonize the energy sector. However, the adverse effects of climate change, such as increasing temperatures, extreme winds, rising sea levels, and decreased precipitation, may impact renewable energies. Here we review renewable energies with a focus on costs, the impact of climate on renewable energies, the impact of renewable energies on the environment, economy, and on decarbonization in different countries. We focus on solar, wind, biomass, hydropower, and geothermal energy. We observe that the price of solar photovoltaic energy has declined from $0.417 in 2010 to $0.048/kilowatt-hour in 2021. Similarly, prices have declined by 68% for onshore wind, 60% for offshore wind, 68% for concentrated solar power, and 14% for biomass energy. Wind energy and hydropower production could decrease by as much as 40% in some regions due to climate change, whereas solar energy appears the least impacted energy source. Climate change can also modify biomass productivity, growth, chemical composition, and soil microbial communities. Hydroelectric power plants are the most damaging to the environment; and solar photovoltaics must be carefully installed to reduce their impact. Wind turbines and biomass power plants have a minimal environmental impact; therefore, they should be implemented extensively. Renewable energy sources could decarbonize 90% of the electricity industry by 2050, drastically reducing carbon emissions, and contributing to climate change mitigation. By establishing the zero carbon emission decarbonization concept, the future of renewable energy is promising, with the potential to replace fossil fuel-derived energy and limit global temperature rise to 1.5 °C by 2050.

show abstract

Assessment of the apparent performance characterization along with levelized cost of energy of wind power plants considering real data

Cited by 13 publications

References 54 publications

Leveraging Blockchain Technology for Secure Energy Trading and Least-Cost Evaluation of Decentralized Contributions to Electrification in Sub-Saharan Africa

Leveraging Blockchain Technology for Secure Energy Trading and Least-Cost Evaluation of Decentralized Contributions to Electrification in Sub-Saharan Africa

Does wind speed effects performance and cost of energy? A case study of wind farm

Cost, environmental impact, and resilience of renewable energy under a changing climate: a review

Contact Info

Product

Resources

About