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Title: | DISTRIBUTION SYSTEM PLANNING |

Authors: | Kaur, Damanjeet |

Keywords: | ELECTRICAL ENGINEERING;DISTRIBUTION SYSTEM PLANNING;SYSTEM PLANNING;AHYBRID POPULATION BASED METHOD |

Issue Date: | 2008 |

Abstract: | Due to ever increasing demand of electric energy, system planning is essential to assure that the growing demand ofenergy can be met by power system additions, which are technically adequate as well as reasonably economical. These requirements necessitate the optimal planning of the power system. In earlier years, planners placed generation and transmission system planning on high priority. But it is observed that distribution system shares 40% of the total investment cost, 75%-80% ofsystem losses and 90% of consumer outages ofthe power system. Distribution % systems are operated at low voltage level and hence the power losses in adistribution system are significantly higher than the transmission system. Thirteen percent of the total power generated is consumed as I2R losses in distribution systems. The pressure of improving the overall efficiency of power delivery has forced the power utilities to reduce the losses, especially at the distribution level which is equivalent to the marginal cost saving that could be realized from the deferred investment in transmission and generation system. Therefore, it has become necessary to consider accurate and sophisticated planning techniques for # distribution system planning in addition to planning oftransmission and generation systems. In distribution system planning, distribution system loads determine the size and location of distribution substations, which must be located and sized in such away so as to serve the load at the minimum cost by minimizing the feeder losses and construction costs. The conductor size used in the feeders affects the system economically as well as technically (losses). Beside the conductor size, the feeder routing is to be determined to provide suitable interconnections between distribution substations and consumers with minimum feeder losses. Future load growth is also to be considered in the distribution system planning. Distribution substation siting, sizing and feeder routing are to be considered simultaneously so that the investment required is minimum. In order to maintain acceptable levels of quality and continuity of supply, loop networks are preferred. It is noticed that low power factor problem is commonly encountered in distribution systems, as majority of loads are inductive in nature. The low power factor of the system leads to increased loading on the feeders, reduction in capacity of the system and degradation of consumer voltage profile due to increased voltage drop. Hence improvement of power factor of the system is one of the important aspects of distribution system planning. For improving the power factor, it is common practice to install shunt capacitors. In the present work, above major issues related with distribution system planning have been considered and mathematical models for multiconductor feeder sizing, multi-loops MV network design, optimal distribution substation siting, sizing and routing of feeders and capacitor placement on primary distribution system have been formulated and different techniques have been developed to solve them. As feeders share a major portion of total cost of distribution systems, the optimal planning of feeders is a necessity. Feeders in distribution systems are generally radial in configuration to simplify the protection system and operating procedure. They may be straight or branched in which current flow decreases from source to far end. From economical point of view, the feeders must be designed according to their current carrying capacity and loading so that the total cost of the system and system losses are minimized. Many authors have studied the conductor sizing problem. In the models available in the literature, only the cost of energy losses is considered while cost of power losses is ignored. In feeder design, diversity in load peaks at load points also plays an important role because in the absence of this factor, feeders will be overdesigned. In most of these models, to optimize the problem heuristic approaches have been developed which give near optimal solution. Therefore there is need to develop a technique, which gives optimal solution. In the present work, these additional factors: cost of power losses and diversity in load peak at various load points are incorporated in the model for finding optimal conductor sizes in radial feeders. The model developed is a generalized one and it takes into account nonuniform loading, load growth, load factor, cost of energy losses, cost of power losses and diversity in load peaks at various load points along the feeder. The optimal conductor sizes are determined by minimizing the total cost consisting of cost of conductor and cost of losses subject to the constraints on voltage drop at far end load points and maximum current carrying capacity of feeder sections. An efficient method is presented to solve this problem in which the search space is enumerated partially, systematically and efficiently. To reduce the computational efforts, a set of skipping rules is developed. The effectiveness and applicability of the developed technique is illustrated with the help of 19-segment and 122-segment branched radial test feeders. In medium voltage (mv) distribution network design, reliability and minimum investment cost and cost of losses of the network are major considerations. For reliable systems, it is preferable to use loop networks even though these are operated in a radial configuration. The aim is to design such a network, which supplies each mv/lv substation with an alternate feeding point to assure the reliability of the system while the total cost of installation and energy losses is minimized subject to operating constraints. For network design, usually length of loops and energy losses are minimized subject to operating constraints. While few researchers have made an attempt to consider unserved energy in the minimization problem. But the technique developed to design the network is not generalized one. So, there is need to develop an efficient technique for the same. Hence in the present work, a mv network is designed so that each mv/lv substation can be supplied from two sources ofsupply from the same hv/mv substation. While the total y cost consisting of fixed cost of conductor lengths, variable cost of energy losses and cost of unserved energy (due to feeder, circuit breakers and transformer failures) is minimized subject to technical constraints. In the present work, a method has been proposed in which first of all, using supervised technique (K-means and Multi Class Support Vector Machines) mv/lv substation are classified in different clusters corresponding to their geographical location. Then mv/lv substations are connected in loops so that alternate source of supply can be provided to each mv/lv substation. During loop formation, costs associated with installation of conductor and unserved energy is minimized by solving multi-TSP (Traveling Salesman Problem). Ahybrid population based method, which consists of Ant Colony System, and Genetic Algorithm (ACS-GA) has been proposed to solve multi-TSP problem. This method can explore and exploit search space efficiently. Then to minimize the variable cost ofeach multi-loop, conductor size is selected for worst condition (when there is a feeder segment outage near to the source end) satisfying constraints on maximal allowable voltage drop and current carrying capacity. In addition to this, in the designed network, position of a tie switch is also determined using a heuristic approach, which opens a branch in the multiclosed loop to minimize losses for radial operation of the network. The developed method is applied to design a 45-bus testsystem. In distribution system planning, distribution substation siting, sizing and feeder routing is considered simultaneously so that consumers can be supplied power at minimum cost with good quality of service. Asignificant number of studies have been carried out by many researchers to develop suitable approach for finding optimal solution of this problem. During last two decades, in researchers have developed Evolutionary algorithm, Expert system, Genetic Algorithm, Ant Colony System algorithms to solve this distribution system planning problem. In most of the models, the site and size of distribution systems and feeder routing are considered. But this planning problem is also affected by the site and size of grid substations and routing of primary feeders. Basically grid substations, distribution substations and primary and secondary feeders are interlinked with each other. To get an optimal solution, these factors should be considered in the problem formulation. If this planning problem is solved as two subproblems, then the solution obtained would be sub-optimal. Which may result into more investment and operating cost and hence there is a need to develop a model, which takes into account the site and size of grid substation and routing of primary feeders along with the siting and sizing of distribution substation and secondary feeders routing simultaneously. In the present work, a generalized mathematical model to determine siting and sizing of grid substations, distribution substations and primary and secondary distribution feeders routing has been developed. The proposed model is also applicable for network expansion problem. The decision variables corresponding to new installation and/or expansion of existing facilities are optimized. The total cost consisting of fixed cost of installation of new facilities/ reinforcement of existing ones and variables cost representing cost of losses is minimized while constraints on voltage, power balance, demand and bounds on variables are within limits. The model is solved using a discrete Particle Swarm Optimization based approach. In this approach, discrete Particle Swarm Optimization is applied for optimizing the feeder routing and for size selection of existing/new facilities. The proposed approach is based on random generation of population, so the diversity of the solution is maintained. PSO has certain advantages over other population based methods like its convergence is faster, it doesn't trap in local minima and there is balance between local and global minima. Hence the technique developed has all these advantages and it can be applied to large size systems also. The applicability of the proposed approach is demonstrated with the help of a 56-bus test system. To exploit economical and technical benefits due to capacitor placement in an optimal way under various operating constraints, distribution planners are required to determine the optimal locations, types, size, and time of installation of capacitors to be placed. IV The capacitor placement problem has been solved by many researchers with different problem formulations and approaches. Most of the authors formulated net cost saving due to reduction in peak power and energy losses against the capacitor cost as constrained optimization problem subject to operating restrictions. The optimum capacitor placement has been determined using sophisticated methods such as Genetic Algorithms, Ant Colony Algorithm and Particle Swarm Optimization. The capacitor allocation problem is solved as asingle time period problem by most of the research workers. There is no model available in the literature, which takes into account the load growth truly with time in the formulation. In this work, to maintain the voltage profile, a dynamic model considering multiperiod capacitor allocation problem ofprimary radial distribution system is formulated. The model incorporates the load growth rate, load factor and cost of power and energy losses. This multiperiod optimization problem is solved using a population based swarm method i.e. ACS for minimizing the total cost of the peak power losses and energy losses and cost of capacitor installation from base to horizon year (for the feasible options at each planning year) subject to constraints corresponding to upper and lower bounds of the voltage magnitude at each bus. The feasible set of options for optimal capacitor site and size placement in each single stage problem is obtained using particle swarm optimization To reduce the computational efforts in each stage, the candidate nodes for placing capacitors in distribution system are determined by calculating change in real power losses with respect to reactive power injection at the buses. The proposed approach has been implemented on 14 and 69-bus test systems. In short, in the present work, efforts have been made to develop methods to solve the distribution system planning problem as given below: > A model has been developed for finding conductor sizes in a radial feeder considering cost ofpower losses and diversity in load peaks in addition to growth in load, load factor and cost of energy losses. APartial Enumeration Technique for optimal feeder design has been developed to solve this problem. > To design reliable and minimal cost multi-loop distribution system, supervised technique for classification of mv/lv distribution substations; ACS-GA for optimum loop formation; an economical method for conductor size selection under worst condition and a heuristic approach for determining the location of tie switch have been developed. > A model has been developed for distribution system planning considering grid substation, distribution substation and primary and secondary feeders. A discrete PSO based approach has been proposed to solve the developed model. > A dynamic model for capacitor allocation problem is formulated. A Swarm based (PSO-ACS) approach to solve multiperiod capacitor placement problem of a radial distribution system has been developed. |

URI: | http://hdl.handle.net/123456789/1844 |

Other Identifiers: | Ph.D |

Research Supervisor/ Guide: | Sharma, Jaydev |

metadata.dc.type: | Doctoral Thesis |

Appears in Collections: | DOCTORAL THESES (Electrical Engg) |

Files in This Item:

File | Description | Size | Format | |
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DISTRIBUTION SYSTEM PLANNING.pdf | 8.09 MB | Adobe PDF | View/Open |

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