Case Study Modelling Introduction
GSK manufacturing plant in Irvine is a typical large-scale industry with both high thermal and electrical demand, which both fluctuate significantly. For this case study, GSK provided measured demand and on-site generation data from the plant. The company had been planning to install a large-scale biomass CHP plant to provide an on-site supply of heat and power, with the aim to achieve on-site energy autonomy by 2020. The proposed plant had a capacity of 20 MWe (85MWnth) and uses wood chips as a fuel.
The original operating strategy for the plant was to run at full boiler load at all times, to bleed the necessary amount of steam for process heating purposes, and to use the remaining steam to generate electricity. An estimated 240000 tons of fuel would be used annually. Full load operation can maximise efficiency and improve economic feasibility; however, the plant has to rely on the grid to accept the large amount of surplus energy that is generated.
The model was used in the case study to highlight opportunities to improve the site’s energy autonomy and reduce its carbon emissions. GSK’s measured demand profiles were used as model inputs, but the energy provided by existing on-site generators was deducted from these beforehand. CHP plant parameters were chosen similar to GSK’s proposed plant, but instead of running on full output, the model’s built-in operating strategies were used. A further set of calculations was done, combining the system with a thermal storage unit. The storage was a molten salt-steam accumulator hybrid technology, sized for 12 hours of average demand (206 MWh capacity) as an example. The baseline scenario was always separate biomass heat and power plants. All calculations used local willow grown on farmland as biomass fuel.
Three hypotheses were made for this analysis:
1. At least one of the model scenarios (which particular scenario that would be, was left to be determined based on the results) could achieve autonomous operation with lower fuel use and lower CO2 emissions than the original.
2. Thermal storage helps improve the autonomy of the CHP plant in all scenarios.
3. For similar levels of autonomy, a CHP plant has lower fuel use and running costs than separate heat and power generation
Modelling Results and Discussion
A selection of model results considered most relevant for the case study is presented below:
The findings show that it is very important to choose the correct operating strategy for a CHP plant. Percentages of autonomous operation over the year indicate that the first two scenarios were unable to achieve reasonable levels of autonomy. It is important to note here that while power can be imported at some additional cost to overcome supply shortages in scenario 1, it is not possible to import steam for scenario 2.
The baseline was the most autonomous scenario due to its flexibility, having separate generators means heat and power output modulation is not constrained by heat to power ratio. However, separate generators had lowest fuel efficiency and highest carbon emissions.
Scenario 3 offered a very high level of autonomy with only a slight need for imported power. This was achieved with lower emissions and much lower costs than the baseline. These findings highlight scenario 3 as the optimum operating strategy for this plant.
A CHP plant similar to the one GSK are planning could cost 15% less than separate biomass heat and power generators sized according to peak demand (data shown in model). Also, CHP annual operating costs can be lower than the baseline. Therefore a CHP plant can be economically more feasible than the baseline and offer financial savings starting from its installation, without a payback period. If the aim of the stakeholders was to install a new on-site energy system, then these results would greatly encourage to choose a CHP over two separate plants.
Surprisingly, thermal storage increased fuel consumption in all scenarios apart from scenario 3, where a slight decrease was noted. However, the savings were not enough to offset the expenses associated with installing and maintaining the storage system.
The benefits of thermal storage are most apparent in scenario 2, where the proportion of steam autonomy increases significantly when storage is included. The advantage of this scenario is that the fuel input is used most fully, meaning the highest efficiency. Scenario 2 is not viable at the moment; but if demand side management becomes available and storage becomes more cost effective, it could provide a feasible alternative. On the other hand, no amount of storage could lead this scenario to 100% steam autonomy with current demands.
Thermal storage was not feasible in the baseline scenario: it added costs, but could not improve the already maximum level of autonomy. What is more, it increased fuel use and emissions, as the plant attempted to keep a full storage at all times and therefore had to offset self-discharge losses.
Case Study Conclusions
Hypothesis 1 was not confirmed, although scenario 3 was very close to full autonomy. However, the original operating scenario was not fully autonomous either.
Hypothesis 2 was confirmed by scenarios 1 and 2; scenario 3 achieved full steam autonomy even without storage, so further improvement was not possible.
Hypothesis 3 was confirmed: scenario 3, with a very small annual grid dependency on the power side, used much less fuel and cost less to operate than scenario 4.
GSK’s proposed CHP plant in power leading mode, bleeding extra steam when required, would be the most suitable option for the GSK Irvine factory.
When demand side management becomes available, a power leading plant with thermal storage could help conserve most energy and operate with lowest carbon emissions.
Thermal storage alone could not help any of the scenarios achieve full autonomy, but it could improve it, and in certain cases provide fuel savings at the same time.
Regardless of costs, fuel use and autonomy in normal operating conditions, all forms of energy storage offer a backup in case of grid failures and on-site generator failures. It is important to know the risk of energy supply outages and the costs involved, and to compare those to the costs and benefits of energy storage.