ROLE OF PHOSPHORUS CYCLING IN ALGAL METABOLISM AND ALGAL SUCCESSION IN LAKE DONGHU, CHINA

The role of phosphorus cycling in algal metabolism was studied in a shallow lake, Donghu, in Wuhan using the methods of measuring cell quota C, N and P, and calculating nutrients uptake rate by algal photosynthesis. The mean daily phosphorus uptake rate of phytoplankton varied between 0.04-0.11 and 0.027-0.053 g/m2/d in station I and station II respectively. The turnover time of phosphorus in phytoplankton metabolism ranged from 0.75-5.0 days during 1979-1986. The available P was 0.176 (+/- 0.156) g/m3 (mean +/- SD) in 1982 and 0.591 (+/- 0.24) g/m3 in 1986. The relationship between P/B ratio (Y) and TP (X: mg/l) was described by the following regression equation Y = 1.163 + 0.512logX (r = 0.731, P < 0.001). The dynamics of algal biomass and algal species succession were monitored as the indicators of environmental enrichment. The small-sized algae have replaced the blue-green algae as the dominant species during 1979-1986. The small-sized algae include Merismopedia glauca, Cryptomonas ovata, Cryptomonas erosa, several species Cyclotella. There has been drastic decrease in algal biomass and an obvious increase in P/B ratio. A nutrient competition hypothesis is proposed to explain the reason of the disappearance of blue-green algae bloom. The drastic change in algal size and the results in high P/B ratio (reaching a maximum mean daily ratio of 1.09 in 1986) may suggest a transition of algal species from K-selection to r-selection in Lake Donghu.

Determining of the delay time for a heating ventilating and air-conditioning plant using two weighted neural network approach

This paper presents an two weighted neural network approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) plan to respond to control actions. The two weighted neural network is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the two weighted neural network and a traditional mathematical method to determine the delay time. The results show that two weighted neural networks can be used effectively determining the delay time for AVAC systems.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Operational characteristics of a 1.2-MW biomass gasification and power generation plant

In this study, we analyzed the operational characteristics of a 1.2-MW rice husk gasification and power generation plant located in Changxing, Zhejiang province, China. The influences of gasification temperature, equivalence ratio (ER), feeding rate and rice husk water content on the gasification characteristics in a fluidized bed gasifier were investigated. The axial temperature profile in the dense phase of the gasifier showed that inadequate fluidization occurred inside the bed, and that the temperature was closely related to changes in ER and feeding rate. The bed temperature increased linearly with increasing ER when the feeding rate was kept constant, while a higher feeding rate corresponded to a lower bed temperature at fixed ER. The gas heating value decreased with increasing temperature, while the feeding rate had little effect. When the gasification temperature was 700-800C, the gas heating value ranged from 5450-6400kJ/Nm3. The water content of the rice husk had an obvious influence on the operation of the gasifier: increases in water content up to 15% resulted in increasing ER and gas yield, while water contents above 15% caused aberrant temperature fluctuations. The problems in this plant are discussed in the light of operational experience of MW-scale biomass gasification and power generation plants.

Design and Operation of A 5.5 MWe Biomass Integrated Gasification Combined Cycle Demonstration Plant

The design and operation of a 5.5 MWe biomass integrated gasification combined cycle (IGCC) demonstration plant, which is located in Xinghua, Jiangsu Province of China, are introduced. It is the largest complete biomass gasification power plant that uses rice husk and other agricultural wastes as fuel in Asia. It mainly consists of a 20 MWt atmospheric circulating fluidized-bed gasifier, a gas-purifying system, 10 sets of 450 kW(e) gas engines, a waste heat boiler, a 1.5 MWe steam turbine, a wastewater treatment system, etc. The demonstration plant has been operating since the end of 2005, and its overall efficiency reaches 26-28%. Its capital cost is less than 1200 USD/kW, and its running cost is about 0.079 USD/kWh based on the biomass price of 35.7 USD/ton. There is a 20% increment on capital cost and 35% decrease on the fuel consumption compared to that of a 1 MW system without a combined cycle. Because only part of the project has been performed, many of the tests still remain and, accordingly, must be reported at a later opportunity.