Almost all process industry facilities have begun to engage in energy management initiatives. Yet sometimes the benefits from these initiatives can erode as fast as they are achieved.
This is primarily because things change, whether that is in the process, systems, fidelity of rigorous simulation models used, and aged assets. As a result, a degree of maintenance is required to maintain rigorous simulation models.
Clearly, different methods and technologies are important to decreasing the total cost of ownership and keeping relevant the energy management initiatives we embark on. So why does energy performance monitoring, targeting and reporting have a higher propensity to fail in the process industries compared to other industries, like building management.
Experts believe it is typically down to the process industries taking a complex approach to what in essence is a simple but repetitive task. Plus, particularly to the approach chemical and petroleum engineers take to solving these problems, which is a rigorous simulation and a precisely theoretical one. These approaches were necessary when we did not live in a connected world of sensors and the need for data via simulated values, in the absence of real-time data, was necessary to supplement this gap in our knowledge. However, times have changed. Twenty to twenty five years ago we may have been 5-10 percent connected to our assets or less, nowadays we are 80-99 percent connected to our assets and the remainder is gradually being added via advances like RTUs, downhole gauges, wireless etc.
So why do we persist in pushing rigorous simulation as the first tool in our energy monitoring, targeting and reporting strategy? It’s time we get with the times and leverage methods and tools which are easier to implement and maintain and which provides us with the information we need to make faster, flexible and more accurate directional decisions/actions.
The rationale
Energy management is a major pillar in many process industry operations excellence strategies. The management of energy information is the most important component of any effective, continuous improvement energy management initiative. It is widely accepted by best-in-class facilities that monitoring, targeting and reporting (MT&R) alone on energy usage can lead to significant energy reductions. Practical working knowledge and techniques like MT&R — which includes computational methods of correlations, best operation base lining, data mining and analytics on key drivers like production, uncontrollable variations like weather –are the most effective and shows greater longevity than rigorous simulation ones which erode as systems, conditions, personnel attrition and expertise retirement ensues.
So the question becomes why is looking back, predicting conditions from historical information and utilising smaller more focused equipment based simulation models so much more effective? The answer lies in the fact that energy used by any business varies as production processes do, volumes change, equipment ages and inputs vary. Determining the relationship of energy used or which should be used, to key performance indicators allows facilities:
- To know how much better or worse they compared to before
- To understand energy trends which are seasonal in nature and operations cycles/modes effects etc. (This is in contrast to a theoretical rigorous simulation which normally does not account for weather, operation cycles/modes or whether you are running with a standby pump or exchanger.)
- To understand equipment residual life effect on total energy usage
- To compare analyses and benchmark similar facilities
- To identify and filter historically reactive operation decisions which have a large effect on energy usage
- To develop more insightful energy usage measures which have profound effects on a facility energy intensity index.
- The strategy to long term energy monitoring, targeting and reporting (MT&R) success lies in keeping it simple and evolving your energy accounting and auditing strategy towards a simple “measure, analyse and adjustment” methodology.
Keep it simple and grow
For most pacesetter facilities addressing energy management, keeping it simple and being flexible is key. So how do you keep it simple but yet be nimble in a few descriptive steps?
- Collect data vigorously (Historian and other data sources)
- Contextualise vehemently (Common Asset Model)
- Cleanse and validate your data (Data Scrubbing and Quality)
- Collect events/modes that affect your process behaviour (shifts, operating modes, range controllers, plans/workflows etc.) (Layer System States )
- Utilise a surveillance engine which can exploit multiple methods of analysis, has an extensive equipment library for rotating and static equipment and which can leverage templates to decrease total cost of ownership on equipment models-graphics-dashboards calculations and can deploy fault models/notification workflows (Analyse)
- Connect seamlessly to data sources using service oriented architectures (Standards based Connectivity/Exchange)
- Utilise standards based reporting services (Reporting Services)
Be guided by standards
Your energy management (MT&R) initiative should support ISA95- Operations Performance implemented using a requirements decomposition similar to the one below on all relevant Energy Business Processes.
Furthermore, your efforts in Energy Management should be guided by ISO 50001 and its associated audit standards for Energy. In general, keep the following with respect to ISO 50001 in mind:
- ISO 50001 requires an organisation to monitor measure and analyse the key characteristics of its operations that determine energy performance at planned intervals. Equipment used in monitoring and measurement of key characteristics should be calibrated to ensure data are accurate and repeatable.
- ISO 50001 requires an organisation to establish an energy baseline(s) for the measurement of the energy performance.
- Option#1: Manual Benchmark of Energy performance baseline: The strategy outlined in this technology note suggest the user to apply baseline on an asset or unit or plant by specifying start and end time to consider as reference, performance data in historian. Use baseline period data set to identify data model using regression techniques and generate target energy model. Trending of current performance along with baseline time period performance to compare and understand the deviation
- Option#2: Use Design Benchmark model: The strategy outlined in this technology note recognises the need for rigorous equipment simulation on a supportive and smaller basis but suggest leaving large plant or field wide simulations to a task conducted offline (or specifically on the supply side not demand side) and for intermittent auditing purposes if warranted. TRY KEEPING IT SIMPLE
- ISO 50001 requires an organisation to identify appropriate energy performance indicators to monitor and measure its energy performance.
