The recent integration of distributed generators (DGs) and renewable energy sources (RESs) into the power system led to the manifestation of a significant number of household microgrid (MG) systems in the electricity market. However, in most of the cases, the DGs in the MG system are passive and are not equipped by their own controllers, thus their integration increases the fluctuation in the power system and brings challenges to its management and control. To address these challenges, this paper proposes a novel electricity trading strategy for a household MG. This is achieved by formulating a nonlinear stochastic control problem that will then be solved such that the profit through electricity trading is maximised. To solve this optimisation problem, a gradient descent method based on compressive sensing is applied. Finally, some numerical examples are given to illustrate the effectiveness of the proposed control method. The results from the simulation experiments indicate that the proposed electricity trading strategy achieves the target and satisfies all constraints by controlling the energy router (ER) with the energy storage component.
|Title of host publication||2020 IEEE 16th International Conference on Control and Automation, ICCA 2020|
|Number of pages||6|
|Publication status||Published - 30 Nov 2020|
|Event||16th IEEE International Conference on Control and Automation, ICCA 2020 - Virtual, Sapporo, Hokkaido, Japan|
Duration: 9 Oct 2020 → 11 Oct 2020
|Name||IEEE International Conference on Control and Automation, ICCA|
|Conference||16th IEEE International Conference on Control and Automation, ICCA 2020|
|City||Virtual, Sapporo, Hokkaido|
|Period||9/10/20 → 11/10/20|
Bibliographical noteFunding Information:
This work was funded in part by the National Key Research and Development Program of China (Grant No. 2017YFE0132100), Tsinghua-Toyota Research Institute Cross-discipline Program, and the BNRist Program (Grant No. BNR2020TD01009).