June 23, 2013
June 23, 2013
June 26, 2013
Electrical and Computer
23.454.1 - 23.454.12
Educational Experiments in Renewable Energy Analysis, Forecasting, and Management in Hybrid Power SystemAbstractIn this paper, analysis, forecasting and management of the renewable power generated by arenewable energy farm including both solar energy and wind energy will be demonstrated. Thisrenewable energy farm is connected to the utility grid, in order to properly cooperate and balancepower between the load and the distributed energy sources, an accurate power forecasting andmanagement model is built based on the analysis of the existing data of load, solar irradiance andwind speed. Considering realistic factors, a stochastic model of local load, available solar energyand wind energy is proposed. The optimal size of the renewable energy farm is achieved basedon the analysis of the stochastic model. Wavelet and back propagation neural network (BPNN)methods are used to forecast both the available power from the optimized renewable energy farmand local short term load for next period. Based on predicting results, the power managementcontroller will adjust the output power of the distributed energy sources to keep the systemvoltage and frequency in stable. The model is built with Simulink and several other toolboxesfrom Mathworks Corp., such as neural network toolbox, statistics toolbox and fuzzy logictoolbox.Educational aspects:Renewable Energy Analysis, Forecasting, and Management can be used for several experimentsand educational aspects; such as • Long term and short term load forecasting o Load forecasting techniques discussed in this paper is a very good example of the application of BPNN in power system. • Energy data analysis and forecasting o Both wind and solar irradiance historical data are analyzed by using Matlab statistics toolbox. It is a good example of the feasibility analysis of renewable energy farm establishing plan. o Also short term energy forecasting will help students get a deeper understanding of how environment factors influencing the output power of the renewable energy sources. • Maximum power tracking for both solar and wind energy o The concept and mathematic equations of the energy conversation from solar irradiance and wind to electricity power are introduced. o Some popular maximum power point tracking techniques is discussed. • Frequency regulation and stability o The concept of frequency regulation and its importance to power system is introduced. o The approach of keeping the hybrid power system’s frequency stable is proposed.• Application of intelligent techniques to power system. o The model in this article is a good example of application of intelligent techniques such as neural network, fuzzy logic to power system. These intelligent techniques can be used widely in power system from analysis, optimization to smart control and operation.
Ma, T., & Mohammed, O. A., & Elsayed, A. T. (2013, June), Educational Experiments in Renewable Energy Analysis, Forecasting, and Management in Hybrid Power System Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19468
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2013 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015