Microbial analysis of soil and groundwater from a gasworks site and comparison to a sequenced biological reactive barrier remediation process (SEREBAR)

Aims: To investigate the distribution of a polymicrobial community of biodegradative bacteria in (i) soil and groundwater at a former manufactured gas plant (FMGP) site and (ii) in a novel SEquential REactive BARrier (SEREBAR) bioremediation process designed to bioremediate the contaminated groundwater. Methods and Results: Culture-dependent and culture-independent analyses using denaturing gradient gel electrophoresis (DGGE) and polymerase chain reaction (PCR) for the detection of 16S ribosomal RNA gene and naphthalene dioxygenase (NDO) genes of free-living (planktonic groundwater) and attached (soil biofilm) samples from across the site and from the SEREBAR process was applied. Naphthalene arising from groundwater was effectively degraded early in the process and the microbiological analysis indicated a dominant role for Pseudomonas and Comamonas in its degradation. The microbial communities appeared highly complex and diverse across both the sites and in the SEREBAR process. An increased population of naphthalene degraders was associated with naphthalene removal. Conclusion: The distribution of micro-organisms in general and naphthalene degraders across the site was highly heterogeneous. Comparisons made between areas contaminated with polycyclic aromatic hydrocarbons (PAH) and those not contaminated, revealed differences in the microbial community profile. The likelihood of noncultured bacteria being dominant in mediating naphthalene removal was evident. Significance and Impact of the Study: This work further emphasizes the importance of both traditional and molecular-based tools in determining the microbial ecology of contaminated sites and highlights the role of noncultured bacteria in the process.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

The cost of water from an autonomous wave-powered desalination plant

A techno-economic model of an autonomous wave-powered desalination plant is developed and indicates that fresh water can be produced for as little as £0.45/m3. The advantages of an autonomous wave-powered desalination plant are also discussed indicating that the real value of the system is enhanced due to its flexibility for deployment and reduced environmental impact. The modelled plant consists of the Oyster wave energy converter, conventional reverse osmosis membranes and a pressure exchanger–intensifier for energy recovery. A time-domain model of the plant is produced using wave-tank experimentation to calibrate the model of Oyster, manufacturer's data for the model of the reverse osmosis membranes and a hydraulic model of the pressure exchanger–intensifier. The economic model of the plant uses best-estimate cost data which are reduced to annualised costs to facilitate the calculation of the cost of water. Finally, the barriers to the deployment of this technology are discussed, but they are not considered insurmountable.