Phd Thesis Nuno Silva Final V3

Total Page:16

File Type:pdf, Size:1020Kb

Phd Thesis Nuno Silva Final V3 Alternative design strategies of distribution systems A thesis submitted to Imperial College London For the degree of Doctor of Philosophy by Nuno Filipe Gonçalves da Silva Department of Electrical and Electronic Engineering Abstract In contrast with traditional approaches based either on the analysis of a small specific area or on idealistic networks, the proposed methodology determines optimal network design policies by evaluating alternative planning strategies on statistically similar networks. The position of consumers influences the amount of equipment used to serve them. Therefore, simple geometric models or randomly placed points used in previous researches are not adequate. Using an algorithm based on fractal theory, realistic consumer sets are generated in terms of their position, type and demand to allow statistical evaluation of the cost of different design policies. In order to systematically deal with the problem of determining justifiable network investments, the concept of economically adapted distribution network was investigated and applied in the context of a loss-inclusive design promoting efficient investment policies from an overall social perspective. The network’s components are optimized, after yearly load flow calculations, based on the minimum life-cycle cost methodology, balancing annuitised capital investments and maintenance costs against the cost of system operation. Evaluating the cost of each particular design over statistically similar networks allows statistically significant conclusions to be drawn. The main results include the optimal number of substations for typical urban and rural LV, HV and EHV distribution systems, network costs (investment, purchasing and maintenance) and losses as well as the sensitivity of optimal network design to future energy prices and cost of equipment. The impact of the increasing amount of microgeneration on networks has not been fully addressed to date. There have not been clustering problems in existing networks as a result of customers choosing to install microgenerators, either as a new device or as a replacement of a previous heating system. The operation of microgeneration connected to the distribution network can cause statutory voltage limits, recommended voltage unbalance levels and switchgear fault ratings to be exceeded. However, there are a range of distribution network designs and operating practices and thus the impact will vary accordingly. The operation of distribution networks is approached considering the existence of single or three-phase loads and microgeneration. This would however cause the network to be unbalanced and hence, traditional methods that consider a three-phase balanced system would provide misleading results. Every residential daily load’s behaviour shows rapid shifts from “load valleys” to high peaks due to the random and frequent “switch on/off” of appliances. Modelling each load individually will reveal problematic operating conditions which were not considered when using a smooth load profile. Thus, each and every domestic load was represented by a different load profile and the impact on losses was evaluated. Relating losses, voltages, currents and load unbalance ratio leads to conclusions about the way how to optimise the network with DG. The aim was to investigate and develop methodology for evaluation of the long-term loss-inclusive optimal network design strategies and to determine the effect of the penetration of microgeneration, such as CHP and PV, in realistic distribution networks and optimal network planning. The need for reinforcement of network components will depend on the level of generation and on the extent to which reverse power flows occurs. In most parts of the network, microgeneration exports will not be sufficient to result in any need for network investment. However, if the network was to be planned accounting with DG, capital investment scenarios are presented and compared to existing networks trying to accommodate clusters of microgeneration. Declaration No portion of the work referred to in this thesis has been submitted in support of an application for another degree or qualification of this or any other university, or institution of learning 6 Acknowledgements First and foremost, I would like to express my deepest gratitude to my supervisor Professor Goran Strbac for making my PhD a uniquely enriching experience. This thesis is the result of a challenging, exciting and stimulating process. My supervisor’s expertise, experience, and brilliant ideas were crucial for every step along the way. He entrusted me a considerable responsibility from the very beginning and honestly believed in my commitment to fulfilling his expectations. I will never be able to thank him enough, but I will continue to try to honour his effort through very hard work. Doing my PhD within the Control & Power Group at Imperial College and the Manchester Centre for Electrical Energy (MCEE) has been a privilege. It made this experience much more productive, interactive and stimulating. This thesis greatly benefited from access to a large network of internal and external fellows. I am extremely grateful to Dejan Melovic, Danny Pudjianto, Predrag Djapic, Gan Chin Kim and all colleagues that contributed for the successful completion of this research. A special word of gratitude to Alexandre Pais da Silva, Cristiano Marantes, Manuel Castro, Rohan Choudhary, Salvador Acha and Sebastien Grenard for being more than colleagues and becoming genuine friends providing me with encouragement and guidance. I would like to acknowledge the financial support of Fundação para a Ciência e a Tecnologia (FCT). Furthermore, I would also like to thank Professor Nick Jenkins from The University of Manchester as well as Professor Peças Lopes, Professor Manuel Matos and Professor Vladimiro Miranda from the University of Porto. They all played an important role in my university education and continuously encouraged and supported my research in various ways. Finally, and very importantly, I would like to thank Marlene for being always there for me when I most needed. Her encouragement, support and dedication made it all easier. I want to pay a very special tribute to my parents and sister who will always be my roots and the solid basis of each of my achievements, thanks for being role models for me and always encourage my career development. 7 Table of contents Abstract ...............................................................................................................................................3 Declaration ..........................................................................................................................................5 Acknowledgements .............................................................................................................................7 Table of contents.................................................................................................................................8 List of figures.....................................................................................................................................12 List of tables ......................................................................................................................................18 Publications .......................................................................................................................................19 Glossary .............................................................................................................................................21 1. CHAPTER INTRODUCTION ............................................................................................................................23 1.1. Overview.................................................................................................................................23 1.2. System losses ..........................................................................................................................25 1.3. Distribution network design....................................................................................................27 1.4. Distributed generation.............................................................................................................28 1.5. Scope, objectives and research challenges..............................................................................30 1.6. Thesis structure .......................................................................................................................32 1.7. Key findings and contributions of the thesis...........................................................................35 2. CHAPTER GENERIC DISTRIBUTION NETWORK MODEL .....................................................................37 2.1. Overview.................................................................................................................................37 2.2. Optimal design policy of distribution networks......................................................................39 2.3. Research to determine the optimum electricity distribution network design policy....................................................................................................................................40 2.4. Model of generic distribution network....................................................................................42 2.5. Generation of realistic distribution networks ..........................................................................45
Recommended publications
  • Microgeneration, Energy Storage, Power Converters and the Regulation of Voltage and Frequency in the Low Voltage Grid
    1 Microgeneration, Energy Storage, Power Converters and the regulation of voltage and frequency in the Low Voltage Grid Manuel Campos Nunes, Instituto Superior Técnico, Universidade de Lisboa. in order to reduce the emission of greenhouse gases, focusing Abstract— This paper focuses on the study and development of on the other hand on sustainable energy and energy efficiency a system composed by Microgeneration (MG) and energy storage (e.g Kyoto Protocol or EU2020 [1]). (ES), which together with other similar systems, might avoid over- Many countries offered big incentives for renewable energy and undervoltages, as well as mitigate voltage dips. The system generation. Consequently MG, most of the times using RES, may use the stored energy on deferred. These systems are expected to contribute to the regulation of the voltage and frequency of a has become increasingly popular and distributed generation low voltage grid, especially in the case of an isolated grid. (DG) is part of the electrical grid nowadays. However despite The increase of distributed generation, using mainly renewable all benefits of DG (economical, environmental, reduce of losses energy sources (RES), motivated some technical and operational etc.), it motivates some technical issues and contributes to the issues that have to be approached. Despite all the benefits of deterioration of electric power quality. The electric power distributed generation and renewable energy, the intermittent system changed a lot with the introduction of DG, which character of such type of source and the mismatch between supply and demand might lead to some problems in reliability and consequently leads to a new paradigm with bidirectional power stability of the grid, and to an inefficient use of RES.
    [Show full text]
  • Residential Demand Response in the Power System
    RESIDENTIAL DEMAND RESPONSE IN THE POWER SYSTEM A thesis submitted to CARDIFF UNIVERSITY for the degree of DOCTOR OF PHILOSOPHY 2015 Silviu Nistor School of Engineering I Declaration This work has not been submitted in substance for any other degree or award at this or any other university or place of learning, nor is being submitted concurrently in candidature for any degree or other award. Signed ………………………………………… (candidate) Date ………………………… This thesis is being submitted in partial fulfillment of the requirements for the degree of …………………………(insert MCh, MD, MPhil, PhD etc, as appropriate) Signed ………………………………………… (candidate) Date ………………………… This thesis is the result of my own independent work/investigation, except where otherwise stated. Other sources are acknowledged by explicit references. The views expressed are my own. Signed ………………………………………… (candidate) Date ………………………… I hereby give consent for my thesis, if accepted, to be available for photocopying and for inter- library loan, and for the title and summary to be made available to outside organisations. Signed ………………………………………… (candidate) Date ………………………… II Abstract Demand response (DR) is able to contribute to the secure and efficient operation of power systems. The implications of adopting the residential DR through smart appliances (SAs) were investigated from the perspective of three actors: customer, distribution network operator, and transmission system operator. The types of SAs considered in the investigation are: washing machines, dish washers and tumble dryers. A mathematical model was developed to describe the operation of SAs including load management features: start delay and cycle interruption. The optimal scheduling of SAs considering user behaviour and multiple-rates electricity tariffs was investigated using the optimisation software CPLEX.
    [Show full text]
  • Diversity Factor Calculation Example
    Diversity Factor Calculation Example Didymous and vulgar Geri underexposes her feints compartmentalizes rightly or tritiate inductively, is Nathanil maroonedbloodstained? Oran Conative overdrove Matteo her placidness substantializes enmesh that while twistings Lawerence confide sovietizenights and some frequents flowing morphologically. philosophically. Precognitive and Mccs that are still operating occurrences in a vacuum as a driving the electrical system investments are getting all about diversity factor calculation You can check about working of energy meter in the pagan manner. Only simple static composite load models are described. What drug the mansion of 1 unit? In an ideal world, estimating your electricity usage would be as easy as looking at an itemized grocery receipt. Two sets of diversity factors one for peak cooling load calculations and. Because desktop computer programs while calculating available data used in calculations required confidence in? If they contribute significantly between different. CUSTOMER CARE UndERSTAnding LOAd FACTOR Austin. Cu or all its ip code allows some examples. This arrangement is convenientfor motor circuits. Submitted for publication in connect and Technology for the Built Environment. Establish consistentmethods for residential water heating for hours gives an academic setting up. When the event of a sale occurs, unit costs will then be matched with revenue and reported on the income statement. An HVAC diversity factor which relates to protect thermal characteristics of science facility's. Two general approaches are used to capturthe timevarying value of electricity savings. Electrical Load Characteristics. Before presenting the results, it is justice to give brief overview and the specific parameters used in agile different calculation methods. Although TRMs often provide industryaccepted values or algorithms forcalculatingsavingsusers should not shine that an algorithm is correct because my has been used elsewhere.
    [Show full text]
  • Q Demand Factor Is Defined As a Object Oriented Design Always Dominates the Structural Design a Maximum Demand X Connected Load
    These are sample MCQs to indicate pattern, may or may not appear in examination G.M. VEDAK INSTITUTE OF TECHNOLOGY Program: Mechanical Engineering Curriculum Scheme: Revised 2016 Examination: Final Year Semester VIII Course Code:MEDLO8041 and Course Name: PPE Time: 1 hour Max. Marks: 50 Q Demand factor is defined as A Object oriented design always dominates the structural design A Maximum demand X Connected load A Maximum demand/ Connected laod A Connected laod/Maximum demand Q Load factor is defined as A Average load/Maximum demand A Average load X Maximum demand A Maximum demand/Average laod A Maximum demand X Connected load Q Diversity factor is always A Equal to unity A More than unity A More than than twenty A Less than unity Q Load factor for heavy industries may be taken as A 10 to 15% A 15 to 40% A 50 to 70% A 70 to 80% Q Which of the following is not suitable to use as peak plant? A Hydroelectric power plant A Gas power plant A Diesel elected plant A Nuclear power plant Q Which of the following power plant cannot be used as base load plant? A Diesel power plant A Hydroelectric power plant A Nuclear power plant A Thermal power plant The system supplying base and peak loads will be more economical if power is supplied by _________ Q A Only gas turbine power plant A Only thermal power plant A Only Diesel power plant A Combined operation of various power plants Q Load factor of power station is generally A Less then unity A Equal to unity A More than unity A More than Ten Q Diversity factor is defined as A Sum of individual maximum demands/Maximum demand of entire group A Maximum demand of entire group/Sum of individual maximum demands A Maximum demand of entire group X Sum of individual maximum demands A Maximum demand of entire group + Sum of individual maximum demands Q In order to have lower cost of electrical energy generation A The load factor and diversity factor should be low.
    [Show full text]
  • Load Survey and Maximum Power Demand of Transformers in Power System Network in Ondo State, Ondo West As a Case Studies
    International Journal of African and Asian Studies - An Open Access International Journal Vol.4 2014 Load Survey and Maximum Power Demand of Transformers in Power System Network in Ondo State, Ondo West as a Case Studies AKINRINMADE AKINKUGBE FEDELIS, IJAROTIMI OLUMIDE Electrical Electronics Engineering Technology Department, Faculty of Engineering, Rufus Giwa Polytechnic, PMB 1019,Owo,Ondo State, Nigeria. [email protected], [email protected] Abstract There are number of matrices used to capture the variability of loads, some of them are mainly used in reference to a single end-user and some of them are mainly used in reference to a substation transformer or a specific factor. This paper will examine data like load density, demand factor, load factor, minimum load demand. The paper will critically look into the number of transformer substation under any of the functioning injection substation. Using the above data, the criteria for the stability of the electricity in the area could be carried out. The paper will reveal, the load density, ranges from 0.0003kvA/m 2 to 0.0329kvA/m 2. The load factor ranges from 58.1% to 91.9% and the demand factor that ranges from 1.1% to 4.0%. Keywords : Load density, Load factor, and Demand factor, Injection Substation, Transformer Substation and Stability. 1. INTRODUTION Most of the Industrial and Residential layout in Ondo State are experiencing power outage. This is as a result of over-loading of a particular Transformer in an injection substation which resulted to load shedding (Usifo and Paul 2006). This paper will define the following information: Load Density, maximum demand, Demand factor, Load factor, and Diversity factors.
    [Show full text]
  • SECONDARY DISTRIBUTION SYSTEM OPTIMIZATION METHODOLOGY and MATLAB PROGRAM a Project Presented to the Faculty of the Department O
    SECONDARY DISTRIBUTION SYSTEM OPTIMIZATION METHODOLOGY AND MATLAB PROGRAM A Project Presented to the faculty of the Department of Electrical and Electronic Engineering California State University, Sacramento Submitted in partial satisfaction of the requirements for the degree of MASTER OF SCIENCE in Electrical and Electronic Engineering by Steve Ghadiri Majid Hosseini FALL 2013 © 2013 Steve Ghadiri Majid Hosseini ALL RIGHTS RESERVED ii SECONDARY DISTRIBUTION SYSTEM OPTIMIZATION METHODOLOGY AND MATLAB PROGRAM A Project by Steve Ghadiri Majid Hosseini Approved by: _________________________________, Committee Chair Turan Gönen, Ph.D. _________________________________, Second Reader Salah Yousif, Ph.D. _________________________ Date iii Student: Steve Ghadiri Majid Hosseini I certify that these students have met the requirements for format contained in the University format manual, and that this project is suitable for shelving in the Library and credit is to be awarded for the Project. _________________________________, Graduate Coordinator Preetham B. Kumar, Ph.D. _________________________ Date Department of Electrical and Electronic Engineering iv ACKNOWLEDGMENTS The authors would like to acknowledge Dr. Turan Gonen, Professor of Electrical Engineering at California State University, Sacramento, for his guidance, supervision, patience, and care in recommending and evaluating this project in the area of Power Engineering at California State University, Sacramento. The authors are also appreciative of Dr. Salah Yousif, Professor of Electrical Engineering at California State University, Sacramento, for his excellent instruction in the area of Power Engineering at California State University, Sacramento, as well as being a reader of this project. The author would also like to acknowledge Dr. Preetham Kumar, Graduate Coordinator, and Professor of Electrical Engineering at California State University, Sacramento, for his guidance and direction in completion of this project.
    [Show full text]
  • Chapter 10, Peak Demand and Time-Differentiated Energy
    Chapter 10: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols Frank Stern, Navigant Consulting Subcontract Report NREL/SR-7A30-53827 April 2013 Chapter 10 – Table of Contents 1 Introduction .............................................................................................................................2 2 Purpose of Peak Demand and Time-differentiated Energy Savings .......................................3 3 Key Concepts ..........................................................................................................................5 4 Methods of Determining Peak Demand and Time-Differentiated Energy Impacts ...............7 4.1 Engineering Algorithms ................................................................................................... 7 4.2 Hourly Building Simulation Modeling ............................................................................ 7 4.3 Billing Data Analysis ....................................................................................................... 8 4.4 Interval Metered Data Analysis ....................................................................................... 8 4.5 End-Use Metered Data Analysis ...................................................................................... 8 4.6 Survey Data on Hours of Use .......................................................................................... 9 4.7 Combined Approaches ..................................................................................................... 9
    [Show full text]
  • Variable Load on Power Stations
    CHAPTER3 Variable Load on Power Stations Introduction he function of a power station is to de- liver power to a large number of consum 3.1 Structure of Electric Power System Ters. However, the power demands of dif- 3.2 Variable Load on Power Station ferent consumers vary in accordance with their activities. The result of this variation in demand 3.3 Load Curves is that load on a power station is never constant, 3.4 Important Terms and Factors rather it varies from time to time. Most of the 3.5 Units Generated per Annum complexities of modern power plant operation 3.6 Load Duration Curve arise from the inherent variability of the load de- manded by the users. Unfortunately, electrical 3.7 Types of Loads power cannot be stored and, therefore, the power 3.8 Typical Demand and Diversity Fac- station must produce power as and when de- tors manded to meet the requirements of the consum- 3.9 Load Curves and Selection of Gener- ers. On one hand, the power engineer would like ating Units that the alternators in the power station should run at their rated capacity for maximum efficiency 3.10 Important Points in the Selection of and on the other hand, the demands of the con- Units sumers have wide variations. This makes the 3.11 Base Load and Peak Load on Power design of a power station highly complex. In this Station chapter, we shall focus our attention on the prob- 3.12 Method of Meeting the Load lems of variable load on power stations.
    [Show full text]
  • Tier 2 Chapter 08
    U.S. EPR FINAL SAFETY ANALYSIS REPORT 8.3 Onsite Power System 8.3.1 Alternating Current Power Systems 8.3.1.1 Description The main generator provides power through the station switchyard to the transmission system via an isolated phase bus (IPB) system and three single-phase main step-up transformers (MSU). Incoming power to the onsite AC power system is from the station switchyard during all modes of plant operation, through the emergency and normal auxiliary transformers to the Class 1E and non-Class 1E distribution systems respectively. The main generator is connected to the switchyard via two circuit breakers in the switchyard. Either breaker enables the generator to provide power to the transmission system. During main generator startup and synchronization with the grid, a generator automatic synchronizer is used in combination with an independent synchrocheck permissive relay, which provides a closing signal to the main generator breaker. Prior to main generator synchronization with the transmission system, the plant loads are fed by the transmission system through the switchyard. The main generator circuit breakers in the switchyard are open at this time. The switchyard and offsite power supply arrangement allows station loads to remain powered from the same source during all plant operating modes and eliminates the need for bus transfers during plant startup or shutdown. Main generator protection is provided by a primary and backup protection scheme. Protective device actuation trips the main generator output breakers in the switchyard, trips the generator excitation and initiates a turbine trip. Main generator protection includes stator overcurrent, ground fault and reverse power.
    [Show full text]
  • Analysis of Heating Load Diversity in German Residential Districts and Implications for the Application in District Heating Systems
    Analysis of heating load diversity in German residential districts and implications for the application in district heating systems Claudia Weissmann, Tianzhen Hong, & Carl-Alexander Graubner Lawrence Berkeley National Laboratory Energy Technologies Area September, 2017 Disclaimer: This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California. Analysis of heating load diversity in German residential districts and implications for the application in district heating systems Claudia Weissmann (corresponding author) Institute of Concrete and Masonry Structures, Technische Universität Darmstadt, Franziska-Braun-Str. 3, 64287 Darmstadt, Germany; [email protected] Tianzhen Hong Building Technology and Urban Systems Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720, United States; [email protected] Carl-Alexander Graubner Institute of Concrete and Masonry Structures, Technische Universität Darmstadt, Franziska-Braun-Str.
    [Show full text]
  • Neue Preismodelle Für Energie
    Neue Preismodelle für Energie Grundlagen einer Reform der Entgelte, Steuern, Abgaben und Umlagen auf Strom und fossile Energieträger STUDIE Neue Preismodelle für Energie IMPRESSUM HINTERGRUND ERSTELLT IM AUFTRAG VON Neue Preismodelle für Energie Agora Energiewende Anna-Louisa-Karsch-Straße 2 | 10178 Berlin Grundlagen einer Reform der Entgelte, Steuern, T +49 (0)30 700 14 35-000 Abgaben und Umlagen auf Strom und fossile F +49 (0)30 700 14 35-129 Energieträger www.agora-energiewende.de [email protected] VERFASST VON Dr. Barbara Praetorius, Agora Energiewende DANKSAGUNG Thorsten Lenck, Agora Energiewende [email protected] Für Vorarbeiten in diesem Projekt danken wir Herrn Dr. Thies F. Clausen, dem arrhenius Institut Dr. Jens Büchner, E-Bridge Consulting für Energie und Klimapolitik und der Stiftung Ass. jur. Franziska Lietz LL.M., Umweltenergierecht. Energie-Forschungszentrum der Technischen Universität Clausthal Dr. Vigen Nikogosian, E-Bridge Consulting Dr. Dominik Schober, Zentrum für Europäische Wirtschaftsforschung und Universität Mannheim Prof. Dr. jur. Hartmut Weyer, Technische Universität Clausthal Dr. Oliver Woll, Zentrum für Europäische Wirtschaftsforschung Satz: UKEX GRAPHIC, Ettlingen Bitte zitieren als: Titelbild: eyeem/Nicolás Agora Energiewende (2017): Neue Preismodelle für Energie. Grundlagen einer Reform der 111/03-S-2017/DE Entgelte, Steuern, Abgaben und Umlagen auf Version: 1.2 Strom und fossile Energieträger. Hintergrund. Erstveröffentlichung: April 2017 Berlin, April 2017. Vorwort Liebe Leserin, lieber Leser, im idealen Strommarkt geben Strompreise das Signal und Umlagen fällig werden. Auch an den Sektoren- dafür, dass sich Angebot und Nachfrage in Echtzeit grenzen stimmen die Preissignale nicht: Heizöl und ausgleichen, Flexibilität angeboten wird und Kosten- Erdgas, Diesel und Benzin werden nach anderen Kri- und Energieeffizienz erreicht werden.
    [Show full text]
  • Load Management Operation
    Power system operation & control Al-Balqa Applied University Department of Electrical EnergyDr AudihEngineering 1 Part 2 Variable Load on Power Stations (Load management) Dr Audih 2 Generally each generation plant in any power may have more than one generating units. Each of the unit may have identical or different capacities. A number of power plants can be tied together to supply the system load by means of interconnection of the generating stations. Interconnected electric power system is more reliable and convenient to operate and also offers economical operating cost . Generation unit , Transformer Unit, Converter Unit, Transmission Unit, Inverter Unit and Consumer Point. This combination of all the unit is called the overall power system units. Dr Audih 3 SYSTEM LOAD VARIATION Effects of variable load. The variable load on a power station introduces many troubles in its operation. Some of the important effects of variable load on a power station are : (i) Need of additional equipment and generation units . (ii) Increase in production cost. The variation of load on the power station with respect to time. SYSTEM LOAD From system's point of view, there are 5 broad category of loads: 1. Domestic 2. Commercial 3. Industrial 4. Agriculture 5. Others - street lights, traction. Domestic: Lights, fans, domestic appliances like heaters, refrigerators, air conditioners, mixers, ovens, small motors etc. 1. Demand factor = 0.7 to 1.0; 2. Diversity factor = 1.2 to 1.3; 3. Load factor = 0.1 to 0.15 Dr Audih 4 Generation Transmission Distribution Loads Dr Audih 5 Industrial: Small scale industries: 0-20kW Medium scale industries: 20-100kW Large scale industries: above 100kW Industrial loads need power over a longer period which remains fairly uniform throughout the day.
    [Show full text]