Kehinde Awodele

Impact of Reward and Penalty Scheme on the Incentives for Distribution System Reliability

Performance-based regulations accompanied by quality regulations are gaining ground in the electricity distribution business. Several European countries apply quality regulations with reward and penalty schemes (RPSs), where the distribution system operator (DSO) is rewarded (or penalized) when fulfilling (or not fulfilling) an adequate level of reliability to its customers. This paper develops a method that the regulator can use before enforcing a regulation to get an understanding of the impact different RPS design solutions have on the DSOs financial risk and incentives to invest in reliability. The proposed method also includes a sensitivity analysis to identify which are the most important parameters in an RPS. The new method is applied to three regulatory challenges to evaluate their RPS design solutions. Results show that the choice of scheme design and cost model used to decide the incentive rate have a large impact on the DSOs financial risk and incentive to invest.

Overview of Common Mode outages in power systems

This paper is a result of ongoing activity carried out by Probability Applications for Common Mode Events (PACME) Task Force under the Reliability Risk and Probability Applications (RRPA) Subcommittee. The paper is intended to constitute a valid source of information and references about dealing with common-mode outages in power systems reliability analysis. This effort involves reviewing published literature and presenting state-of-the-art research and practical applications in the area of common-mode outages. Evaluation of available outage statistics show that there is a definite need for collective effort from academia and industry to not only recommend procedures for data collection and monitoring but also to provide appropriate mathematical models to assess such events.

A concept of dynamic pricing for rural hybrid electric power mini-grid systems for sub-Saharan Africa

This paper presents a dynamic pricing concept that can be applied to hybrid electric power mini-grid systems to enable affordability of energy in these systems setup for the supply of energy to rural consumers. A location was identified in Eastern Uganda, resource assessment done, and a proposed hybrid electric power mini-grid system designed to supply electricity to this rural location. A theoretical deterministic demand profile was generated, and with it different supply configurations of the system were simulated to meet the daily load. The fluctuations in the demand and supply triggered a change in the cost of generating energy, due to the variations in the contributing electricity generating sources. Through communication, an intelligently designed and operated time-varying pricing scheme can be an effective tool for influencing the actions of price-responsive end-users such as rural consumers. A software program was used to simulate the hourly demand, supply, and corresponding cost of energy variations. This pricing model could potentially contribute to the ongoing search for the provision of affordable rural energy services.

Impacts of DG penetration in the reliability of Distribution Systems

The paper investigates the impact of penetration of Distributed Generation (DG) on the reliability of a radial distribution network. The authors evaluate the reliability of a portion of RBTS (Roy Billinton Test System) network with and without DG connection at different load points. Reliability assessment is performed using the analytical and Monte Carlo simulation techniques and enhancement of reliability is compared with both methods for DG placement at different load points. It is found that the analytical evaluation method only evaluates the expected values. The expected values do not give any information on the variability of the indices, which could happen in practice. On the other hand, Monte Carlo simulation is able to take into account the variability of the indices. The results demonstrate that DG penetration does improve the reliability of the radial distribution network and the location of DG in the network has an impact on the extent of improvement. Results clearly indicate that different locations give different reliability improvements and the location with the best improvement might be chosen.

Reliability impact of different smart grid techniques on a power distribution system

This paper focuses on the application of certain smart grid technologies to a distribution system and the impact on reliability. Smart grid techniques were researched thoroughly in the form of a literature review. Some of the techniques that were considered to impact on reliability were selected to be modeled using Monte Carlo simulation performed in MATLAB. The RBTS bus 5 feeders 1 & 2 were chosen to have the techniques modeled on. The simulations were separated into cases with 2 base cases and 5 smart grid techniques application cases. Each technique was implemented separately with the last case being a combination of all techniques. The techniques were shown to improve the reliability indices although the amount of improvement varies between techniques.

Reliability evaluation of distribution networks using fuzzy logic

Reliability is a measure of performance. This measure can be used to help systems meet performance criteria, to help quantify comparisons between various options, and to help make economic decisions. This paper presents a fuzzy knowledge based approach for reliability evaluation of a distribution network. This approach makes a direct assessment of the network configuration, distribution substation, the maintenance policy and the weather and assigns to the network under consideration a reliability index by expressing those variables mathematically using fuzzy logic. Results obtained using the fuzzy model on actual utility data are presented and compared to historical reliability indices. The flexibility of the fuzzy model allows for its application in simplification of complex concepts into easily handled models. Because of the simplicity of the model, the speed of computation is very fast. Thus, large systems could be evaluated easily with minimal computation time.

Reliability Evaluation of distribution networks using NEPLAN & DIgSILENT power factory

Reliability Evaluation involves calculating reliability indices which are a measure of how reliable a system is. This evaluation is important to electric utilities since it can show important information about the functioning of the power system. The aim of the research was to view the differences, if any, between results obtained from running reliability analysis tools in NEPLAN v5.5.1 and DIgSILENT Power Factory v14.0.511. A demo version of NEPLAN version 5.5.1 was used to obtain one set of results. The other set of results were obtained from the university licensed DIgSILENT Power Factory version 14.0.511. In order to compare these results a third method was chosen, Failure Mode and Effects Analysis, to get base values for comparison. Due to its simplifying assumptions, NEPLAN gives different results; it also does not display all of the system indices with the assumption that one can use the given ones to calculate the rest. DIgSILENT has hidden components that can affect the results obtained.

Improving distribution network state estimation by means of Phasor Measurement Units

As more Distributed Generation (DG) is connected to distribution networks; they are evolving from passive networks to active networks. Some of the new characteristics of active networks include bi-directional power flows, voltage profile issues, as well as unintentional islanding, to mention but a few. With these new characteristics, the present monitoring schemes characterized by slow and highly inaccurate measurements are no longer adequate. There is a need to develop a faster, more accurate real-time monitoring scheme. One way of achieving this is by installing Phasor Measurement Units (PMUs) on distribution networks. This paper investigates the impact that PMUs can have on distribution network monitoring. Specifically, it considers the role that appropriate PMU placement patterns have to play in improving Distribution System State Estimation (DSSE). Finally, it investigates the effect of improved system monitoring on the reliability of distribution systems.

Reliability analysis of distribution networks

Historical assessment and predictive methods are normally used to evaluate the reliability of a distribution network. Most utilities focus more on historical assessment rather than predictive methods. Predictive methods are categorised into analytical and simulation methods. The difference between these methods is the way in which the system reliability indices are evaluated. In this paper, the authors apply both analytical and simulation methods to calculate the reliability indices such as System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) for two distribution systems. The Test systems are bus six of the Roy Billinton Test System and a real distribution network in Western Cape, South Africa. Results from these two approaches and some changes in operating philosophy are presented and compared in the paper. Probability distribution of SAIFI and SAIDI which give information about the variability of the indices and are therefore useful for decision making were obtained.

Proof-of-concept load control system using wireless technologies and smart metering techniques

As people in the world consume electrical energy more and more each day, a need for smarter and more resilient power systems arises. By implementing smart metering techniques into the distribution network, consumers can monitor their energy costs and usage which could help reduce global energy demands. Through the use of Smart Meters and Smart Metering techniques and the implementation of such techniques, various areas of application for the model can be assessed and established and the effects on the network can be analysed and quantified. This paper describes the implementation of consumer remote load control which allows consumers to control their own household loads when not at home. Utility Companies can also use the device to reduce the energy demand on the network by remotely switching consumer loads on and off.