Electric Power Systems Research 105 (2013) 142–151 Contents lists available at ScienceDirect Electric Power Systems Research jou rn al hom epage: www.elsevier.com/locate/epsr Optimization of economic/emission load dispatch for hybrid generating systems using controlled Elitist NSGA-II Ahmed R. Abul’Wafa ∗ Ain-Shams University, Electric Power and Machines, Cairo, Egypt a r t i c l e i n f o Article history: Received 1 January 2013 Received in revised form 3 July 2013 Accepted 13 July 2013 Keywords: Hybrid generation systems Controlled elitist NSGA-II multi-objective optimization Renewable sources of energy Stochastic economic/emission dispatch a b s t r a c t A model is developed for stochastic economic/emission dispatch of thermal/wind/solar hybrid generation system taking into account cost of modern thermal units with multiple valves point effect, polluting gases emission and factors for both overestimation and underestimation of available wind and photovoltaic power. The technique proposed in this work uses novel probability density functions (pdf) of wind power and clearness index to model the wind power and solar irradiance. A multi-objective controlled elitistNSGA-II procedure is proposed to derive a set of Pareto-optimal hybrid system configuration in terms of cost and emission with good diversity. Controlled elitist-NSGA-II favors, not only individuals with better fitness value (rank) as in elitist NSGA-II but also individuals that can help increase the diversity of the population even if they have a lower fitness value. The best compromise solution has been obtained using Fuzzy cardinal priority ranking. Optimal solutions are presented for various values of the input parameters, and these solutions demonstrate that the allocation of system generation capacity may be influenced by multipliers related to the risk of overestimation and to the cost of underestimation of available wind and solar power. A numerical example, including six fossil-fuel-fired generators (FFGs), two Wind Energy Conversion Systems (WECS), and two Photo Voltaic (PV) systems is presented. To validate the effectiveness of the algorithm, results are compared with techniques given in literatures. © 2013 Elsevier B.V. All rights reserved. 1. Introduction Stricter global environment regulations have posed a great chal- lenge to the conventional power generation industry. Distributed generation (DG), using renewable sources of energy has drawn sig- nificant attention from both industry and academia in recent years [1–3]. It offers wider user choices and causes lower emissions. It may also be built much more quickly than central station genera- tors. Multienergy generating system is a representative application for the utilization of renewables, which supplies energy by com- bining the power outputs from different sources [4–7]. Wind and solar power are the two types of fastest growing renewable energy and they are highly environmentally friendly [8–12]. One of the interesting stochastic economic dispatch (SED) formulations that address the uncertainty associated with wind power is proposed in [4]. The cost function includes the operating cost of the thermal unit and wind plants and imbalance cost due to the mismatch between actual and scheduled power outputs of the wind plants. However this formulation does not take into account the solar power. ∗ Tel.: +20 222639022; fax: +20 222639022. E-mail address: Ahmedlaila.nelly.ola@gmail.com In [8] the paper dealt with wind and photovoltaic generated power as negative load, therefore load demand is reduced by wind and photovoltaic power producing a new demand. The authors of [3,8], develop a model to include the WECS generators in the economic dispatch (ED) problem adding factors for both overes- timation and underestimation of available wind power. In [1] the probability of stochastic wind power based on the Weibull proba- bility density function is included in the model as a constraint. The hybrid generating system discussed in this paper comprises different power sources including the traditional fossil-fuel-fired generators (FFGs), wind turbine generators (WTGs), and PV panels (PVs). Both of these renewables are intermittent energy sources since they are highly dependent on weather conditions and geo- graphical locations. Probabilities techniques can be used to express the variability of the wind speed and solar irradiance. The wind speed and solar irradiance distribution primarily determine the performance and the feasibility of wind power and solar power systems, respectively. Modeling wind speed and solar irradiance using proper pdfs provides a few key parameters which can illu- minate the characteristics of a wide range of wind speed and solar irradiance data. In this paper the Electricity Supply Industry (ESI) structure is operated in a Single Buyer manner [13]. The EED model is thus 0378-7796/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.epsr.2013.07.006