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1.
Electric Power Systems Research ; 221, 2023.
Article in English | Scopus | ID: covidwho-2292332

ABSTRACT

In load frequency control (LFC) study of a large power system, the key concept is control area, which is the segment of the system consisting of strongly interconnected buses, generator buses thereof working in unison. For accurate linearization of load frequency control problem, proper determination of control area is important. In the present work, a novel deterministic method is proposed and formulated to calculate the sharing of load changes by the generators to determine the control areas for LFC study of multimachine systems. This method is applied on a weakly interconnected two-area system and then on the 10-Machine New England Test System for area segmentation of each of the two systems. Furthermore, LFC studies are carried out with proposed Fuzzy Rule-tuned PID controllers (FRT-PID Controllers) for both the systems incorporated with Dish-Stirling Solar thermal system (DSTS) in each area. The scaling factors and the controller gains are optimized using Coronavirus Herd Immunity Optimizer Algorithm (CHIOA). Performance of the proposed FRT-PID controllers is compared with that of the Conventional PID controllers for the LFC studies of the systems. To test effectiveness of the FRT-PID controllers, effect of random step load perturbation (SLP) in load buses located in different areas are considered. © 2023 Elsevier B.V.

2.
Ocean and Coastal Management ; 232, 2023.
Article in English | Scopus | ID: covidwho-2242644

ABSTRACT

It is necessary to accurately calculate ship carbon emissions for shipping suitability. The state-of-the-art approaches could arguably not be able to estimate ship carbon emissions accurately due to the uncertainties of Ship Technical Specification Database (STSD) and the geographical and temporal breakpoints in Automatic Identification System (AIS) data, hence requiring a new methodology to be developed to address such defects and further improve the accuracy of emission estimation. Firstly, a novel STSD iterative repair model is proposed based on the random forest algorithm by the incorporation of13 ship technical parameters. The repair model is scalable and can substantially improve the quality of STSD. Secondly, a new ship AIS trajectory segmentation algorithm based on ST-DBSCAN is developed, which effectively eliminates the impact of geographical and temporal AIS breakpoints on emission estimation. It can accurately identify the ships' berthing and anchoring trajectories and reasonably segment the trajectories. Finally, based on this proposed framework, the ship carbon dioxide emissions within the scope of domestic emission control areas (DECA) along the coast of China are estimated. The experiment results indicate that the proposed STSD repair model is highly credible due to the significant connections between ship technical parameters. In addition, the emission analysis shows that, within the scope of China's DECA, the berthing period of ships is longer owing to the joint effects of coastal operation features and the strict quarantine measures under the COVID-19 pandemic, which highlights the emissions produced by ship auxiliary engines and boilers. The carbon intensity of most coastal provinces in China is relatively high, reflecting the urgent demand for the transformation and updates of the economic development models. Based on the theoretical models and results, this study recommends a five-stage decarbonization scheme for China's DECA to advance its decarbonization process. © 2022 Elsevier Ltd

3.
Ocean & Coastal Management ; 224:106182, 2022.
Article in English | ScienceDirect | ID: covidwho-1796247

ABSTRACT

Shore power (SP) and emission control area (ECA) have been two of the main polices for a green maritime logistics. However, it is still not clear how the joint impact of these two polices will influence vessels' shipping and energy consumption plan. The influence could be more complicated at the post-pandemic era of COVID-19 when the vessel's refueling could be risky. This paper develops mathematical model of the vessel's routing and fuel inventory decisions by considering both the SP and ECA. Based on the model, we analyze the optimal decision of a vessel under three different policy conditions, which are non-SP, compulsive utilization of SP at all ports, and optional SP utilization by the vessel. The numerical experiments are conducted based on the information of a vessel delivering cargos along the coastline in China. The results uncover a novel phenomenon that the implementation of the SP might incentive the vessel to travel longer distance outside the ECA for a lower total cost that results in more pollutant emissions. We show that the SP policy would influence the vessel's fuel management and refueling times which can change the route of vessel sailing inside and outside ECAs. Sensitivity analysis also shed light on how the government's decision on the SP policy may influence the overall pollutant emissions of the vessel from both berthing at ports and sailing on the sea. We discussed how the fixed cost of refueling, which is affected by the risk of the COVID-19 condition, will influence the vessel's plan under the SP and ECA polices. This study suggests the government to make an integrated policy of both SP and ECA at the post-pandemic era to achieve an overall reduction of the pollutant emission.

4.
J Clean Prod ; 317: 128361, 2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1313206

ABSTRACT

The onset of 2020 is marked by stricter restrictions on maritime sulfur emissions and the spread of Coronavirus Disease 2019 (COVID-19). In this background, liner companies now face the challenge to find suitable sulfur reduction technologies, make reasonable decisions on fleet renewal, and prepare stable operation plans under the highly uncertain shipping market. Considering three sulfur reduction technologies, namely, fuel-switching, scrubber, and liquefied natural gas (LNG) dual-fuel engine, this paper develops a robust optimization model based on two-stage stochastic linear programming (SLP) to formulate a decision plan for container fleet, which can deal with various uncertainties in future: freight demand, ship charter rate, fuel price, retrofit time and Sulfur Emission Control Area (SECA) ratio. The main decision contents include ship acquisition, ship retrofit, ship sale, ship charter, route assignment, and speed optimization. The effectiveness of our plan was verified through a case study on two liner routes from the Far East to Northwest America, operated by COSCO Shipping Lines. The results from SLP model show that large-capacity fuel-switching ships and their LNG dual-fuel engine retrofits should be included in the long-term investment and operation plan; slow-steaming is an important operational decision for ocean liner shipping; if the current SECA boundary is not further expanded or the sulfur emission restrictions not further tightened, the scrubber ship will have no advantage in investment cost and operation. However, considering the probabilities of more flexible scenarios, the results from the robust model suggest that it is beneficial to install scrubber on medium-capacity fuel-switching ships, and carry out more LNG dual-fuel engine retrofits for large-capacity fuel-switching ships. Compared with SLP, this robust strategy greatly reduces sulfur emissions while slightly pushing up carbon emissions.

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