Design of Aggregators for the Day-Ahead Management of Microgrids Providing Active and Reactive Power Services

Abstract

The increasing diffusion of distributed energy generation systems requires the development of new control paradigms for the coordination of micro-generators, storage systems, and loads aimed at maintaining the efficiency and the safe operability of the electricity network. MicroGrids (MGs) are an interesting way to locally manage groups of generation devices, but they cannot singularly provide a significant contribution to sustain the main electricity grid in terms of ancillary services, such as the availability of a minimum amount of power reserve for the frequency regulation. For these reasons, in this paper we propose a framework for the aggregation and coordination of interconnected MGs to provide ancillary services to the main utility. The proposed framework is structured in three main phases. In the first one, a distributed optimization algorithm computes the day-ahead profile of the active power production of the MGs based on the available forecasts of the renewable sources production and the loads absorption. In this phase, scalability of the optimization problem and confidentiality requirements are guaranteed. In the second phase, reactive power flows are scheduled and it is ensured that the active power trends planned in the first phase do not compromise the voltage/current limitations. A final third phase is used to schedule the active and reactive power profiles of the generation units of each MG to make them consistent with the requirements and results of the previous two phases. The developed method is used for control of the IEEE 13-bus system network and the results achieved are thoroughly discussed in terms of performance and scalability properties.

Optimization-Based Control of Microgrids for Ancillary Services Provision and Islanded Operation

“…Therefore, MGs are properly modeled as equivalent generators, which allows to address the electrical feasibility in a pure centralized way, without however requiring MGs to communicate their internal information and involving computational issues. Figure 12.2 shows some results of the described procedure, considering as benchmark an aggregation of 4 MGs connected to the IEEE 37 bus system [12]. In particular, from Fig.…”

Software-in-the-loop testing of a distributed optimal scheduling strategy for microgrids’ aggregators

“…The objective of this section is to give a general overview of the algorithm proposed in [8] and highlight its peculiarities. Every day, within the closure of the Day-Ahead energy market, the AG is required to submit its overall power profile to the System Operators and its availability in terms of capacity reserve.…”

“…Another important service to address, which becomes necessary in presence of many MGs connected to the same distribution network, concerns the regulation of line power flows to avoid over-voltage and over-current events, possibly leading to line congestion issues. The whole optimization procedure presented in [8] is structured in three steps, which are described in the following. The flowchart of the steps' sequence is depicted in Fig.…”

“…Secondly, a privacy-friendly coordination strategy is desirable, meaning that single MGs should not be required to disclose unnecessary internal information. For these motivations, in [8] a distributed day-ahead scheduling approach for MG-AG, guaranteeing the optimal energy management and power reserve provision, has been proposed. The aim of this paper is to demonstrate the real-world applicability of the algorithm proposed by in [8], verifying its scalability and performances through a real test-bench, with industrial-grade MG simulators and EMS provided by ABB Power Grids, and with real power profiles extracted from the NREL Wind Integration Database and Solar Integration databases [9].…”

“…The paper is structured as follows. The optimization approach to schedule the AG operations is briefly described in Section II, since more details are available in [8]. Section III describes the ABB Power Grids e-mesh™ EMS, while the test bechmark and results are presented in Section IV.…”