Reduction of Transient Engine-Out NOx-Emissions by Advanced Digital Combustion Rate Shaping

Increasing the combustion efficiency of power plant boilers and reducing pollutant emissions are important for energy conservation and environmental protection. The power plant boiler combustion process is a complex multi-input/multi-output system, with a high degree of nonlinearity and strong coupling characteristics. It is necessary to optimize the boiler combustion model by means of artificial intelligence methods. However, the traditional intelligent algorithms cannot deal effectively with the massive and high dimensional power station data. In this paper, a distributed combustion optimization method for boilers is proposed. The MapReduce programming framework is used to parallelize the proposed algorithm model and improve its ability to deal with big data. An improved distributed extreme learning machine is used to establish the combustion system model aiming at boiler combustion efficiency and NOx emission. The distributed particle swarm optimization algorithm based on MapReduce is used to optimize the input parameters of boiler combustion model, and weighted coefficient method is used to solve the multi-objective optimization problem (boiler combustion efficiency and NOx emissions). According to the experimental analysis, the results show that the method can optimize the boiler combustion efficiency and NOx emissions by combining different weight coefficients as needed.

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Investigation of Effect on Environmental Performance of Using LNG as Fuel for Engines in Seaport Tugboats

Journal of Marine Science and Engineering ◽

10.3390/jmse9020123 ◽

2021 ◽

Vol 9 (2) ◽

pp. 123

Author(s):

Sergejus Lebedevas ◽

Lukas Norkevičius ◽

Peilin Zhou

Keyword(s):

Diesel Engine ◽

Natural Gas ◽

Baltic Sea ◽

Impact Assessment ◽

Fuel Consumption ◽

Dual Fuel ◽

Nox Emissions ◽

The Baltic Sea ◽

Emission Analysis ◽

The Baltic

Decarbonization of ship power plants and reduction of harmful emissions has become a priority in the technological development of maritime transport, including ships operating in seaports. Engines fueled by diesel without using secondary emission reduction technologies cannot meet MARPOL 73/78 Tier III regulations. The MEPC.203 (62) EEDI directive of the IMO also stipulates a standard for CO2 emissions. This study presents the results of research on ecological parameters when a CAT 3516C diesel engine is replaced by a dual-fuel (diesel-liquefied natural gas) powered Wartsila 9L20DF engine on an existing seaport tugboat. CO2, SO2 and NOx emission reductions were estimated using data from the actual engine load cycle, the fuel consumption of the KLASCO-3 tugboat, and engine-prototype experimental data. Emission analysis was performed to verify the efficiency of the dual-fuel engine in reducing CO2, SO2 and NOx emissions of seaport tugboats. The study found that replacing a diesel engine with a dual-fuel-powered engine led to a reduction in annual emissions of 10% for CO2, 91% for SO2, and 65% for NOx. Based on today’s fuel price market data an economic impact assessment was conducted based on the estimated annual fuel consumption of the existing KLASCO-3 seaport tugboat when a diesel-powered engine is replaced by a dual-fuel (diesel-natural gas)-powered engine. The study showed that a 33% fuel costs savings can be achieved each year. Based on the approved methodology, an ecological impact assessment was conducted for the entire fleet of tugboats operating in the Baltic Sea ports if the fuel type was changed from diesel to natural gas. The results of the assessment showed that replacing diesel fuel with natural gas achieved 78% environmental impact in terms of NOx emissions according to MARPOL 73/78 Tier III regulations. The research concludes that new-generation engines on the market powered by environmentally friendly fuels such as LNG can modernise a large number of existing seaport tugboats, significantly reducing their emissions in ECA regions such as the Baltic Sea.

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