Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2016. / Power fluctuations in a microgrid are caused by disturbances due to the connection and disconnection of Distributed Generators (DG’s), as well as the irregular input of the sun and wind renewable energy. Renewable penetration such as the sun, wind and tidal energy causes intermittency which directly affects the input and resultant output power of a microgrid. Control systems have to be implemented on three different levels to ensure the stability and reliability of the power supplied to the load. This can be achieved by implementing the following: 1) Primary control with mechanical valves and actuators to translate feedback signals through droop control. 2) Secondary control with power electronics to facilitate maximum power point tracking, phase lock loops and switch mode inverters to manipulate the electrical signals to a desired set points including PID control. 3) Tertiary control with software program management to monitor the power flow as well as to evaluate congregated logic and implement decision making. Energy storage systems like super capacitors can compensate for power imbalance by providing excess stored energy to the microgrid for short periods of time. The added advantage of capacitor banks is that it can facilitate power factor correction where inductive loads like rotating motors form large part of the total load. Battery banks can compensate for energy shortage for longer periods of time. The duration of the compensation can be determined by the size, topology and the type of batteries used. The objectives of this study is to improve the unstable power output responses of a renewable energy microgrid by designing and analysing control strategies intended at power wavering compensation which also includes energy storage. Sub control systems is created and simulated in Matlab/Simulink for analytical comparative observations. Results of the simulated model are discussed and recommendations are given for future works.

Microgrid is an essential part of the nation’s smart grid deployment plan, recognized especially for improving efficiency, reliability, flexibility, and resiliency of the electricity system. Since microgrid consists of different distributed generation units, microgrid scheduling and real-time dispatch play a crucial role in maintaining economic, reliable, and resilient operation. The control and optimization performances of the existing online approaches degrade significantly in microgrid applications with missing forecast information, large state space, and multiple probabilistic events. This dissertation focuses on these challenges and proposes efficient online learning and optimization-based approaches. For addressing the missing forecast challenges on online microgrid operations, a new fitted rolling horizon control (fitted-RHC) approach is proposed in Chapter 2. The proposed fitted-RHC approach is designed with a regression algorithm that utilizes the empirical knowledge obtain from the day-ahead forecast to make microgrid real-time decisions whenever the intra-day forecast data is unavailable. Simulation results show that the proposed fitted-RHC approach can achieve the optimal policy for the deterministic case study and perform efficiently with the uncertain environment in the stochastic case study. / Includes bibliography. / Dissertation (PhD)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection

Today, there is a growing number of buildings in a neighborhood and business parks that are utilizing renewable energy generation, to reduce their electric bill and carbon footprint. The most current way of implementing a renewable energy generation is to use solar panels or a windmill to generate power; then use a charge controller connected to a battery bank to store power. Once stored, the user can then access a clean source of power from these batteries instead of the main power grid. This type of power structure is utilizing a single module system in respect of one building. As the industry of renewable power generation continues to increase, we start to see a new way of implementing the infrastructure of the power system. Instead of having just individual buildings generating power, storing power, using power, and selling power there is a fifth step that can be added, sharing power. The idea of multiple buildings connected to each other to share power has been named a microgrid by the power community. With this ability to share power in a microgrid system, a catastrophic event which cause shutdowns of power production can be better managed. This paper then discusses the data from simulations and a built physical model of a resilient microgrid utilizing these principles.

Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.