Abstract
A virtual power plant consists of various sources, storage devices, and responsive loads. The operator of this unit can operate it as an energy storage device and transmitter in power distribution networks by controlling the active power of the aforementioned elements. This virtual unit is also connected to the grid with an electrical inverter, which can control active and reactive power between the grid and the virtual unit. Therefore, the system operator can gain financial benefits from different markets for sources, storage devices, and responsive loads. This study presents the operation of an intelligent distribution system (IDN) as a coupling of the virtual power plant and electric inverter (CVE). CVEs participate in energy and active (flexibility market) and reactive (reactive power market) service markets simultaneously. The deterministic formulation of the proposed scheme is responsible for maximizing the profits of CVEs in the markets for reactive power and energy. In this case, the problem is limited by the AC optimal power flow equations in the network and the operation model of CVEs. A nonlinear formulation and a linear approximation model are used in this scheme to achieve the optimal solution. An adaptive robust optimization (ARO) approach is applied to model uncertainties in energy prices, renewable energy, and mobile storage device energy consumption. Since flexibility modeling requires at least two uncertainty scenarios, the formulation of CVE participation in the flexibility market is further modeled. The CVE's objective function in this scheme is to maximize profit in each of the markets listed above, and the model is constrained by the resulting robust model and the formulation of CVE flexibility. Finally, CVEs can improve network functionality and allow access to significant profits in these markets for power sources, storage devices, and responsive loads, as demonstrated by numerical results obtained from implementing this scheme on an IEEE 69-bus IDN. The proposed design can be applied in consumption areas such as industrial, agricultural, and residential sectors, leading to increased energy efficiency.