In Fig. 3, it is possible to see a visual representation of the first two principal components (from the 3D space). From here, it is possible to see the correlation between certain categories of customers. In the figure, the customer labels are R for domestic rural housing, U for domestic urban housing, C for commercial customers and N for new domestic buildings. Almost all of the commercial customer classifications are grouped together as well as certain types of domestic customers where the main divide seems to be whether the customer is urban or rural. The scores of the substations themselves seem to be more concentrated towards the left of the plot which suggests there is a greater influence from domestic customers, in particular those in urban environments. Afterwards, k-means clustering is applied on the three dimensional PC scores and by using the DB criterion, seven clusters are found to be optimal. Fig. 3 shows the clusters in the PC space.
In this paper, an algorithm is proposed and also applied to make a topological analysis in an electricaldistributionnetwork. The topological method applied is Breath First Search. The purpose is to know the operating state of the elements in the network which are either energized o de-energized due to opening or closing of switches. The result of this kind of studies can be applied in graphic interfaces to either make other studies or monitoring. The paper presented here is based on digraph representation, that is, devices that are interconnected and have a unidirectional path; this assumption is based in the fact that each device has a sending bus and a receiving bus. As the electrical devices might not be connected in a sequential form, the use of the classic topological BSF algorithm could deliver some errors. These errors consist in no considering buses in the analysis; therefore, it could identify electrical buses that are not energized when they really are. The algorithm proposed takes this into account and one solution is shown. It is presented two study cases which employ the IEEE 37 bus system test case modified to show the response of the algorithm proposed.
Fuzzy clustering does offer the potential for more insight but the method offered the least corroboration with the principal component analysis in Section 4.3. The method produced cluster centres of a similar nature to the crisp methods but with inconsistent customer values. For the purposes here, the partial membership proved to be more of a hindrance because it made analysing the total cluster more difficult. Regarding the clusters in general, it is desirable for each cluster centroid to be unique in shape with the clusters generally having significant numbers in population size. Apart from a good computational performance criteria, there is also a need for human interpretation. If the clusters appear similar visually or the population is mostly contained in a small number of n clusters where n K then the clustering has lost much of its purpose. Arguably, if the initial data set contains many instances in close proximity to each other then this cannot be helped. However, here there is prior knowledge that on a distributionnetwork of this level that there will be unique profiles each with a healthy population size. The load profiles shown in Western Power Distribution (2013) are evidence of this. Based on this reasoning and the best support of the customer data, K-means is seen as the most appropriate method.
Optimal planning and operation of a power system requires steady state power flow analysis. Power flow analysis determines the steady state voltage at each bus of the system and also real and reactive power flowing in each of the lines. Power flow solution forms the basis of all optimization problems. The distributionnetwork is radial in nature having high R/X ratio whereas the transmission system is loop in nature having low R/X ratio. The distribution systems are known as ill conditioned power systems. The conventional Newton-Raphson  and Guass-Seidel methods, used for transmission system analysis may provide inaccurate results and pose converge problems for the distribution networks.
The multi-objective optimization framework was applied to a 69- bus test network. The results elaborated that SOP is an e ﬀective tool to improve the network operation in power loss reduction, load balancing and voltage proﬁle improvement. With the DG penetration increasing from 0 to 200%, on average, an SOP reduces power losses by 58.4%, reduces the load balance index by 68.3% and reduces the voltage proﬁle index by 62.1%, all compared to the case without an SOP. The analysis of the impact of DG penetrations on SOP performance showed that, the use of SOP facilitates a large increase in DG penetration and provides a signiﬁcant increase in the ﬂexibility of distributionnetwork operation. When compared with the conventional MOPSO method, the proposed integrated method increases the diversity metric by 25% and reduces the mean ideal distance metric by 10%. It is also found that the network with an SOP outperformed the one using network re- con ﬁguration in operation optimization under various DG penetrations. With the DG penetration increasing from 0 to 200%, on average, an SOP outperforms network reconﬁguration on power loss reduction, feeder load balancing and voltage pro ﬁle improvement by 21.7%, 41.1% and 8.7% respectively.
After the analysis of the major categories of the electricaldistribution system the idea is drawn about its complexity. Being a highly labyrinth structure and connected through a number of devices, electricaldistribution system is the end mean to supply electricity to the consumer. The loads which are connected to the highly meshed electricaldistribution system are of different characteristics e.g. either lagging/leading power factor. The connectivity of these loads with power system is through the different devices like transformers, electrical fuses, line switches, circuit breakers, tie switches etc. Since distribution system is designed in such a way that it covers all the consumers in a given area which are usually described as zones. These consumers are connected within the zone by line switches through which they can be connected or isolated as required. There are a number of zones exist within an electricaldistribution system. These zones are connected with each other with the help of tie-switches. To switch the load from one zone to another the switching i.e. opening or closing operation of line switch and tie switch took place respectively. For the switching to be successful the loads connected to the outgoing feeder having contingencies like fault on the lines and overloading of feeders, should be selected in such an intelligent way that the feeder which is going to supply these loads should not get overloaded or meet with any other fault. Due to the number of uncertainties occur during the loading and unloading of a distribution feeder with vague data, advantage is taken by implementing various techniques which works in such a scenario. Various methods have also been formed on the basis of the past experience of the operators and experts working in the distribution system field.
Electrical power are vital important to our modern society nowadays in line with the challenges to provide the most efficient and cost effective way of supplying electricity from industrial area up until residential consumers. The availability of a reliable power supply at reasonable cost is crucial for the economic growth and development of a country . Power Utilities Company nowadays try to enhance and develop their own strategies based on experience, trending, research and studies to meet customer demands as economically as possible at reasonable service of reliability. An analysis throughout the word shows that around 90% of all customer reliability problems are due to the problem in distribution system. Thus, improving distribution reliability is the key to improving customer reliability . The concept of power-reliability is extremely broad and covers all aspects of the ability of the system to satisfy the customer requirements. There is a reasonable subdivision of the concern designated as system reliability which is shown in Figure 2.1.
pipelines flow rate. By dividing a pipeline into a number of electrical elements like Figure 1 until the pressure distribution becomes independent of the number of elements, we can assume the network as a circuit and solve it. In the sample network shown in Figure 2, node 1 is the pressure source with a constant pressure of 5 MPa. Furthermore, at nodes 2 and 3, constant standard volumetric flow rate (flow rate at standard pressure and temperature) of 20 and 40 (m 3 /s) are leaving from network, respectively. Here like an electrical circuit, a clockwise current for loop is considered and by writing KVL and KCL in circuit, electric potential distribution or pressure distribution and the value of flow rate in pipelines can be obtained.
Covering 97% of the state, Queensland’s distribution networks comprise of over 1.7 million poles and 220,000km of powerlines, delivering 34,482GWh of electricity annually (EQL 2018). One of the largest in the world, around 40% of Ergon’s distributionnetwork is single wire earth return (SWER), measuring more than 64,000km (EE, 2018). This vast SWER network, supplying rural and remote regional Queensland, is characterised by sparse customer numbers dispersed across long distances of aging assets. Queensland’s extensive distribution networks continue to age (Ergon & Energex, 2019), and operating in Queensland’s harsh environments, presents a range of technical challenges for the network operators. Maintaining operational reliability and withstanding the forces of increasingly frequent and severe weather events, is a significant challenge in an atmosphere where network customers’ reliability expectations continue to rise.
In this paper, we present the controlling and distribution of electricity from a micro grid deployment in rural areas based on Wireless Sensor Network. The objectives of the project is to minimize the queue at the electricity billing counters , to restrict the usage of energy ,reduce the loss of revenue due to power thefts.The microcontroller is used as heart of the system. The main unit contain a ZIGBEE module which is connected to PC for controlling the electrical lines and the status of usage power will be displayed on PC. The consumer unit contains LPC2148 GSM(Global System for mobile communication) ZIGBEE module relay energy meter LDR and LCD.Energy Meter pulsing led as input to the LDR sensor which is interfaced to microcontroller, proportional to the energy consumed which is calculated by using counter microcontroller. A relay is used to make connection of load.The GSM technology is used so that the consumer would receive messages about the consumption of power (inwatts) and if it reaches the minimum amount, it would automatically alert the consumer to recharge. When balance is zero GSM modem will send SMS to customer for further recharge of energy units and power cut off until recharge is done. The work system adopts a totally new concept of “Prepaid Electricity”.
ABSTRACT: The continuous power outages and interruptions in the instantaneous electrical parts distributionnetwork always adversely affect the health, safety and economic activity and the low level of production in the industrial sector .the paper discusses the reliability of the electric distributionnetwork through the study of indicators of reliability analysis technology which is characterized as a fast, efficient and know that by SAIFI, SAIDI, CAIDI, MAIFI, CTAIDI, in order to repeat the failures at different times for Lines 33KV and 11KV, from readings to the control station for the automated distributionnetwork for the Omdurman area.
Although the individual customer order should be seen as the ultimate profit centre (Gattorna and Walters, 1996), a more selective reporting is needed because distribution profitability analysis concerns the strategic level and the information is directed to the upper levels of the organisation (cf. Bowersox and Closs, 1996). Therefore, calculating the profitability of orders in a period usually aggregates information. Furthermore, some comparative information such as the profitability of earlier periods is often added. Thus, the shifts of profitability during the time are easily seen. But, this output does not provide basic profitability profiles, which should be important basic data (Bowersox et al., 1992). Nor does it assist in comparing the profitability of one customer to another (cf. Christopher, 1993).
of the most critical factors of a network operating system that is supported. Several things become essential parameters in determining an index that complements the distribution system, namely SAIFI and SAIDI. This research is able to know about the high levels obtained by the distribution system at the Wates substation. With this analysis, it is expected that this will become a reference for improving service quality in the coming year. Based on the results of calculations and analyses that have been done, it can be said that the distribution system at the substation has been reliable, because all feeders have met the standards set by the SPLN, IEEE, and WCS, especially the WT 05 feeder meets the standard.
In this paper, we present the controlling and distribution of electricity from a micro grid deployment in rural areas based on Wireless Sensor Network. The objectives of the project is to minimize the queue at the electricity billing counters , to restrict the usage of energy ,reduce the loss of revenue due to power thefts. The microcontroller is used as heart of the system. The main unit contain a ZIGBEE module which is connected to PC for controlling the electrical lines and the status of usage power will be displayed on PC. The consumer unit contains LPC2148 GSM (Global System for mobile communication) ZIGBEE module relay energy meter LDR and LCD. Energy Meter pulsing led as input to the LDR sensor which is interfaced to microcontroller, proportional to the energy consumed which is calculated by using counter microcontroller. A relay is used to make connection of load. The GSM technology is used so that the consumer would receive messages about the consumption of power ( in watts) and if it reaches the minimum amount, it would automatically alert the consumer to recharge. When balance is zero GSM modem will send SMS to customer for further recharge of energy units and power cut off until recharge is done. The work system adopts a totally new concept of “Prepaid Electricity”.
Distribution is a collection of interconnected organization and facility in the process of logistics distributionnetwork. Its ultimate goal is to meet the final customer satisfaction, so as to realize the value of the entire supply chain and strengthen the ability of supply chain. In particular, it includes a number of nodes and the connection among the lines. In the initial distributionnetwork there are only a few suppliers, clients, and a logistics distri- bution center, the connection among them is straightforward. As developing, there will be more suppliers, dis- tribution centers and customers to join the network, through the network of self-organization evolution, forming a complex network of large and complex.
Regardless of clustering technique used, it is desirable to have an idea of the types of customer associated to each substation. By using the PCA investigation in  it is possible to attribute a customer make-up to each of the primary substa- tions. In particular, there is a need to distinguish between do- mestic customers and commercial/industrial customers. Within domestic customers, there is also a distinction between rural and urban domestic customers. In , it was determined that the first principal component (PC1) shows a distinction between domestic and commercial/industrial customers where a positive values indicates a greater influence from commer- cial/industrial customers and a negative value indicates greater influence from domestic customers. The second principal component (PC2) shows a distinction between rural and urban customers where a positive value indicates a greater influence from rural customers and a negative value indicates a greater influence from urban customers. By making this association, it will give supporting evidence for an engineering explanation of resultant clusters. This is useful as both an explanation of the load profiles themselves and as insight into the differences between the clustering techniques.
strength while others property such as electrical is not affected. Due to that, the best technique to determine ageing state of paper is the mechanical strength measurement. However, paper samples from in-service transformers is impossible to obtain. Due to that, non-intrusive methods are used to determine the condition of the paper by measuring by- products of paper ageing from Furanic Compound Analysis (FCA), Degree of Polymerization (DP), and Dissolved Gas Analysis (DGA).
ABSTRACT: This research presents new smart approaches for the estimation and complete analysis of the two main power quality factors (sags and swells) using Neural Networks. Typical power quality (PQ) disturbances include sag, swell, harmonics, transients, over voltage, under voltage, momentary and sustained interruptions in a power supply network. Among all these disturbances, sags and swells get prime status, as they can cause necessary damage to industrial customer’s equipment and can finally lead to shut down of their system. In this study Principal Component Analysis technique (PCAT) is used to pre-process the raw PQ data and reduce the number of characteristics of real PQ data. Refined data characteristics are then processed through Feed Forward Back Propagation (FFBP) & Recurrent Neural Networks (RNN) for the approximation/prediction of sag and swell. Application of RNN on PQ data demonstrates its good approximation abilities (accuracy for sag & swell approximation=96%) as compared to FFBP neural network (accuracy for sag approximation [93.5%] & swell approximation [91.5%]). The results obtained in this paper are likened with the field data of a power corporation in Australia. This research will facilitate power utilities and industrial customers on common identifications to set a base line for PQ parameters and also to evolve a complete plan for better organization of PQ problems
The voltage of the distribution feeders at the zone substation is generally controlled at somewhere from 101% to 103% of nominal voltage. This is achieved by automatically changing the winding ratio of the zone substation transformer incrementally to maintain these values regardless of load levels. The incremental changes of winding ratio range from 1% to 2.5% of the nominal ratio and these ratio changes can boost the output voltage by up to 20% and buck by up to 10%. The load supply is not broken by this process and the method is usually known as On Load Tap Changing (OLTC). The OLTC operation can be complicated but are essentially set up to operate when voltage deviates from the prescribed range by a set amount for a set time, for example if the voltage deviates outside the limits of 101% and 102.5% for more than 90 seconds. The majority of distribution feeders have only the voltage at their source (at the zone substations) regulated to a set value and rely on their construction and set up of the distribution substations to keep the customer voltage within an acceptable range. On some excessively loaded distribution feeder this arrangement does not deliver suitable voltages to the customer. These feeders require additional voltage support, which is generally provided by Voltage Regulators. A Voltage Regulator is a transformer with a winding ratio of nominally 100% and an OLTC with a tap range of up to 20% boost and 20% buck and tap step from 0.5% to 2%. The Voltage Regulator OLTC is controlled to maintain the output voltage in the same way as that done for Zone Substation transformers. These regulators can be operated to maintain the voltage on their downstream side regardless of the direction of power flow and so can be bi-directional. 1.2.12 Impacts of Small DG Systems
Three types of EV charging such as dumb charging, delayed charging, and smart charging were involved in paper . Dumb charging means that EVs are charged like battery depleted without concerning any constraints. Delayed charging is like grid-to-vehicle (G2V) where the grid operator control the EV charging either by ripple control or by financial. Financial instrument motivates EV owners to charge their vehicles during off peak hours with a lower tariff rated. Smart charging needs continuous bidirectional communication between EV battery management system and distribution system operator (DSO) supervisory control and data acquisition (SCADA). Dumb charging had been using in the simulation for investigating a worst case scenario in Hungary. Dumb charging was used because no smart metering infrastructure in Hungary yet. Some assumption has been made in this study such as the customer amount in the network is very large, all customers are independent to decide the time for charging EV, and a single customer only consumes very small percentage on the network performance. Thus, paper concluded that dumb charging causes on increase in transformer loading. When 100% penetration was applied on transformer it may cause serious overloading. Furthermore, dump charging also cause voltage drop but it does not exceed the permissible limits which states 7.5% according to Hungary Standard MSZ EN 50160.