MINLP for Hydro-Thermal Unit Commitment problem using BONMIN solver

Sutradhar, Suman; Choudhury, Nalin B. Dev; Sinha, Nidul

doi:10.1109/icpeices.2016.7853419

Cited by 6 publications

(5 citation statements)

References 24 publications

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“…In this work, basic open-source non-linear mixed-integer programming (BONMIN) [22] is utilised as an efficient solver to obtain the planning results. Compared to the other methods, BONMIN demonstrates faster convergence speed and better quality of solutions in [23,24].…”

Section: β Problem Statement and Research Gapsmentioning

confidence: 99%

Low carbon oriented power‐to‐gas station and integrated energy system planning with ancillary service provision and wind power integration

Wang

Yanrong

Wang

et al. 2020

IET Renewable Power Generation

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This study proposes an integrated energy system (IES) model consisting of natural gas system, electricity system, and power-to-gas stations (P2GSes), and then uses a centralised coordinated method to plan the IES. P2GSes can convert excessive renewable energy to natural gas and provide a promising approach to large-scale energy storage and long-distance energy transmission in the form of gas. However, considering the carbon emission of natural gas utilisation and high cost of P2G process, new embedded P2GSes will pose a threat to the economic and environment-friendly operation for the existing integrated energy system. Therefore, a more comprehensive P2G revenue objective, which is comprised of a secondary reserve service model, wind power integration model and carbon trading market participating model, is proposed in this study. The potential of P2GSes to provide the capacity of absorbing wind power and carbon reduction is innovatively and thoroughly evaluated in this study. The effectiveness of the proposed model is verified on an IES containing a coupled 24-bus electricity and 20-bus natural gas system. Simulation results show that it is optimal for the P2GSes revenue model to possess both capacities of absorbing wind power and converting the acquired power into natural gas as much as possible.

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Section: β Problem Statement and Research Gapsmentioning

confidence: 99%

Low carbon oriented power‐to‐gas station and integrated energy system planning with ancillary service provision and wind power integration

Wang

Yanrong

Wang

et al. 2020

IET Renewable Power Generation

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show abstract

“…Due to the prominent uncertainties existed in the IES planning, the stochastic optimization [14] and the chance-constrained programming [15] are applied in the solving process and they demonstrate good effectiveness in avoiding risks and improving the robustness of the planning schemes. However, there are many drawbacks related to these applied algorithms [63]. The performance of these algorithms highly depends upon the stability between their exploration and exploitation capabilities, which requires heavily diversified population based on the multidimensional search space of the problem to be solved.…”

Section: B Relative Backgroundmentioning

confidence: 99%

“…BONMIN is a useful solver for solving nonconvex MINLP [61]. Its superiority has been demonstrated in [62] and [63].…”

Section: B Relative Backgroundmentioning

confidence: 99%

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Game-theoretic planning for integrated energy system with independent participants considering ancillary services of power-to-gas stations

Zhang

Chan

Wang

et al. 2019

Energy

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“…From Figure 3 it is evident that the power generation from hydro units is a function of both hydro discharge and water volume. For this reason in this research this quadratic concave function is represented by (8) [11,27,37]…”

Section: (B) Physical Limitations On Reservoir Storage Volume Andmentioning

confidence: 99%

Modelling of Hydrothermal Unit Commitment Coordination Using Efficient Metaheuristic Algorithm: A Hybridized Approach

Sutradhar

Choudhury

Sinha

2016

Journal of Optimization

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In this paper, a novel approach of hybridization of two efficient metaheuristic algorithms is proposed for energy system analysis and modelling based on a hydro and thermal based power system in both single and multiobjective environment. The scheduling of hydro and thermal power is modelled descriptively including the handling method of various practical nonlinear constraints. The main goal for the proposed modelling is to minimize the total production cost (which is highly nonlinear and nonconvex problem) and emission while satisfying involved hydro and thermal unit commitment limitations. The cascaded hydro reservoirs of hydro subsystem and intertemporal constraints regarding thermal units along with nonlinear nonconvex, mixed-integer mixed-binary objective function make the search space highly complex. To solve such a complicated system, a hybridization of Gray Wolf Optimization and Artificial Bee Colony algorithm, that is, h-ABC/GWO, is used for better exploration and exploitation in the multidimensional search space. Two different test systems are used for modelling and analysis. Experimental results demonstrate the superior performance of the proposed algorithm as compared to other recently reported ones in terms of convergence and better quality of solutions.

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MINLP for Hydro-Thermal Unit Commitment problem using BONMIN solver

Cited by 6 publications

References 24 publications

Low carbon oriented power‐to‐gas station and integrated energy system planning with ancillary service provision and wind power integration

Low carbon oriented power‐to‐gas station and integrated energy system planning with ancillary service provision and wind power integration

Game-theoretic planning for integrated energy system with independent participants considering ancillary services of power-to-gas stations

Modelling of Hydrothermal Unit Commitment Coordination Using Efficient Metaheuristic Algorithm: A Hybridized Approach

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