Historical data based energy management in a microgrid with a hybrid energy storage system

In a micro-grid, due to potential reverse output profiles of the Renewable Energy Source (RES) and the load, energy storage devices are employed to achieve high self-consumption of RES and to minimize power surplus flowing back into the main grid. This paper proposes a variable charging/discharging threshold method to manage energy storage system. And an Adaptive Intelligence Technique (AIT) is put forward to raise the power management efficiency. A battery-ultra-capacitor hybrid energy storage system (HESS) with merits of high energy and power density is used to evaluate the proposed method with onsite measured RES output data. Compared with the PSO algorithm based on the precise predicted data of the load and the RES, the results show that the proposed method can achieve better load smoothing and maximum self-consumption of the RES without the requirement of precise load and RES forecasting

Control of wind-diesel microgrid using affine projection-like algorithm

This paper deals with brushless generators-based isolated wind-diesel microgrid for rural areas. Here, a permanent magnet brushless dc generator (PMBLDCG) is used to convert renewable wind power into electrical energy. A diesel engine-driven generator based on the squirrel-cage induction generator (SCIG) and a battery storage system (BSS) with a voltage source converter (VSC) deliver power to feed necessary loads. BSS provides load leveling during load variations and wind fluctuations. For such microgrid, control schemes must be accurate and robust to overcome any discrepancy, and able to provide voltage and frequency regulation to the microgrid. Here, voltage and frequency control at the point of common coupling (PCC) is achieved with affine projection-like (APL) algorithm by proper switching of a VSC. This control algorithm is also able to provide reactive power compensation, load balancing, and harmonics suppression, and therefore provides sinusoidal voltage supply. Performance of the algorithm is demonstrated with wide range of test results of developed prototype of proposed microgrid

Integration and Control of Distributed Renewable Energy Resources

The deployment of distributed renewable energy resources (DRERs) has accelerated globally due to environmental concerns and an increasing demand for electricity. DRERs are considered to be solutions to some of the current challenges related to power grids, such as reliability, resilience, efficiency, and flexibility. However, there are still several technical and non-technical challenges regarding the deployment of distributed renewable energy resources. Technical concerns associated with the integration and control of DRERs include, but are not limited, to optimal sizing and placement, optimal operation in grid-connected and islanded modes, as well as the impact of these resources on power quality, power system security, stability, and protection systems. On the other hand, non-technical challenges can be classified into three categories—regulatory issues, social issues, and economic issues. This Special Issue will address all aspects related to the integration and control of distributed renewable energy resources. It aims to understand the existing challenges and explore new solutions and practices for use in overcoming technical challenges