Microgrids: Planning of fuel energy management by strategic deployment of CHP-based DERs – An evolutionary algorithm approach

Planning of fuel energy management of a CHP-based microgrid requires strategic deployment of DERs. Strategic deployment of DERs is meant to select their optimal locations, optimal sizes and optimal technologies. Optimal locations and sizes, which are independent of types of CHP-based DERs used, are selected, here, by loss sensitivity index (LSI) and by loss minimization using differential evolution (DE) algorithm respectively. In the context of planning of a 14-bus radial microgrid present paper incorporates originality in ideas in the analysis technique based on differential evolution (DE) algorithm to evaluate how different optimal output sets of a group of four DERs, while operating within their respective capacity limits as well as tracking an electrical demand without grid participation, could satisfy a range of heat demands, each representing a specific solution of optimal fuel consumption. For investment decision in the perspective of the owner of the microgrid the author performs the analysis with two separate groups of 4-DER each of various sizes – one group with all diesel generators (i.e. All-Dg) and other with mix of diesel generators (Dgs) and microturbines (Mts) (i.e. Mix-DER). As the present microgrid is intended to cater both heat and electric demands, as per profiles, to its all-commercial customers, a boiler is considered as need-based back-up source to meet the deficit of daily heat generation, if any, for balancing the daily heat demand. At the best result of optimal fuel cost of each group obtained from above analysis, an economic comparison is done between the two groups with the help of pay back period (PP), internal rate of return (IRR) and net present value (NPV) of the microgrid to decide better investment option of the two. Results of DE are confirmed and compared with particle swarm optimization (PSO) technique.     

Levelized cost of energy definition – An economic paradox

Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect.     

On the measurement and quantification of electricity affordability in the commercial and industrial sectors – A cost burden approach

This paper proposes a novel method to quantifying the affordability of electricity from the perspective of commercial and industrial establishments. While there is a prolific amount of literature on the quantification of electricity affordability from a household’s perspective, there has been no known attempt to quantify affordability from the perspective of the firm. This paper addresses this gap in the literature by proposing a methodology for quantifying electricity affordability that is aligned with the definition of affordability as laid out in the grid modernization literature and is also derived from the principles of profit maximization of a firm. A demonstration of the effectiveness of this methodology was carried out by its application to publicly available data sets covering different sectors and to firms within those sectors. This simple, yet effective tool will allow policy makers to identify disadvantaged sectors (by city and state) and design policy more effectively so as to benefit them.     

Determination of reduced order model for torsional interaction investigations using selective modal analysis – Part I: Initial approach

This paper presents a new methodology for the determination of reduced order model in torsional interaction investigations. The conventional methods, even though give fast results for the model reduction, the physical meaning of the system is generally lost in the process. The proposed method, based on selective modal analysis (SMA), overcomes the drawbacks of the conventional methods for the determination of reduced order model (ROM). The selective modal analysis gives a reduced order model for subsynchronous resonance analysis preserving the significant dynamics. The formulation is illustrated on linearised model of IEEE first benchmark model (FBM). The companion paper explores the enhancements on the proposed algorithm and its applications to large practical power system.     

A hybrid real coded genetic algorithm – Pattern search approach for selective harmonic elimination of PWM AC/AC voltage controller

Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package. Finally, these results are verified by means of an experimental prototype.