Total Factor Productivity Growth of Ghanaian Electricity Distribution Utilities Using Data Envelopment Analysis and Malmquist Index (2000–2020)

The increasing need for electricity access to drive economic growth, social development, poverty alleviation and environmental sustainability requires that efficient allocation of scarce and competing resources in the generation, transmission and distribution subsectors of the electricity sector is indispensable. This paper analyses total factor productivity growth in a single input multiple-output framework in Ghana. The technique applied is data-orientated nonparametric Data Envelopment Analysis using Win4Deap 2 software. Total Factor Productivity Change is evaluated through Malmquist Productivity Index (MPI), as well as technological change (TECHC) and efficiency change (EFFCH) using firm-level panel data. Sources of productivity growth comparison are made between Electricity Company of Ghana (ECG) and the Northern Electricity Distribution Company (NEDCO) for the periods 2000 to 2020. The results show TECHCH marginally declined at an average annual rate of 0.3% and drives the electric power distribution productivity regress in ECG and NEDCO from 2000 to 2020. Further, the results indicate stagnation in scale efficiency, pure efficiency and efficiency change when estimated over 20 years. At firm levels comparison, the study shows that the Northern Electricity Distribution Company recorded a productivity growth rate of 4.9%, mainly due to technical progress. However, the Electricity Company of Ghana experienced a slight deterioration of productivity performance due to a 5.3% decline in technical efficiency. The study offers several policy recommendations on how the underperforming firm can learn to improve efficiency and technical to reduce electricity transmission losses.

An innovative deterministic algorithm for optimal placement of micro phasor measurement units in radial electricity distribution systems

Purpose Heuristic algorithms have been widely used in different types of optimization problems. Their unique features in terms of running time and flexibility have made them superior to deterministic algorithms. To accurately compare different heuristic algorithms in solving optimization problems, the final optimal solution needs to be known. Existing deterministic methods such as Exhaustive Search and Integer Linear Programming can provide the final global optimal solution for small-scale optimization problems. However, as the system grows the number of calculations and required memory size incredibly increases, so applying existing deterministic methods is no longer possible for medium and large-scale systems. The purpose of this paper is to introduce a novel deterministic method with short running time and small memory size requirement for optimal placement of Micro Phasor Measurement Units (µPMUs) in radial electricity distribution systems to make the system completely observable. Design/methodology/approach First, the principle of the method is explained and the observability of the system is analyzed. Then, the algorithm’s running time and memory usage when applying on some of the modified versions of the Institute of Electrical and Electronics Engineers 123-node test feeder are obtained and compared with those of its deterministic counterparts. Findings Because of the innovative method of step-by-step placement of µPMUs, a unique method is developed. Simulation results elucidate that the proposed method has unique features of short running time and small memory size requirements. Originality/value While the mathematical background of the observability study of electricity distribution systems is very well-presented in the referenced papers, the proposed step-by-step placement method of µPMUs, which shrinks unobservable parts of the system in each step, is not discussed yet. The presented paper is directly applicable to typical problems in the field of power systems.

Measure of Customer Satisfaction in the Residential Electricity Distribution Service Using Structural Equation Modeling

The main objective of this study is to apply structural equation modeling with partial least squares and based on covariance to assess the satisfaction of residential electricity consumers. The methodology used compares the results of both structural equation models to indicate the model that best fits the problem of measuring the satisfaction of residential consumers of electricity concessionaires and licensees. The sample used in the survey contained questionnaire responses from 86.175 individuals considering the period from 2014 to 2018. The constructs evaluated were satisfaction, quality, value, loyalty, and trust. Confidence interval analysis shows that all weights are significant, demonstrating the importance of all the indicators that represent the constructs. The trust, quality, and value constructs can explain 74.4% of the variability of the satisfaction construct, so the explanatory capacity of this relationship is considered substantial. Finally, the evaluation of the performance of the service provided by the electric energy concessionaires/licensees, measured by customer satisfaction, allows for the continuous improvement of services and meeting, even if minimally, the expectations of its consumers.

Synchronization of wind farm power supply into the utility grid

Wind turbines and wind farms can be connected to the major electricity distribution system. This paper presents the research results on synchronization of wind farm power supply into the utility grid depending on parameters of the grid at the moment. Measurement time gets synchronized with the external time signal delivered from a navigating system like GLONASS. This can help eliminate antiphase operation of individual wind turbines. Connection diagrams and the whole methodology presented in this paper aim to make wind farm power supply into the grid more effective and loss-eliminating.