The modern Distribution Network Planning implements combination of traditional network planning options and so called non-network solutions. Advance load forecasting techniques and simulation of network dynamics based on different topologies, variable system regimes and load categories with detail network and project risk assessments are its core components. It also includes study of network demand management, smart grids, distributed energy resources (DER), embedded generation, energy storage equipment and grid support systems. Modelling of impact on distribution High (HV) and Low (LV) networks of photovoltaic (PV) units and other renewable, alternative and new technologies is now an organic part of distribution planning processes, as well as understanding of all aspects of massive penetration of plug-in electric vehicles (PEV) in electricity network which is expected in near future.
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The ‘traditional’ concept of existing distribution network study has vertical structure distribution planning that includes only partially overview of feeder status (Figure 1.3). Technical characteristics have very basic components, like area of supply, feeder total length and backbone conductor. Feeder capacity and capability are based on its technical characteristics, maximum load and very general weather conditions (summer and winter, day and night) for the entire region. The component of customers represents a simple collection of customer numbers and their major load type characteristics (domestic, industrial, commercial and mixed). In conjunction with feeder technical characteristics and operational performances, this chapter includes very basic ‘customer related’ reliability indices of a particular feeder providing only part of the real reliability picture. As noted, modelling and load and voltage profile components provide only level of constraints based on ‘static’ simulations, as understanding of fault levels was composed together with protection specifics. Finally, feeder load forecast includes future major customers (‘block loads’) and natural load growth without detail understanding of energy forecast and weather corrections.
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nation and planning, the safety benefits of each other, the economic benefits as well as environmental effective will improve, at last, to maximize the social benefit. The model of distribution network planning considering DG presented above will optimize the allocation of resources to be a higher level, at the same time, transform the un- certainty into the certainty in the new grid planning pe- riod, and make planning approachas the way of certainty. Besides the presented penalty factor and coordinated development coefficient which effectively guide con- struction of investment and distribution network planning, are easy to achieve a rational distribution and constant volume of geographical and time-domain as well as to reduce the investment risk of the DG investors and the power supply companies, in line with the sustainable development needs of environmental protection and energy in the new era, to realize the social benefits to maximize accompany with the healthy and harmonious development of the DG construction, distribution net- work planning, the economy and the environment, so as to provide a foundation of further study on distribution network planning considering DGfor the new era.For the reason that the distribution network planning including DGrelates to the stationing and constant volume of DG, the planning and design of distribution network, as well as the calculation and introduction of penalty factor, which will be a challenging and innovative work in the future.
As a weak link in China's economic system, the construction of electric energy transportation system including power transmission network becomes urgent affairs. This paper does a study on optimization of distribution network planning in electric energy transportation system, and proposes imperialist competitive algorithm which based on biological evolution, through the introduction of differential evolution strategy, it can effectively enhance the diversity of the population and retain outstanding individuals, so it can avoid falling into local optimum in the optimization process. A numeric example is employed to validate the effectiveness of the proposed model.
There are some studies that discuss how to model load and renewable uncertainties in distribution network planning models. In order to incorporate the DG reactive capability in distribution planning, a combined PSO and ordinal optimization is proposed considering load and renewable uncertainties, exploiting sub-optimization at each system’s state . Moreover, an interior-point-method-embedded discrete GA is employed to solve MSDEP taking into account uncertainties associated with renewable energy generation and price-responsiveness of customers but not considering load forecast uncertainty . Furthermore, to find the optimal level of renewable DGs and plug-in electric vehicle integration considering uncertainties, a method based on non-dominated sorting genetic algorithm is proposed . Moreover, GA- based multi-stage distribution planning including DGs, rewiring, and network reconfiguration is proposed in  based on one forward and one backward planning. This work is extended to include DR in MSDEP as well . In addition, a hedging algorithm to impose implementability of scenarios regarding load uncertainty in the optimization process is presented in . A modified data envelopment analysis is utilized to evaluate the uncertainties regarding the location of loads after planning a distribution network for different scenarios . A hybrid possibilistic–probabilistic DG and load impact on electric loss in distribution network is proposed . This work is expanded to find the optimal place for DGs using a fuzzy-based approach . Furthermore, a planning approach is developed to examine different air-pollutant management policies considering uncertainties using fuzzy
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to the best levels of downlink coverage (though it is competitive in many places as illustrated by low mean maximum DL coverage difference values) it does result in the best overall combined mean coverage difference indicating that it performs better in terms of DL coverage than DL optimization does in terms of UL coverage. As a result, where time for planning a network is limited, the experimental results presented here suggest that a com- promise in many cases is to optimize for uplink only rather than optimizing in both the uplink and downlink directions.
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A network of roads and road users forms a system for movement, and the premise underlying interactions between users is that they ‘drive on sight’. There is a distinction between the objective ‘visibility’ of a vehicle (for example car, or bicycle and rider) and the ability, for whatever reason, of road users to appropriately perceive other moving objects or people in the road. In countries with relatively low cycle use, like the United Kingdom and New Zealand, cultural emphasis has been placed on the responsibility of the person cycling to be ‘visible’, which simultaneously and implicitly reduces the perceived need of other road users to properly use their senses to ‘perceive’ the other vehicle or person. To some extent, a rebalancing has been recently attempted by Transport for London in a series of advertisements that suggest to the general public and road users in particular that ‘the more you look for something, the more obvious it becomes’. Cycle users generally take up less road space, although they are frequently taller than most private motor vehicles. On the basis of their relatively smaller size, it could be argued that they are relatively less visible. However, a difference in relative visibility is not an argument that a ‘lazy’ road user should be able to make for not having perceived a person cycling: it comes back to the principle that the road network is offered on a ‘drive on sight’ basis.
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This project is basically focused on network deployment for providing a Wi-Fi access for a selected test-bed. In this project, FKEKK building area is taken as the test-bed. Thesis process involves network planning, monitoring, data collection, analyses and optimization of wireless mesh network in order to maximize the usage and quality of the network. Two parameters will be observed namely Received Signal Strength Indicator or RSSI (can be translated to Signal-to-Noise ratio or SNR) and network Throughput.
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Decisive factors of the design of logistic park functions are the needs of the logistics. After the analysis and prediction of the needs can we proceed to the design of logistic parks’ functions. The instruction for the design of logistic park’s functions is logistic park’s development strategy, including the theory, goal, demand of the strategy, which should all be considered in the design. Funds, technology and environment affect the designing process. The development of the technology restrains the effects of the functions. For example, the functions of e-commerce are restrained and supported by electronic network technology; with the support of the limited financial support, the profit return should be considered in the function design while for services with a large capital input and little return, the necessity of the design of them should be taken into the consideration; as environment is a factor that should be noted in the design, it should be noticed that an industrial exploitation on a large scale cannot be conducted if logistic parks are built inside the nature reserves or residential building complexes. The design must follow the principle of the park’s functions being intensive, specialized and further expanded, instead of pursuing the all-roundness single-mindedly and ignoring the efficiency of the land use. Besides, the design must also aim for the advancement and higher profit return.
This paper explains how encrypting power signals helps in preventing power thefts in distribution system with distribution generation. Non-technical loss (NTL) during distribution of power is a major problem in rural India and it has been very difficult for the distribution companies to prevent illegal distribution line tapings. Illegal tapings forms a major chunk of NTL .Due to these losses the power quality decays and load on the generating station increase. The proposed work is an attempt to stop the losses by preventing the power theft; one such method is presented in this paper. In our proposed system we use power semiconductor switching systems at the low voltage side of distribution transformer in such a way that three phases (R,Y,B) & neutral is passed through this semiconductor based switched system .The switching system is operated through the bit sequence generated by the microcontroller. The same bit sequence is generated at the load circuit inbuilt in smart energy meters through RF transmitter- receiver synchronization. The power line between the distribution transformer and the energy meter is protected as encrypted power signal flows through it which cannot be used for running the home appliances, therefore providing protection against illegal distribution line tapping‟s in power networks.
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tag coverage, readers collision avoidance, cost efficiency and good load balance (Ben, Wong, Yujuan, and Li, 2009; I. Bhattacharya and U.K. Roy, 2010; H. Chen and Y. Zhu, 2008; Chen, Zhu, and Hu, 2010; Chen, Zhu, Hu, and Ku, 2011; Di Giampaolo, Forni, and Marrocco, 2010; Y. Gong, Shen, Zhang, Chen, and Zhan, 2011; Leong, Ng, and Cole, 2005, 2006; Lin and Lin, 2007; Qiang, et al., 2006; Yahui, Yujie, Min, and Zhijing, 2009). These challenges formed a new branch of knowledge named RFID Network Planning (RNP). RNP is very crucial before deploying an RFID system because RNP focuses on solving the challenges mentioned above.
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A significant challenge with WNS is that closing links in the network to address sector isolation deteriorates hydraulic behaviour of the network. In particular, network reliability, energy efficiency, and water quality are negatively affected. Graph theory can be used to address the structural requirements, but existing graph-theory techniques cannot address direct access to a source for each sector and sector isolation. Current solutions for WDN partitioning do not address all the requirements of sectorisation. In particular, direct access to a source for each sector and sector isolation are not addressed in most of the existing approaches. Those approaches that do address direct access and sector isolation, cannot handle large networks, as the number of sources is a limiting factor for the number of sectors. The only scalable approach that addresses direct access and sector isolation, does not address some other sectorisation requirements, e.g., pressure requirements during different consumption scenarios, energy efficiency, limited water velocity in pipes, minimum nodal elevation differences within the sectors, and the requirement that sectors should cross as few mains as possible are not addressed.
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All the equipments involved in electric transmission network have got some limited time period on its durability. Periodic change on these equipments is necessary to maintain the standards in electrical network. So spatially managing these with temporal dimension involved will pave way for the system to automatically denote / trigger / tell about the time limit for each and every equipment automatically within a threshold time limit and thereby decreasing the frequent power failures involved in an electrical network. To reach the equipment / to find the exact fault wherein it has occurred could be substantiated presently only by line patrolling through man power. The notified location on the identified network wherein the fault has occurred could not be easily identified and asked for the first responders to act / go to the exact area and rectify the problem immediately
The location and sizing of compensating units (DG, capacitor, etc.) to utility network like: when DG is employed alone or while performing the network reconfiguration in the presence of DG or application of combined DG-capacitor is of great importance to achieve maximum positive benefits. The non-optimal placement can increase the system losses, thereby implying an increase in the cost. DG can be used to accommodate new load growth and provide relief for the over loaded components. The present paper critically reviews of the operational and planning strategies that can be employed to address the various issues of DG planning at the distribution network. The analytical techniques may not be suitable to offer solution to complex problems but the artificial intelligent search techniques may offer flexible and simplified solutions with compromise between solution quality and computation time. A hybrid of two or more approaches can, however, offer a better solution by incorporating benefits of each and discarding their draw- backs.
In order to calculate traffic delays using the proposed method, a number of different data inputs are need- ed, including the geographical characteristics of the road network along with the traffic flows through it at different times of the day. In terms of geograph- ical network features, the length for each link and the flow capacity for each arm of the junction are re- quired. In addition, the traffic volume entering each link of the network throughout the day are required, along with the proportion of vehicles leaving each junction on each of the exit arms and the signal con- trol inputs at each time interval. Note that in this model traffic flows and turning movements are con- stant over each time step. For maintenance model- ling the locations and the arrangements of mainte- nance works are needed, including the type of the road under maintenance, the length of the worksite, the duration of works, the speed restrictions, etc.
The planning part starts with traffic and coverage analysis, information about the geographical area and the expected need of capacity. Drive test also will be done to determine the actual problem of that area. Using the data from traffic and coverage analysis, a nominal cell plan will produce. Nominal cell plan contains the information such as number of sector, antenna height, location of the new station (latitude and longitude) and antenna direction. The next stage is site survey and the survey will consider the nearby obstacles, space for radio equipment and transmission link. The survey will come out with the actual planned data (antenna height, antenna direction, suitable location). After the site survey, the process will proceed with coverage prediction and frequency planning using planning tools (TEMS Cell Planner).
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In effect, a single questionnaire can neither possibly cover all the urban problems nor for such complicated urban planning bring about all-inclusive information on public opinion while citizens are not necessarily main- taining that certain problems are so closely bound up with their life. Factors, as of distinctively different back- ground of intelligence, asymmetrical information and obstruction from design regime, are all along having in- fluence upon public participation in urban planning. Nevertheless, public participation into a process has thus created a kind of collaboration correlate to personal interests, and in this scenario the interests of an individual citizen may associate his/her own opinions with certain issues, whereas these opinions may not be directly cor- related to the individual life but would be taking effect by public participation into practical activities such that finally citizens acquired hands-on understanding to the common interests (Yang, 2012: p. 260).
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Due to integration of non conventional energy source and energy storage device, challenges arise in micro grid planning, operation and control. Due to variation in weather condition there will be change in the load demand and renewable power generation so it may deviate from forecasted values. The lithium-ion rechargeable battery provides a buffer against short term fluctuations in output from renewable energy sources such fluctuation can last for seconds or several minutes long. In order to address these challenges, stochastic modeling and optimization tools can be used for micro grid planning, operation and control.
Abstract — One of the most important problems in the transportation networks is the physical distribution optimization. A huge effort has been invested in cutting the transport costs via computer optimization of vehicle routing. Abstractly, the task is known as the vehicle routing problem (VRP) and there exist many different algorithms for approximate solutions, with various tradeoffs. The main goal of the problem is to carry out deliveries from the central storage facility to all customers incurring minimal costs. Generally, putting VRP into practice presents a number of additional difficulties, from obtaining road network information, gathering data about shipments and packaging to efficient coding of algorithms. The purpose of this paper is to present development and implementation of a transport routing application for a special distribution centre and customer network, the environmental aspect being importantly represented in the model. Namely, the presented distribution optimization model can be a useful tool for trading as well as for manufacturing companies that face problems and questions related to distribution of goods and at the same time aim to be competitive from the eco-friendly aspect, as well. The paper presents new findings on further optimization options of goods distribution and new challenges for further research.
In this paper, in order to achieve the optimal allocation of distributed generation resources with several scenarios in the presence of non-linear loads and shunt capacitors for the network including harmonic distortions, the harmonic load flow method using forward/backward sweep is used and genetic algorithms have also been used for the optimal placement of distributed generation resources for reducing energy losses. The objective function includes the annual energy losses and voltage restrictions on different buses, total harmonic distortions and penetration limits and candidate buses for the installation of distributed generation resources. The proposed method is applied on a 31-buses system and the simulation results in MATLAB software show the ability of the proposed method to improve the energy losses and total harmonic distortions [9,10,2].
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