Multi-Objective Techno-Economic Assessment of Real Life Hydrocarbon Facility Real Power Loss and Power Factor Optimization Using Improved Strength Pareto and Differential Evolutionary Algorithms   M. T. Al-Hajri, M. A. Abido and M. K. Darwish 2017/04/25

Abstract

In this paper, a techno-economic assessment of a real life hydrocarbon facility electrical system real power loss and grid connection power factor optimization is presented. This optimization was attained by using the Improved Strength Pareto Evolutionary Algorithm (SPEA2) and the Differential Evolutionary Algorithm (DEA). The study is the first of its kind as none of the previous studies were conducted in the context of a real life hydrocarbon facility’s electrical system. The hydrocarbon facility’s electrical system examined in the study, consists of 275 buses, two gas turbine generators, two steam turbine generators, and large synchronous motors, with both rotational and static loads. For the real life hydrocarbon facility, the performance of the SPEA2 and the DEA were benchmarked in the course of optimizing two competing objectives - power loss and grid connection power factor. The problem was articulated as a constrained nonlinear problem. The constraints were all real values reflecting the system equipment and components’ limitations. The results obtained from the research show the efficiency and prospects of the proposed research in solving the described multiple objectives of the study case. Also addressed in this study the annual cost avoidance, due to the study objectives’ optimization, based on real fuel value.

Authors and affiliations

M. T. Al-Hajri(1), M. A. Abido(2) and M. K. Darwish(3)
1. Power Systems, Saudi ARAMCO Oil Company, Dhahran, Kingdom of Saudi Arabia
2. Electrical Engineering Department, King Fahad University (KFUPM), Dhahran, Kingdom of Saudi Arabia
3. Computer & Electronic Eng. Department, Brunel University, U.K., Uxbridge, United Kingdom

Key words

Improved Strength Pareto Evolutionary Algorithm (SPEA2), differential evolutionary algorithm, power loss optimization, grid connection power factor enhancement, hydrocarbon facility, millions of standard cubical feet of gas (MMscf).

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