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Microgrid is an important form of distributed renewable energy utilization, and its optimal scheduling is a widespread concern for scholars. However, the predictability of distributed new …
In recent years, renewable energy has seen widespread application. However, due to its intermittent nature, there is a need to develop energy management systems for its …
It is, therefore, the object of the study to develop microgrid optimal dispatch with demand response ( MOD-DR ), which fills in the gap by simultaneously exploiting both the demand and supply sides in a renewable-integrated, storage-augmented, DR-enabled MG to achieve economically viable and system-wide resilient operational solutions.
First, a multi-objective interval optimization dispatch (MIOD) model for microgrids is constructed, in which the uncertain power output of wind and photovoltaic (PV) is represented by interval variables. The economic cost, network loss, and branch stability index for microgrids are also optimized.
Microgrid optimization promotes resilience by reducing the reliance on centralized power grids, which are vulnerable to outages, cyberattacks, and natural disasters. ... and then …
dispatch problems on different microgrids. These methods are used for large-scale optimization problems, and some methods are computationally fast. However, the traditional mathematical …
In order to minimize the operating cost and gaseous pollutant emission of the multi-microgrid system, which is composed of renewable energies and electric vehicles and so on, this paper builds a 24 hours day-ahead multi-objective …
According to the optimization method, the optimization dispatch method of microgrid can be divided into deterministic method and uncertainty method. The deterministic method takes the predicted value of renewable distributed power as an accurate known quantity and then optimizes the dispatch of the microgrid.
The scale of electric vehicles (EVs) in microgrids is growing prominently. However, the stochasticity of EV charging behavior poses formidable obstacles to exploring their dispatch potential. To solve this issue, an …
schedule and (2) optimizing the size. The dispatch schedule optimization is implemented using MIP, while the sizing optimization is performed using heuristic search. II. METHODS A. …
Beluga whale optimization (BWO) is a novel optimization method inspired by the behaviour of real Beluga whales, including their hunting, swimming, and feeding habits. ...
This paper presents an improved deep reinforcement learning (DRL) algorithm for solving the optimal dispatch of microgrids under uncertaintes. First, a multi-objective interval optimization …
In low-inertial microgrids, rapid convergence of the power dispatch is beneficial to keep the power balance. In Zhao and Ding (2018), a two-layer optimization strategy is …
One of the biggest challenges in microgrid (MG) management is finding the optimal way to operate the system while accounting for numerous constraints, using different …
A method of multi-objective optimization based on the dynamic dispatch of BESS(Battery Energy Storage System) is proposed for optimal microgrid operation, which …
This paper proposes a microgrid adaptive robust optimal dispatch model with different robust adjustment parameters. The robust equivalent characterization method is used to convert uncertain parameters …
methods are not suitable for the optimization dispatch of a microgrid that is a non-linear, non-smooth and non-convex problem. Considering the features of the MOOD problem, …
As a core technology of microgrid, optimal dispatching of the microgrid is an important support to deal with the uncertainty of renewable energy and load and ensure the economic and reliable operation of the microgrid [5, 6]. Regarding the optimal dispatch of microgrids, a large number of references have been studied.
By increasing the lower bound of the loop, the upper and lower bounds of the Benders algorithm can reach the same value faster, and the final optimization result can be obtained faster. This paper proposes a microgrid adaptive robust optimal dispatch model with different robust adjustment parameters.
Thus, intelligent algorithms are now viable options for resolving the nonlinear scheduling issues of microgrids. In this paper, we propose a double-layer optimization strategy …
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