Abstract
In this paper, an innovative method for managing a smart-community microgrid (SCM) with a centralized electrical storage system (CESS) is proposed. The method consists of day-ahead optimal power flow (DA–OPF) for day-ahead SCM managing and its subsequent evaluation, considering forecast uncertainties. The DA–OPF is based on a data forecast system that uses a deep learning (DL) long short-term memory (LSTM) network. The OPF problem is formulated as a mathematical mixed-integer nonlinear programming (MINLP) model. Following this, the developed DA–OPF strategy was evaluated under possible operations, using a Monte Carlo simulation (MCS). The MCS allowed us to obtain potential deviations of forecasted data during possible day-ahead operations and to evaluate the impact of the data forecast errors on the SCM, and that of unit limitation and the emergence of critical situations. Simulation results on a real existing rural conventional community endowed with a centralized community renewable generation (CCRG) and CESS, confirmed the effectiveness of the proposed operation method. The economic analysis showed significant benefits and an electricity price reduction for the considered community if compared to a conventional distribution system, as well as the easy applicability of the proposed method due to the CESS and the developed operating systems.
Highlights
A microgrid is a smart power system with electrical loads, distributed generation, energy storage systems, and other components grouped in a limited geographical area
This allows for the developed operation strategy to be evaluated and critical situations to be predicted during the day-ahead
A DA-Optimal Power Flow (OPF) based on the deep learning (DL) data forecast to predict the input data for the OPF is formulated as an mixed-integer nonlinear programming (MINLP) problem
Summary
A microgrid is a smart power system with electrical loads, distributed generation, energy storage systems, and other components grouped in a limited geographical area. Most existing distribution community networks can be updated to a smart-community microgrid (SCM). By adding a centralized renewable generation, an intelligent management system, and a storage unit to the community [1,2]. This allows the community to have a more resilient, efficient, and environment-friendly supplying microgrid [3]. The local renewable energy (RE) production supplies base-electricity to grid-connected end-user(s) and on-site assets, which are able to run the community microgrid in the off-grid mode, for a limited period [5].
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