Abstract
In this chapter we put forward the premise that the operations and planning of future electric energy systems will become much more complex than in the past and that data-driven knowledge about system changes will become essential. To support this claim, we briefly review today’s industry practices. We start by posing the single operations and planning industry objective mathematically. We then formally derive for the first time ever how commonly made engineering assumptions lead to the simpler planning and operation tasks. The limitations of computer methods currently used in EHV/HV energy management system (EMS) centers and in the MV/LV distribution management system (DMS) centers and of the automation logic currently embedded in power plants are discussed in light of the assumptions made and the implications of using these assumptions on system performance. We use these findings to identify what needs to change and why, in order to enable efficient and reliable future electric energy systems. In particular, we discuss the challenge to the next-generation Information Technology (IT)-enabled operations and control tools in light of ever-evolving system complexity and the need for enabling choice at value.
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Notes
- 1.
Depending on the potential system demand use, more detailed annual, seasonal, monthly, and weekly forecasts can be made. Here, for simplicity and without loss of generality, only the annual, hourly, and 10-min forecast components are modeled.
- 2.
- 3.
For this derivation, see [5].
- 4.
Observe that the proxy line limit generally varies with the operating conditions; at present, there are no on-line computations of this proxy line flow limit.
- 5.
In traditional electric power systems literature a constrained DC power flow is often written without any reference to time, as each time sample [H ∗ T H ] is viewed as the power flow static steady-state solution.
- 6.
Control areas have recently been restructured and are managed by a single Independent System Operator (ISO) in areas where power is provided competitively. Conceptually, the same ramp-limited dispatch is performed as in the existing power pools.
- 7.
Strictly speaking, discretization of the continuous time problem defined in (1.19) and Sect. 1.3 can only be done as long as there are no dynamic problems in transitioning from the state at [H ∗ T H ] to [(H + 1) ∗ T H ]. As discussed above, in today’s industry, ensuring no dynamic problems amounts to replacing the thermal line flow limits by more conservative proxy line flow limits. Power-electronically controlled FACTS and fast storage are shown in Chap. 19 to have major potential for ensuring no transient stability problems and for contributing to a larger security region.
- 8.
Shown in [12] is that much-debated nodal pricing as a proposed means of short-term congestion pricing is a result of solving the fast control subproblem in near-optimal composite control of the coupled operations/planning problem. System λ is the short-term spot electricity price.
- 9.
This classification was initially introduced to align physical system operations with the electricity market design rules.
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Acknowledgements
The ideas presented in this chapter draw in part on joint early work with Professor Francisco Galiana from McGill University in Canada. The ideas have also evolved as a result of many research efforts with several graduate students, notably Benoit Lecinq and Jean-Pierre Leotard. The author fondly remembers many hours of working together and acknowledges the input. The joint early work is cited to the best of the author’s ability.
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Ilić, M. (2013). The Case for Engineering Next-Generation IT-Enabled Electricity Services at Value. In: Ilic, M., Xie, L., Liu, Q. (eds) Engineering IT-Enabled Sustainable Electricity Services. Power Electronics and Power Systems, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09736-7_1
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