Multilayer Optimisation for Day-Ahead Energy Planning in Microgrids

In the search for low carbon, reliable and affordable ways to provide electricity, an increased attention is going to the microgrid, a small-scale power system that uses a combination of energy generation and storage devices to serve local customers. The most promising feature of the microgrid is its flexibility to act as a standalone source of electricity for remote communities, and to be connected to the main power system, selling and purchasing power as required. Additionally, a microgrid can be considered as a coordinated system approach for incorporating intermittent renewable sources of energy. Microgrid customers can have power from their batteries or distributed generators, they can buy it from the utility grid, or they can reduce their consumption.When designing a new optimal planning tool for a microgrid, a major challenge (and opportunity) is to decide on what units to operate in order to meet the demand. The question is what mix will provide the performance needed at the lowest cost, or with the lowest possible emissions. Unfortunately, both objectives are often contradictory. Generally, low costs mean high emissions, and vice versa. A microgrid system operator may care more about achieving lower costs rather than lower emissions. Given the preferences, the operator needs to decide how to configure and operate the microgrid while satisfying all technical requirements, such as voltage stability and power balance. In order to control and manage the microgrid units in real-time while fully exploiting the benefit of long-term prediction, an off-line optimisation approach imposes itself to devise the online microgrid management. In this PhD thesis, an efficient multilayer control approach is developed which obtains a day-ahead unit commitment method to provide an economically and environmentally viable unit commitment (UC) that is physically feasible in terms of voltage violations. With the multilayer control approach, the future operational states of the controllable units within the microgrid are determined ahead of time. The proposed concept follows the idea of a day-ahead coordination including the unit commitment problem (scheduling layer), an off-line power flow calculation (executive layer) and a security check with feedback control (adjustment layer). Since the complete multilayer control concept works on a day-ahead time scale, the model can be considered as an off-line optimisation approach. The power reference set points provided by the multilayer control approach can, in turn, be used for an online microgrid implementation to achieve real-time system state updates.

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