Energy-saving cases and solutions that use digital technology to optimise the operation of utility plants are introduced. By Mike Suzuki, advanced solution department, Azbil Corporation.
The Paris Agreement adopted during the 21st Conference of Parties (COP21) in December 2015 brought 196 state parties together to mitigate climate change.
Many countries agreed to a long-term goal for reducing greenhouse gases (GHG) in their National Determined Contributions (NDCs). For example Japan is aiming to reduce GHG emissions 26 percent by 2030 compared to 2013 and further reduce such emissions 80 percent by 2050.
This article introduces the energy-saving cases and solutions that use digital technology to optimise the operation of utility plants.
Operation optimisation is an investment with high returns using the quick win approach, with a payback period ranging from a few months to two years.
It improves energy usage by reexamining and improving the operation of existing plants without the need to purchase new equipment, and without the need to update and modify existing equipment as well.
Operation optimisation can be realised by using digital solutions such as Advanced Process Control, Optimisation Planning, AI and other technologies.
Difficulties In Achieving Optimal Operation
Generally, equipment in utility plants is designed according to the maximum demand. Thus, when the utility plant is operating at intermediate demand, it is necessary to adjust the equipment’s load according to fluctuations in demand.
However, it is difficult for operators to manually maintain the load of such equipment to achieve total optimal efficiency for the utility plant because they have to account for the differences of energy efficiency for each piece of equipment.
Moreover, they also need to respond to disturbances caused by load fluctuations, environmental changes, etc. In short, a multitude of factors have to be taken into consideration for operation optimisation.
One of the keys to achieving operation optimisation of plants in order to realise a reduction in GHG emissions lies in Advanced Process Control (APC).
APC is a system that can be applied on top of an existing control system such as a distributed control system (DCS). The main optimisation strategy to be carried out by APC is load allocation among the same type of equipment in the plant.
Such allocation is based on the equipment’s individual efficiency characteristic and then the optimal load for each piece of equipment is distributed to improve the overall efficiency.
Generally, DCS control without APC distributes load among equipment equally without considering their individual efficiency, which reduces overall efficiency compared with continually operating at optimal efficiency.
Various Case Studies That Apply Digital Solutions
Digital solutions such as APC have been successfully deployed in various plants and achieved noteworthy results in terms of GHG emissions reduction.
The following case studies show the application of digital solutions in a boiler plant, district cooling plant and cogeneration plant, respectively.
Typical operation for boiler plants feature all boilers operating with the same load, which is controlled and determined by steam header pressure control. Thus, there lies an opportunity for APC to optimise operation.
APC can optimise the load for each boiler based on the efficiency difference between individual boilers while considering various constraints such as the minimum load of each boiler and the safety capacity that should be maintained in case of emergency shut down of a boiler or other unexpected scenario.
The overall efficiency of a boiler plant can be improved from two percent to four percent using APC. Case by case considerations have to be taken into account for the optimization of a boiler plant because different plants have different boiler systems of varying condition.
District cooling plants can be separated into chilled water systems and cooling water systems. Comparing a chiller and cooling tower, the chiller has overwhelmingly higher energy consumption.
Thus, there are many cases focused on the optimisation of the chiller while optimisation for the cooling tower is neglected.
However, there are trade-off relations between the energy consumption of a chiller and cooling tower. Thus, it is important to optimise the operation of the cooling tower as well to minimise total energy consumption.
For example, the factors affecting the operation of a cooling tower system are the number of cooling towers, the fans’ rotation speed, and cooling water flow rate.
It is difficult to operate the cooling tower system to minimise the total energy consumption for the cooling tower and the chiller due to the fluctuation in cooling demand, number of operating chillers, wet bulb temperature and also the effect of the chiller’s energy consumption.
Thus, the operation of the cooling tower system in each plant usually varies depending on the operator. Therefore, it is very useful to add APC on the top of the existing control system so that APC can determine the best operational points with minimum total power consumption systematically based on operation data.
Operating a cooling tower at the optimal condition using this solution can save three percent to five percent of the total power consumption for the chiller and cooling tower depending on the cooling tower configuration.
Additional digital solutions such as AI-based advanced equipment monitoring can also be beneficial to maintain system performance because it can monitor and detect signs of a decline in the performance of the chiller and heat exchangers.
The cogeneration system (CGS) gained popularity in recent years due to the spread of the electricity unit price and gas unit price, and high-efficiency gas turbines.
CGS is a system utilising gas and other fuels to generate electricity while also effectively utilising the waste heat to convert it into steam or other heat.
CGS is often integrated with a heat utility plant, which has caused challenges for operators to determine the best operation points for the equipment in the CGS and also the related heat equipment in the heat utility plant, such as absorption chillers, all the while keeping an eye on the steam and power demand.
The optimal operation to minimise total energy cost and GHG emissions varies depending on electricity unit price, gas unit price, emission factor, and the efficiency and characteristics of equipment.
The electricity unit price and gas unit price varies every month due to the fuel cost adjustment. The efficiency and characteristics of equipment are affected by many factors including the aging of equipment over time as well as the variation of environmental conditions due to the changing of seasons.
Furthermore, in order to carry out process control to stop or run the equipment depends on the scenario, it is also necessary to make a judgment not only for the current demand but also future demand. Thus, it is difficult for a human to manually analyse necessary data, consider all the various factors, and continuously make decisions for optimal operation.
An optimisation planning system is the digital solution for this problem. It can predict the future demand and plan an optimised solution for operation with the least amount of total energy cost taking GHG emissions into account to fulfill the predicted future demand. Then, this optimised operation planning is output into the existing control system.
Additionally, virtual power plants and smart grids are expected to become more widespread in the near future. Thus, this optimisation planning system is expected to be beneficial for activities such as the determination of the optimal operation of virtual power plants and the selection of optimal actions when demand response (DR) is activated.
The following references illustrate that operation optimisation by using digital solutions is a low-cost and effective method to help industries reduce GHG emissions by improving the efficiency of the operation of their plants.
APC was installed into a utility plant for PT. Pertamina, a major oil producer in Indonesia. As a result, the company achieved 35,000 tons of CO2 reduction in 10 months. The amount of fuel reduction through APC is valued at more than three million US dollars.
An optimisation system was installed into three district cooling plants of Keppel DHCS located in Woodlands, Changi and Biopolis in Singapore. This system successfully achieved the target energy saving level for each district cooling plant.
Azbil Corporation has a long history of successfully applying digital solutions to industries. Recent years have seen an increase in energy saving projects through operation optimisation from various industries, showing that they acknowledge the effectiveness of digital solutions to improve the energy efficiency of plants while reducing GHG emissions.
The improvement in energy efficiency and reduction of GHG emissions in a plant creates a win-win situation because the industries can save energy cost while contributing to NDCs. Thus, we believe such digital solutions offer a quick win approach and are one of the most efficient methods for ESG investment.
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