• Environmental Engineering Research
• /
• v.22 no.3
• /
• pp.266-276
• /
• 2017

A life cycle impact assessment was applied in an industrial waste incineration plant to evaluate the direct and indirect environmental impacts based on toxicity and non-toxicity categories. The detailed life cycle inventory of material and energy inputs and emission outputs was compiled based on the realistic data collected from a local industrial waste incineration plant, and the Korean life cycle inventory and ecoinvent database. The functional unit was the treatment of 1 tonne of industrial waste by incineration and the system boundary included the incineration plant and landfilling of ash. The result on the variation of the impact by the unit processes showed that the direct impact was decreased by 79.3, 71.6, and 90.1% for the processes in a semi dry reactor, bag filter, and wet scrubber, respectively. Considering the final impact produced from stack, the toxicity categories comprised 91.7% of the total impact. Among the toxicity impact categories, the impact in the eco-toxicity category was most significant. A separate estimation of the impact due to direct and indirect emissions showed that the direct impact was 97.7% of the total impact. The steam recovered from the waste heat of the incineration plant resulted in a negative environmental burden.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.20-23
• /
• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. That makes it very difficult to apply conventional control methods to the combustion control of the refuse. In this paper, an adaptive fuzzy model predictive controller is proposed for the combustion control of the refuse. And computer simulation was carried out to evaluate performance of the proposed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1109-1113
• /
• 1993

A refuse incineration plant is a complex process, whose multi-variable control problems can not be solved conventionally by deriving an exact mathematical model of the process. The usage of advanced fuzzy technologies within the suitable development methodology is demonstrated by a controller implemented for the refuse incineration plant in Hamburg-Stapelfeld, Germany.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.11
• /
• pp.2762-2770
• /
• 2000

The refuse incineration plant has an important role in saving the combustion energy for local heating system. But harmful combustion gas(NOx etc.) leads to some serious environmental problem. To reduce the gas, a SCR(Selective Catalytic Reduction)system is installed and it is controlled by adjusting the flow of ammonia gas(NH3) . In this paper, we apply a repetitive control method to reduce NOx by adjusting the flow of ammonia gas for SCR system in a refuse incineration plant which is located in Haeundae, Pusan, Firstly, we analyze the inlet NOx period by FFt method, and verify its periodic variations. Secondly, we design a repetitive control system by using state space model method. Lastly, the effectiveness of repetitive control system is shown by comparing to a conventional PID control in simulation and experimental results.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.7
• /
• pp.2116-2124
• /
• 2000

In this paper we propose combustion control of refuse incineration plant using fuzzy model and genetic algorithm. At first fuzzy modelling is performed to obtain fuzzy model of the refuse incineration plant and obtained fuzzy model predicts outputs of the plant when inputs are given. Fuzzy model ca be used to obtain control strategy, and train and enhance operators' skill by simulating the plant. Then genetic algorithms search and find out optimal control inputs over all possible solutions in respect to desired outputs and these are inserted to plant. In order to testify proposed control method, computer simulation was carried out. As a result, ISE of fuzzy model of refuse incineration plant is 0.015 and ITAE of control by proposed method, 352 which is better than that by manual operation.

• Proceedings of the IEEK Conference
• /
• 2001.10a
• /
• pp.616-620
• /
• 2001

The objectives of this study are to investigate the suitability of various coal fly ashes and incineration ashes for zeolite synthesis. Zeolite P and hydroxysodalite are produced from coal fly ash and paper sludge incineration ash. When soluble and acid-soluble materials in incineration fly ash are removed by the water washing or acid washing before hydrothermal synthesis, hydroxysodalite can be produced. The factors to make solid-liquid separation difficult are the calcium component and the unburned carbon in ash.

• Journal of Power System Engineering
• /
• v.11 no.3
• /
• pp.9-15
• /
• 2007

This paper provides a methodology for the optimization of waste heat usage in Jeju Province. The incineration plant was considered as heat source and the food garbage plant and the youth hostel were selected as heat sink of this study. The distribution of the reusing energy in incineration plant is decide by load analysis and numerical calculation of the operational methodology. The main objective of this study is on the reduction of the fuel costs and reuse of waste heat. As the results, the efficiency of the incineration plant and two heat sink, the food garbage plant and the youth hostel, are improved and economical suggestions are proposed through the optimization analysis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.116-119
• /
• 1998

Abstract-In paper, an operation support software for combustion control of refuse incineration plant is developed using fuzzy model and genetic algorithm. It has two major modules which are simulation module and optimal operation module. In simulation module modelling is performed to obtain fuzzy model of the refuse incineration plant and obtained fuzzy model predicts outputs of the plant when inputs are given. This module can be used to obtain control strategy, and train and enhance operators' skill by simulating the plant. And in optimal operation module, genetic algorithm searches and finds out optimal control inputs over all possible solutions in respect to desired outputs. In order to testify proposed operation support software, computer simulation was carried out.

• Resources Recycling
• /
• v.23 no.3
• /
• pp.3-12
• /
• 2014

This study aims at providing an economic assessment for incineration plants which recover heat during its incineration process. In this study, Life Cycle Cost(LCC) of incineration plants is performed based on each regression analysis formula for construction cost, operation cost, and heat generation in order to compare economic feasibility. The result shows that the incineration plant recovering waste heat while processing 80 tons of waste per day increases both initial investment and operation cost but this type of an incineration plant has economical predominance from the recovered waste heat over the one that does not recover heat when being operated for more than eleven years if the retrieved heat replaces the use of LNG. And its payback time reaches more than 19 years in case of selling heat and performing emission trading.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.2
• /
• pp.43-50
• /
• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. This makes it very dificult to apply conventional control methods to the combustion control of the refuse. So most of the refuse incineration plant are operated by operators. In this paper, an multi-variable fuzzy model predictive controller is proposed for the combustion control of the re:fuse. Adaptive network based fuzzy inference system is used for modeling of the refuse incineration plant and multi-variable fuzzy model predictive controller is designed based on the identified fuzzy model. And computer simulation was carried out to evaluate performance of the proposed controller.