A mixed-integer nonlinear programming paradigm to solve multi fuel-based environmentally-constrained active-reactive optimal power flow

Abstract

Nowadays the power systems are becoming more competitive; as a result, demanding of more precise and practical models is increasing. This motivates the researchers to focus more on the practical aspects of a power system and develop or propose novel approaches, models, or paradigms. On the other hand, in real world those developments which are solvable via commercial solvers (solver-friendly) are more demanded, therefore, studies on these kinds of novelties are growing. In this regard, the solvers' developers are trying to empower the solvers to address the current concerns of researchers and companies to obtain a faster and more precise solution. Among the practical aspects of a power system, those with discontinuous characteristics are the most complicated aspects to be considered. For example, in optimal power flow (OPF) problems, the prohibited operating zones (POZs) and multiple fuel options are the discontinuous characteristics of generation units. Until now, a nonlinear solver that can handle the discontinuous and logical constraints of nonlinear optimization problems does not exist; therefore, the researchers that concern about such constraints are developing or creating the heuristic-based algorithm to find an optimal solution. The lack of a mathematical model, which is solvable by commercial solvers, for OPF problems considering multiple fuel options and POZs is considered as a big gap in this area of research. In this project, three mixed-integer nonlinear programming model (MINLP) must be investigated to fill the aforementioned existing research gaps. In an economic-oriented OPF, the POZs are considered as constraints while the multiple fuel options is appeared in the objective function as a term of cost function, then the POZs and multiple fuel options have different effects in the problem modeling; in this regard, three different MINLP models must be investigated to address the following existing concerns: 1) OPF problem considering POZs; 2) OPF problem with multiple fuel options; and 3) Multiple fuel-based OPF problem considering POZs. And finally in order to have a more practical model, the effects of reactive power on active power generation via the capability curve, which is a highly nonlinear constraint, is taken into consideration where to address the existing concerns about harmful environmental effects of each technology used to generate electricity, the emission limits such as area emission limits (EMA), sub-area emission limits (EMSA), and system emission limits (EMS) are taken into account as well. In this regard, an environmentally-constrained active-reactive OPF model must be developed. Consequently, the final outcomes of this research project are to propose three Mixed-Integer Nonlinear Programming Models to solve the Environmentally-Constrained Active-Reactive Optimal Power Flow considering POZs, multiple fuel options, and both POZs and multiple fuel options simultaneously. (AU)