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Short-Term Hydrothermal Scheduling Using Bio-inspired Computing: A Review

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Nature Inspired Optimization for Electrical Power System

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

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Abstract

Short-term hydrothermal scheduling (SHTS) problem comprises of scheduling together several hydro and thermal generation units such that objectives such as cost, emission, etc., can be optimized. Normally, the objective of SHTS is to minimize the fuel cost of the thermal units over a certain time of period while satisfying different operating constraints associated with thermal and hydro systems. Due to complex, nonlinear, multimodal and/or discontinuous nature of objective function, various bio-inspired optimization methods have been proposed to obtain the optimal dispatch solution for the hydrothermal systems of different dimensions and complexity levels. This chapter attempts to present a detailed review of the numerous bio-inspired optimization algorithms employed over the last two decades to solve the short-term SHT scheduling problem.

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Abbreviations

\(F_{mt}\) :

Cost of generation of mth thermal plant at ‘t’

\(P_{mt}^{s}\) :

Power generation of mth thermal unit at time ‘t’

\(a_{m} , b_{m} , c_{m} , e_{m} , f_{m}\) :

Fuel cost coefficients of mth unit

\(N_{s}\) :

Number of thermal power generation units

\(P_{\text{load}} \left( t \right)\) :

Total load demand at time ‘t’

\(P_{mt}^{s} ,P_{nt}^{h}\) :

Power generation of thermal and hydro units at time ‘t’

\(P_{\text{loss}} \left( t \right)\) :

Total transmission losses of the system at time ‘t’

\(C_{1n} ,C_{2n} ,C_{3n} ,C_{4n} ,C_{5n} ,C_{6n}\) :

Coefficients of n hydro unit

\(V_{n} t^{h} ,Q_{n} t^{h}\) :

Volume and discharge of nth hydro unit at time ‘t’

\(P_{{(n , {\text{min}})}}^{h} ,P_{{(n , {\text{max}})}}^{h}\) :

Min. and max. power generation values of nth hydro unit

\(P_{{(m , {\text{min}})}}^{s} ,P_{{(m , {\text{max}})}}^{s}\) :

Min. and max. power generation values of mth thermal unit

\(V_{{(m , {\text{min}})}}^{h} ,V_{{(m , {\text{max}})}}^{h}\) :

Min. and max. values of reservoir volume of mth hydro plant

\(Q_{{(m , {\text{min}})}}^{h} ,Q_{{(m , {\text{max}})}}^{h}\) :

Min. and max. values of water discharge of mth hydro plant

\(V_{m0}^{h} ,V_{m24}^{h}\) :

Reservoir volume of mth hydro unit at time zero and twenty-four

\(V_{{(m , {\text{min}})}}^{h} ,V_{{(m , {\text{end}})}}^{h}\) :

Initial and final reservoir volume of mth hydro unit

HP:

Hydro plants

TP:

Thermal Plant

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Acknowledgements

The financial support provided by AICTE-RPS project File No. 8-36/RIFD/RPS/POLICY-1/2016–17 dated 2.9.2017 and TEQIP III is sincerely acknowledged. Thanks are also due to the Director and management of MITS, Gwalior, India, for providing facilities and support.

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Authors and Affiliations

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

    Khushboo Sharma, Hari Mohan Dubey & Manjaree Pandit

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Correspondence to Khushboo Sharma .

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Editors and Affiliations

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

    Manjaree Pandit

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

    Hari Mohan Dubey

  3. South Asian University, New Delhi, India

    Jagdish Chand Bansal

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Sharma, K., Dubey, H.M., Pandit, M. (2020). Short-Term Hydrothermal Scheduling Using Bio-inspired Computing: A Review. In: Pandit, M., Dubey, H., Bansal, J. (eds) Nature Inspired Optimization for Electrical Power System. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-4004-2_9

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  • DOI: https://doi.org/10.1007/978-981-15-4004-2_9

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