IEEE PES Asia-Pacific Power and Energy Engineering Conference 

About: IEEE PES Asia-Pacific Power and Energy Engineering Conference is an academic conference. The conference publishes majorly in the area(s): Electric power system & Wind power. Over the lifetime, 6216 publications have been published by the conference receiving 23943 citations.

Virtual Power Plant (VPP), Definition, Concept, Components and Types

Abstract: Along with the rising energy consumption in the world, new technologies will influence the way we generate, distribute and consume energy. Alongside others, distributed energy generation becomes a major trend in many countries. The fast upward penetration of Distributed Energy Resources (DER) and the ongoing trend towards a more competitive electricity market requires new technologies and policies to handle both emerging technical and economic issues. In order to handle distributed generation and to intensify its visibility within power markets, the idea of virtual power plant (VPP) has emerged and is used by many researchers. It is composed of combining various small size distributed generating units to form a "single virtual generating unit" that can act as a conventional one and capable of being visible or manageable on an individual basis. Present paper tries to sheds light on main issues related to the idea of the VPP. The paper will review various definitions and primary concept of VPP, its main components, and finally two principal VPP types namely commercial VPP (CVPP) and technical VPP (TVPP).

Short-term prediction of wind power based on deep Long Short-Term Memory

Abstract: This paper proposes a wind power prediction model based on the Long Short-Term Memory model, one of the deep learning method. Deep learning conforms to the trend of big data and has powerful capability of learning and generalization for mass data. Principal component analysis (PCA) is used to choose input samples and reduce the dimensions of the input variables of the LSTM prediction model based on numerical weather prediction(NWP) data. Simulation results show that, compared with BP neural network and support vector machine(SVM) model, the LSTM prediction model has higher prediction accuracy and greater potential for engineering applications. It is effective to apply the Long Short-Term Memory model to the field of wind power prediction.

Research on Battery Supercapacitor Hybrid Storage and its application in MicroGrid

Abstract: This paper presents the utilization of a battery supercapacitor hybrid storage (BSHS) in MicroGrid. The BSHS which is composed of batteries, supercapacitor module, BUCK/BOOST bi-directional converter (BBBC), and voltage sources converter (VSC) has the virtue of high power density and high energy density. With the control loop composed of reference current calculation block and BBBC controller block, the BSHS can compensate the fluctuating power from the renewable energy source such as wind turbine generators and photovoltaics in MicroGrid; and the BSHS can also extend batteries lifetime by optimizing its operating process. A 5 kW laboratory system composes of a supercapacitor module (20 F, 324 V) and a battery module (124 V, 10 batteries) is designed, constructed and tested. Experimental results verify the effective of the proposed control strategy and the excellent performance of the BSHS.

Quantifying Spinning Reserve in Systems with Significant Wind Power Penetration

Abstract: With increasing wind power penetration in many power systems, the requirement of spinning reserve is becoming an important issue, which is directly related to the reliability and economy of the system. To analysis it, there are many uncertainties, such as load forecast error, wind forecast error and generator outage rate, which relate system reserve level to the reliability of it. In this paper, a new method is proposed to quantify the system reserve levels. The method considers the probability distribution of forecast errors of wind and load, as well as generator forced outage rate by using the Expectation of Demand Not Served (EDNS) as evaluation index. The proposed method is then applied to a test system. Results illustrate the relationships of uncertainties with the system reserve level.

LEDs: A Promising Energy-Saving Light Source for Road Lighting

Abstract: Rising demand with diminishing reserves of oil and gas spread the energy crisis all over the world Renewable energy and efficiency technology are the keys to resolve the energy crisis As the improvement in luminous efficacy, LEDs have been an energy-saving choice for general illumination and road lighting This paper made a comparison between LEDs system and HPS system for road lighting to evaluate which one is more energy efficient and discussed some factors may influence the efficiency of LEDs system and HPS system, such as mesopic vision, dimming, color of illumination Though the difference in total luminaire efficacy was not that much in favor of the LEDs, LEDs show a promising prospect in the near future because of the dramatic improvement in luminous efficacy