In order to remain competitive, industrial facilities with heavy energy use must now
consider not only the cost of excess reliability but also of every potential operational
inefficiency. Operators must understand the true incremental cost of every real-time
decision. This information can be provided effectively by a rigorous thermodynamic
model of the site-wide utility system, which accurately accounts for the incremental price
of fuel and electricity purchase and/or sale in order to calculate the cost of every potential
operating mode that satisfies the heat and power needs of the process in real-time.
However, the complexity of most modern utility systems yields hundreds, if not
thousands, of potential operating modes among which the operator must choose in order
to achieve the goal of minimum cost operation. A site-wide thermodynamic model can be
leveraged by applying an optimization engine to calculate the lowest-cost operational
mode currently available.
A key component in successful application of such an optimization method is proper
constraining of the limits the optimizer must recognize. A mathematical optimizer will by
definition seek for lower cost until it encounters a constraint that will not allow it to find a
feasible lower cost operating mode. The optimization, of course, must not violate any
reliability, environmental, safety, or contractual constraint.
The limits to optimization must be realistic in consideration of actual operation and
decided with alignment from management to engineering to operations staff. Management
must define the expectations of the energy management framework under which
operators are to act in order to measure success.
The ISO 50001 Energy Management Standard (Chapter 6) addresses this need and
defines specific principles that allow an organization to design, implement, and continuously
improve energy management. The standard utilizes the “Plan–Do–Check–Act”
approach to continuous improvement. Figure 19.1 illustrates the cycle from management
planning through local execution back to audit and adjustment to planning required for
energy management process improvement.
Real-time optimization and management systems for utilities can provide a rigorous
basis for the Plan–Do–Check–Act cycle by aligning recommended operator behavior
with the expectations of management regarding energy use at an industrial facility. In the
process, they can drive significant operational savings that can be sustained over time.