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Abstract
Offshore micro integrated energy systems (OMIESs) are the basis of offshore oil and gas engineering and play an important role in developing and utilizing marine resources. By introducing offshore wind power generation, the carbon emissions of offshore micro integrated energy systems can be effectively reduced; however, greater challenges have been posted to the reliable operation due to the uncertainty. To reduce the influence brought by the uncertainty, a multiobjective optimization model was proposed based on the chance-constrained programming (CCP); the operating cost and penalty cost of natural gas emission were selected as objectives. Then, the improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the model efficiently. Finally, the numerical studies verified the efficiency of the proposed algorithm, as well as the validity and feasibility of the proposed model in improving the economy of OMIES under uncertainty.
Highlights
There are 6500 offshore oil and gas platforms worldwide [1], which is expected to become an important way to solve energy and environmental problems worldwide by developing and utilizing marine oil and gas resources [2,3,4]. ese offshore oil and gas platforms are far away from the land and can be categorized as an offshore micro integrated energy system [5]
The improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the biobjective optimization model based on chance-constrained programming (CCP) to minimize the operating cost and natural gas emission. e paper mainly has the following contributions: (i) A biobjective optimization model based on CCP was proposed to handle the uncertainty of load and wind power
(ii) Based on NSGAII, the hybrid constraints handling strategy was introduced and modified through three aspects, namely, dimensionality reduction, individual repair, and normalization to improve the performance of NSGAII when dealing with complex constraints (iii) e relationship between natural gas emission and wind power utilization was analyzed by implementing an offshore micro integrated energy systems (OMIESs) example in the Bohai Sea to provide schemes or suggestions for offshore oil and gas platforms e rest of this paper is organized as follows
Summary
There are 6500 offshore oil and gas platforms worldwide [1], which is expected to become an important way to solve energy and environmental problems worldwide by developing and utilizing marine oil and gas resources [2,3,4]. ese offshore oil and gas platforms are far away from the land and can be categorized as an offshore micro integrated energy system [5]. The improved hybrid constraints handling strategy based on nondominated sorting genetic algorithm II (IHCHS-NSGAII) was introduced to solve the biobjective optimization model based on CCP to minimize the operating cost and natural gas emission. The natural gas emission was selected as the other objective considering the current situation that there exists a large amount of natural gas emission in actual OMIES (ii) Based on NSGAII, the hybrid constraints handling strategy was introduced and modified through three aspects, namely, dimensionality reduction, individual repair, and normalization to improve the performance of NSGAII when dealing with complex constraints (iii) e relationship between natural gas emission and wind power utilization was analyzed by implementing an OMIES example in the Bohai Sea to provide schemes or suggestions for offshore oil and gas platforms e rest of this paper is organized as follows. It is necessary to do some research based on the characteristics of OMIES
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