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Techno-Economic Assessment of a Hybrid Renewable Energy System Using Dynamic Search Space

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Artificial Intelligence and Sustainable Computing

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

The standalone hybrid renewable energy system (HRES) is one of the alternate solutions for electrifying the dark villages, islands and remote habitats. The widespread application of these systems all over the globe requires the conduction of techno-economic feasibility studies to find the optimal generation mix and their sizing. In this paper, a hybrid model having solar PV units, wind power units, diesel generators (DG) and battery storage is undertaken for analysis. The idea is to minimize the levelized cost of energy (LCE), which includes the cost of annual investment, operation and maintenance costs expected to incur over the life period of the components of the HRES. Particle swarm optimization (PSO) algorithm with dynamic search space (DSS) has been employed for solving the optimal sizing problem taking into consideration the seasonal load demands. The effect of diesel generator on LCE is also studied. The seasonal effect also found to be system. Results are also comparing with different algorithms. The results are validated using the interior point algorithm (IPA).

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Abbreviations

DSS:

Dynamic search space

CRF:

Capacity Recovery factor

\({\text{I}}_{\text{cc}}\) :

Initial capital cost

ANC:

Annualized cost

\({\text{M}}_{\text{NC}}\) :

Operating and maintains cost

\({\text{cf}}_{\text{nt}}\) :

Net capacity factor

n:

Number of years

i:

Interest rate

NPV:

Number of solar PV

NWT:

Number of wind turbine

NDG:

Number of DG

NST:

Number of storages

NS:

Number of sources

\({\text{P}}_{\text{gen}}\) :

Total power generation

\({\text{P}}_{\text{d}}\) :

Load demand

\({\text{P}}_{\text{losses}}\) :

Power losses

PPV:

Power of solar

PWT:

Power of wind

PDG:

Power of DG

\({\text{P}}_{\text{st}}\) :

Power of storage

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Acknowledgements

The authors acknowledge and thankful to the Director MITS Gwalior for facilitating to carry out this research work. The authors are thankful to MHRD New Delhi for TEQIP-III financial assistance program.

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Authors and Affiliations

  1. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India

    Poonam Singh, Manjaree Pandit, Laxmi Srivastava & Nikhil Paliwal

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  1. Poonam Singh
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  2. Manjaree Pandit
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  3. Laxmi Srivastava
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  4. Nikhil Paliwal
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Editors and Affiliations

  1. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, India

    Hari Mohan Dubey

  2. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, India

    Manjaree Pandit

  3. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, India

    Laxmi Srivastava

  4. Department of Electrical Engineering, Indian Institute of Technology Delhi, Delhi, India

    Bijaya Ketan Panigrahi

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Singh, P., Pandit, M., Srivastava, L., Paliwal, N. (2022). Techno-Economic Assessment of a Hybrid Renewable Energy System Using Dynamic Search Space. In: Dubey, H.M., Pandit, M., Srivastava, L., Panigrahi, B.K. (eds) Artificial Intelligence and Sustainable Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1220-6_30

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