Reliability assessment of microgrid with renewable generation and prioritized loads

With the increase in awareness about the climate change, there has been a tremendous shift towards utilizing renewable energy sources (RES). In this regard, smart grid technologies have been presented to facilitate higher penetration of RES. Microgrids are the key components of the smart grids. Microgrids allow integration of various distributed energy resources (DER) such as the distributed generation (DGs) and energy storage systems (ESSs) into the distribution system and hence remove or delay the need for distribution expansion. One of the crucial requirements for utilities is to ensure that the system reliability is maintained with the inclusion of microgrid topology. Therefore, this paper evaluates the reliability of a microgrid containing prioritized loads and distributed RES through a hybrid analytical-simulation method. The stochasticity of RES introduces complexity to the reliability evaluation. The method takes into account the variability of RES through Monte- Carlo state sampling simulation. The results indicate the reliability enhancement of the overall system in the presence of the microgrid topology. In particular, the highest priority load has the largest improvement in the reliability indices. Furthermore, sensitivity analysis is performed to understand the effects of the failure of microgrid islanding in the case of a fault in the upstream network

An improved firefly algorithm for optimal microgrid operation with renewable energy

Lately, an electrical network in microgrid system becomes very important to rural or remote areas without connection from primary power grid system. Higher cost of fuels, logistic, spare parts and maintenance affect the cost for operation microgrid generation to supply electrical power for remote areas and rural community. This project proposes an Improved Firefly Algorithm (IFA), which is a improvement of classical Firefly Algorithm (FA) technique using characteristic approach of Lévy flights to solve the optimal microgrid operation. The IFA has been used for optimizing the cost of power generation in microgrid system where daily power balance constraints and generation limits are considered. The microgrid system for this case study considered both of renewable energy plant and conventional generator units. There are two test systems that have been considered as case study. The first test system is a simple microgrid system which consists of three generators. The second test system consists of seven generating units including two wind turbines, three fuel-cell plants and two diesel generators. The IFA method has been implemented using MATLAB software. The results obtained by IFA was compared to FA and other algorithms based on optimal cost, convergence characteristics and robustness to validate the effectiveness of the IFA. It shows that the IFA obtained better results in terms of operating costs compared to FA, Differential Evolution (DE), Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA)

Load flow studies on stand alone microgrid system in Ranau, Sabah

This paper presents the power flow or load flow analysis of Ranau microgrid, a standalone microgrid in the district of Ranau,West Coast Division of Sabah. Power flow for IEEE 9 bus also performed and analyzed. Power flow is define as an important tool involving numerical analysis applied to power system. Power flow uses simplified notation such as one line diagram and per-unit system focusing on voltages, voltage angles, real power and reactive power. To achieved that purpose, this research is done by analyzing the power flow analysis and calculation of all the elements in the microgrid such as generators, buses, loads, transformers, transmission lines using the Power Factory DIGSilent 14 software to calculate the power flow. After the analysis and calculations, the results were analysed and compared

Regression Monte Carlo for Microgrid Management

We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.Comment: CEMRACS 2017 Summer project - proceedings

Distributed MPC for coordinated energy efficiency utilization in microgrid systems

To improve the renewable energy utilization of distributed microgrid systems, this paper presents an optimal distributed model predictive control strategy to coordinate energy management among microgrid systems. In particular, through information exchange among systems, each microgrid in the network, which includes renewable generation, storage systems, and some controllable loads, can maintain its own systemwide supply and demand balance. With our mechanism, the closed-loop stability of the distributed microgrid systems can be guaranteed. In addition, we provide evaluation criteria of renewable energy utilization to validate our proposed method. Simulations show that the supply demand balance in each microgrid is achieved while, at the same time, the system operation cost is reduced, which demonstrates the effectiveness and efficiency of our proposed policy.Accepted manuscrip