Scenario-based stochastic optimal operation of wind/PV/FC/CHP/boiler/tidal/energy storage system considering DR programs and uncertainties

Energy, Sustainability and Society

Touraj Amraee¹  Ehsan Jafari²  Soodabeh Soleymani²  Babak Mozafari² 

[1] Department of Electrical Engineering, K. N. Toosi University of Technology;Department of Electrical and computer Engineering, Science and Research Branch, Islamic Azad University;

关键词: Micro-grid;    Wind farm;    Photovoltaic;    Combined heat and power;    Tidal steam turbine;    Expected profit;   

DOI  :  10.1186/s13705-017-0142-z

来源: DOAJ

【 摘 要 】

Abstract Background Micro-grid (MG) can be described as a group of controllable loads and distributed energy resources that can be connected and disconnected from the main grid and utilized in grid-connected or islanded modes considering certain electrical constraints. Methods The objective of this article are as follows: (1) predict the uncertainties through the hybrid method of WT-ANN-ICA and (2) determine the optimal generation strategy of a MG containing wind farms (WFs), photovoltaic (PV), fuel cell (FC), combined heat and power (CHP) units, tidal steam turbine (TST), and also boiler and energy storage devices (ESDs). The uncertainties include wind speed, tidal steam speed, photovoltaic power generation (PVPG), market price, power, and thermal load demand. For modeling uncertainties, an effort has been made to predict uncertainties through the hybrid method of wavelet transform (WT) in order to reduce fluctuations in the historical input data. An improved artificial neural network (ANN) based on the nonlinear structure is applied for better training and learning. Furthermore, the imperialist competitive algorithm (ICA) is applied to find the best weights and biases for minimizing the mean square error of predictions. Result The scenario-based stochastic optimization problem is proposed to determine the optimal points for the energy resources generation and to maximize the expected profit considering demand response (DR) programs and uncertainties. Conclusions In this study, three cases are assessed to confirm the performance of the proposed method. In the first case study programming, MG is isolated from grid. In the second case study, which is grid-connected mode, the WT-ANN-ICA and WT-ANN uncertainty prediction methods are compared. In the third case, which is grid-connected mode, the effect of DR programs on the expected profit of energy resources is assessed.

【 授权许可】

Unknown