Published May 15, 2015 | Version v1
Journal article

Optimal power flow based TU/CHP/PV/WPP coordination in view of wind speed, solar irradiance and load correlations

Description

Highlights: • Formulate probabilistic OPF with VPE, multi-fuel options, POZs, FOR of CHP units. • Propose a new powerful optimization method based on enhanced black hole algorithm. • Coordinate of TUs, WPPs, PVs and CHP units together in the proposed problem. • Evaluate the impacts of inputs' uncertainties and their correlations on the POPF. • Use the 2m + 1 point estimated method. - Abstract: This paper addresses a novel probabilistic optimisation framework for handling power system uncertainties in the optimal power flow (OPF) problem that considers all the essential factors of great impact in the OPF problem. The object is to study and model the correlation and fluctuation of load demands, photovoltaic (PV) and wind power plants (WPPs) which have an important influence on transmission lines and bus voltages. Moreover, as an important tool of saving waste heat energy in the thermoelectric power plant, the power networks share of combined heat and power (CHP) has increased dramatically in the past decade. So, the probabilistic OPF (POPF) problem considering valve point effects, multi-fuel options and prohibited zones of thermal units (TUs) is firstly formulated. The PV, WPP and CHP units are also modeled. Then, a new method utilizing enhanced binary black hole (EBBH) algorithm and 2m + 1 point estimated method is proposed to solve this problem and to handle the random nature of solar irradiance, wind speed and load of consumers. The correlation between input random variables is considered using a correlation matrix. Finally, numerical results are presented and considered regarding the IEEE 118-busses, including PV, WPP, CHP and TU at several busses. The simulation and comparison results obtained demonstrate the broad advantages and feasibility of the suggested framework in the presence of dependent non-Gaussian distribution of random variables

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2014.12.070

Additional details

Identifiers

DOI
10.1016/j.enconman.2014.12.070;
PII
S0196-8904(14)01109-1;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
96
Journal Page Range
p. 131-145
ISSN
0196-8904
CODEN
ECMADL

Optional Information

Copyright
Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.