Techno-Economic Optimization of Small-Scale Hybrid Energy Systems Using Manta Ray Foraging Optimizer

Alturki, Fahd A.; Farh, Hassan M. H.; Al-Shamma’a, Abdullrahman A.; AlSharabi, Khalil

doi:10.3390/electronics9122045

Cited by 29 publications

(20 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the generic discounted cash flow (DCF) approach using the net present value (NPV) criterion is generally adopted to evaluate investments, the DCF method is inappropriate for a rapidly changing investment situation (Dixit and Pindyck [20]; Herath and Park [21]; Lee and Shih [11]) and does not consider managerial flexibility in investment decisions (Hayes and Abernathy [23]; Hayes and Garvin [24]; Trigeorgis and Mason [25]; Trigeorgis [26]). In the current study, we consider a two-stage approach-one turbine at the 1st stage and a field of 50 at the 2nd stage; along with the possibility to withdraw at the 2nd stage.…”

Section: Methodsmentioning

confidence: 99%

“…The main purpose of this paper is to study the effect of energy value fluctuations on the assessment of the profitability of wind turbine facilities using the real option analysis method. The economic output of a wind turbine installation is a function of its electric energy output [23][24][25] and the value of market energy. The electric energy output is a function of the turbine used and wind speed statistics.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

2021

View full text Add to dashboard Cite

The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for wind energy, thus improving the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique has been widely applied in many studies for the valuation of renewable energy investment projects. Taking into account the above background, we apply, in this study, the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel, which is the context of our work. We hypothesize that due to nature of wind energy production uncertainties, the ROA method is better than the alternative. The novelty of this paper includes the following: real world wind statistics of the Merom Golan site in Israel (velocity 3.73 m/s, with a standard deviation of 2.03 m/s), a realistic power generation estimation (power generation of 1205.84 kW with a standard deviation of about 0.5% in annual value which is worth about 1.3 M$ per annum), and an economic model to evaluate the profitability of such a project. We thus discuss the existing challenges of diversifying renewable energy sources in Israel by adding wind installations. Our motivation is to introduce a method which will allow investors and officials to take into account uncertainties when deciding in investing in such wind installations. The outcomes of the paper, which are obtained using the method of Weibull statistics and the Black–Scholes ROA technique, include the result that market price volatility adds to the uncertainties much more than any wind fluctuations, provided that the analysis is integrated over a long enough time.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

2021

View full text Add to dashboard Cite

show abstract

“…At the rated speed (u r ), the wind power reaches its rated value till the cut-off or furling speed (u f ), where the wind turbine stops running if the wind speed exceeds its cut-off speed value. The output power captured by the WT depends on P r , u c , u r , and u f , which can be formulated as shown below [51].…”

Section: Modeling Of the Wt Genertation Systemmentioning

confidence: 99%

Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

et al. 2022

Self Cite

View full text Add to dashboard Cite

In this study, a novel bonobo optimizer (BO) technique is applied to find the optimal design for an off-grid hybrid renewable energy system (HRES) that contains a diesel generator, photovoltaics (PV), a wind turbine (WT), and batteries as a storage system. The proposed HRES aims to electrify a remote region in northern Saudi Arabia based on annualized system cost (ASC) minimization and power system reliability enhancement. To differentiate and evaluate the performance, the BO was compared to four recent metaheuristic algorithms, called big-bang–big-crunch (BBBC), crow search (CS), the genetic algorithm (GA), and the butterfly optimization algorithm (BOA), to find the optimal design for the proposed off-grid HRES in terms of optimal and worst solutions captured, mean, convergence rate, and standard deviation. The obtained results reveal the efficacy of BO compared to the other four metaheuristic algorithms where it achieved the optimal solution of the proposed off-grid HRES with the lowest ASC (USD 149,977.2), quick convergence time, and fewer oscillations, followed by BOA (USD 150,236.4). Both the BBBC and GA algorithms failed to capture the global solution and had high convergence time. In addition, they had high standard deviation, which revealed that their solutions were more dispersed with obvious oscillations. These simulation results proved the supremacy of BO in comparison to the other four metaheuristic algorithms.

show abstract

“…Optimization [82] Computational cost is comparatively less compared to other optimizers and also has good precision in solutions.…”

Section: Manta Raymentioning

confidence: 99%

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Muqeet¹,

Munir

Javed

et al. 2021

Energies

View full text Add to dashboard Cite

The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.

show abstract

Techno-Economic Optimization of Small-Scale Hybrid Energy Systems Using Manta Ray Foraging Optimizer

Cited by 29 publications

References 48 publications

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

Valuation of Wind Energy Turbines Using Volatility of Wind and Price

Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges

Contact Info

Product

Resources

About