Development and analysis of AC optimal power flow optimization algorithms for minimization of cost and emissions with stochastic renewables

Economic growth, population rise, and industrialization have increased the daily energy demand. The rapid depletion of fossil fuels and the adverse effects of greenhouse gas (CO2, NOx) emissions from huge conventional power plants, forced the environmentalists and power system engineers to come up w...

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Bibliographic Details
Published in:Energy reports Vol. 11; pp. 2059 - 2076
Main Author: Barnawi, Abdulwasa Bakr
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.06.2024
Subjects:
Electric vehicles
Emission
Generalized normal distribution optimization
Hydro Power
Optimal power flow
Probability distribution function
Solar energy
Tidal energy
Wind energy
Hydro Power
Wind energy
Optimal power flow
Solar energy
Emission
Probability distribution function
Electric vehicles
Tidal energy
Generalized normal distribution optimization
ISSN:2352-4847, 2352-4847
Online Access:Get full text
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Summary:Economic growth, population rise, and industrialization have increased the daily energy demand. The rapid depletion of fossil fuels and the adverse effects of greenhouse gas (CO2, NOx) emissions from huge conventional power plants, forced the environmentalists and power system engineers to come up with an alternative solution for more reliable and economical generation and distribution of electricity. The alternating current optimal power flow (AC-OPF) problem is an effective tool for analysis, which involves the adjustment of certain controllable variables to optimize objective functions while satisfying operational, physical, and security limits on various controls and dependent variables. This paper focuses on analyzing the optimal power flow operation of a system with renewable integration, taking into account more popular wind and solar resources along with electric vehicles and tidal energy systems. In this context, proposed a model of the optimal power flow problem incorporating thermal-hydro-solar-wind-tidal-EV energy systems. Probability distribution functions (Weibull, Gumbel, and Lognormal) are used for renewable uncertainties and to determine predictable wind and solar power for proper generation scheduling. Furthermore, this paper provides solutions to the optimal power flow problem by including test cases of stochastic renewables involving minimizing the cost of power generation, minimizing emissions from fossil-fuelled plants, minimizing losses in the system, maximizing profit, and maximizing voltage stability. The generalized normal distribution optimization algorithm is applied to handle the above-mentioned AC-OPF problems in contingency conditions. The proposed method is employed on a modified IEEE 30-bus system integrated with RESs to assess the accuracy and performance. Statistical analysis and comparison of the results establish the superiority and robustness of the proposed algorithm over other available techniques in the literature. Simulation solutions indicate that the recommended optimization can achieve reasonable techno-economic results. Such optimum performance is expected to increase the power systems towards net zero and use renewable energy sources. [Display omitted]
ISSN:2352-4847
2352-4847
DOI:10.1016/j.egyr.2024.01.052