Optimal Placement of Distributed Generation (DG) for Minimizing Power Loss, Voltage Deviation and Harmonics in Electrical Distribution systems.
Abstract:
In this write-up, we will be considering an effective method of optimally placing Distribution Generation for minimizing power loss, voltage deviation and harmonics in electrical distribution systems. This proposed algorithm will determine the optimal location of a specified distribution network, as well as solving the various problems in the distribution system. This new technique will be a hybridized optimization technique that is aimed at solving the same distribution problems and tackling the cost function. In other words, the outcome of the simulation of this technique will be measured with those of other techniques in terms of reliability and capabilities.
Keywords; Distributed Generation, Optimal Placement and sizing, power loss, Resonance, Discrete Particle Swarm Optimization
Introduction
Distribution generation has achieved great attention from researchers in the power sector, due to its working performance in reducing loss of power, increasing consumer reliability and minimizing the cost speculation.[1,2] ] (El-Khattam W et al) and (Pepermans G et al) In recent years, maximizing power loss reduction, voltage fluctuation reduction and minimizing total harmonic distortion in order to achieve consumer satisfaction, low cost and safety has been the major goals of most power supply firms, scientific quests and political agenda. Electric distribution networks are turning out to be extensive and complex prompting higher loss of networks and poor voltage regulation. Studies show that just about 13% of the aggregate force produced is absorbed as I2R loss at the appropriation level (Ng et al. 2000). Consequently to lessen power misfortunes or loss, shunt capacitors are introduced in influence circulation systems to satisfy receptive force.
Distributed or conveyed generation is an electric force source joined straight forwardly to the dispersion networks or on the client site of the meter. Before introducing distribution generation, its belongings on line losses, voltage profile, cut off, measures of infused wavelength and unwavering quality must be assessed independently.
The arranging of the electric network with the vicinity of DG requires the meaning of a few elements, for example, the best innovation to be utilized, the number and the cutoff of the units, the best zone, the best location, the kind of system association, and so forth. The effect of DG in framework working qualities, for example, electric misfortunes, voltage profile, strength, all out wavelength bending and unwavering quality should be fittingly assessed.
The issue of DG siting and sizing is of awesome significance, its establishment at non-ideal location can bring about an increment in loss of power network, suggesting in an increment in expenses and, along these lines having an impact inverse to the visualized.
Numerous methods have been proposed in which their common goal is to reduce power loss improve voltage profiles and for settling the optimal DG problem in electrical distribution system. These methods may be grouped into the taking after classifications: conventional optimization technique and artificial optimization method. Among these strategies, the artificial optimization procedures have been broadly connected in unraveling the optimal DG issue.
The heuristic based strategy is proposed by (Huang et al. 2000) used for selecting optimal placement and sizing of DG in an electrical system and the genetics calculation is connected to discover the optimal sitting and sizing of attached DG location at different capacity levels (Das et al. 2002). The genetics calculation is considered as one of the first meta-heuristic strategies utilized for taking care of optimal DG placement problem however it has some setbacks, for example, disparity and local optimal issues. Fussy logic has been connected to take care of the DG position issue in which the requirements are fortified and the quality are utilized to guide the inquiry procedure to guarantee that the target capacity is enhanced at every cycle process (Masoum et al. 2004).
Other heuristic based strategies incorporate the ant colony utilization province calculation for comprehending the DG sitting and sizing planning problem (Annaluru et al. 2004). In the application of the ant colony optimization for the issue, capacitors ought to be in discrete qualities and not in persistent qualities which are typically more exact.
Literature Review
This paper reviews the method of DG optimal location in power distribution system. It proposes that the technique can be used to determine the optimal location and to solve various problems in a distribution system.in DG optimal placement; heuristic optimization technique is commonly used to study DG problems, there is likely to be some influence on the overall distribution system in terms of power losses, voltage profile, unwavering quality or reliability, power quality or protection and safety. The potential impacts of DG in an electrical system are described below.
Impact of DG paper chapter 2
3.1. Power Loss
DG causes a critical effect in electric loss because of its nearness to the load focuses. DG units ought to be distributed in places where they give a higher deduction of loss. This procedure of DG sitting like capacitor designation is to minimize loss. The primary contrast is that the DG units cause impacts on both the dynamic and reactive power, while the capacitor banks just have impact in the reactive power flow .In feeders with high power loss, a little measure of DG deliberately assigned (10–20% of the feeder load) could bring about a high deduction of misfortunes [28,71–76]. Borges CLT, Falcao DM.
• With the combination of DG in a grid power misfortunes are reduced.
• For a specific DG limit there is an area in the system such that if we join DG at that location power misfortunes are minimum in comparison, when same DG is placed at any other point.
• That specific location where power misfortunes are least, known as optimum location.
3.2. Voltage profile palgerise
The distribution networks are typically controlled through tap changing at substation transformers and by the utilization of voltage controllers and capacitors on the feeders. This type of voltage regulation accepts power flow circling from the substation to the loads. DG presents meshed force flows that may interfere with the customarily utilized regulation practices [28, 58, 86] 86 Barin Alexandre et al 2010 . Since the control of voltage regulation is normally in view of radial power streams, the unsuitable DG assignment can bring about low or over-voltages in the system. Then again, the establishment of DG can have positive effects in the distribution network by empowering reactive compensation for voltage control, decreasing the misfortunes, contributing for frequency control and going about as turning store in fundamental network fault. Under voltage and over voltage conditions can emerge given the inconsistency of DG with the voltage regulation in radial power flow [78–80, 83]. Singh A, Singh B 2010
3.3. Power quality
Power quality refers to the extent to which control attributes adjust to the perfect sinusoidal voltage and current waveform, with current and voltage in parity [87, 91]. To protect the networks from reduction in power quality, it is important for system administrators to ensure as determined least short circuit limit [89]. The connectio
n between distribution generation and force quality is a questionable one. From one viewpoint, numerous researchers stretch the recuperating impacts of distributed generation for power quality issues. For instance, in a location where voltage support is troublesome, distribution generation can contribute because combining propagation generation commonly leads to increase in voltage in the system [81,82,84–86,88,90] additionally specify the potential positive outcomes of distributed generation or voltage support and adjustments of power factor
3.3.1. Excess voltage
if there are numerous DG connections fixed on a particular line, the space in the power stream among feeder lines enlarges because of the back flow from the DG .This difference may bring about the voltage profile or feeder lines to depart from the best possible range [81–85]. The voltage of substation propagation lines is controlled by a line drop compensator (LDC) or programmed timer. Typically, a solitary distribution transformer has a various feeder lines, and the voltage for these lines is regulated in a block.
3.3.2. Voltage fluctuation
The voltage of the local line networks is liable to vary if the output of DG changes over a short period, and this variance would bring about over or under voltage at the users receiving point [91–93]. There is specific concern while setting up systems that depend on essential conditions, for example, wind power or solar voltaic generators are interconnected to the local framework.
3.4. Unwavering quality or realibility
The objective of a power system is to supply power to its users in a conservative and reliable manner. It is necessary to plan and support dependable power networks because cost of interference and power outages can have extreme financial effect on the utility and its end users [28, 58]. Generally, reliability analysis and assessment methods at the distribution level have been far less advanced than at the generation level since dissemination outages are more restricted and less costly than transmission or generation level outages .notwithstanding, analysis of end users outages information of utilities has demonstrated that the biggest individual contribution for inaccessibility of supply originates from distribution network failure. One of the principle purposes of integrating DG to distribution network is to expand the unwavering quality of power supply [58]. DG can be utilized as a reinforcement system or as a fundamental supply. DG can likewise be operated during peak load periods in other to stay away from extra charges. A fundamental issue in distribution dependability evaluation is measuring the adequacy of past service. A typical arrangement comprises of consolidating the impacts of service disruption into indices of framework performance. Unwavering quality records are utilized by system operators and planners as an apparatus to enhance the level of service to the end users [94, 95]. Planners use them to decide the necessities for generation, transmission, and distribution size additions. Operators use them to guarantee that the system is sufficiently vigorous to withstand conceivable faults without disastrous outcomes. Unwavering quality lists are thought to be sensible and rationale approach to judge the performance of an electrical power networks.
Paper modeling science direct palgerise
3. DG Modeling
The effect of DG on speculations deferral relies on upon the number and size of DG units and particularly on DG energy generation designs. Number and size of DG units are considered through various situations with distinctive DG concentration and penetration levels. The DG energy generation example is simulated with a particular model for every DG technology. DG accessibility is additionally incorporated into the simulation. Modeling of DG technology and DG accessibility is illustrated below
Review of optimization techniques and their comparison
Optimal sizes of DG units are determined and are consequently placed in the best location in distribution systems. To find out the optimal size and location of DG units in power systems has been a major challenge to distribution system planners as well as researchers in the field. In tackling this problem many critical review of different methodologies employed; hence in solving this optimization problem. For ease of reference and to facilitate understating, these literatures categorized and discuss the various existing approaches into five different major headings. They are
i. The analytical approaches.
ii. The artificial intelligence approaches.
iii. Hybrid Artificial Intelligent Techniques.
iv. The genetic algorithm (GA) hybrid approaches.
v. Other approaches.
The benefits as well as drawbacks of each approach are thoroughly examined based on the major DGs placement constraint i.e. power losses minimization, improvement of voltage profile, improvement of reliability and power quality.
2.2. Analytical Method
Different analytical method (AM) having been designed for the position of DRG with optimal size in the distribution system. A large portion of the techniques depend on hypothetical, numerical calculations and analysis [15–20]. They have common objectives, which are to decrease the power losses, enhance voltage profiles, discovering optimal location and optimal size. In a work presented in 2004, Wang and Nehrir [18] presented AM to decide the optimal placement in radial as well as system frameworks to minimize the power loss of the framework.
2.2.3 Hybrid Artificial Intelligent Techniques
To design a hybrid intelligent system, two or more AI method is utilized. Within the past decade, hybrid intelligent systems have been used in electrical engineering functions.(Al-Mohammed and Elamin 2003) discuss about a combination optimization problem with a non-differential objective function has been planned and solved utilizing GA, TS, simulating annealing and hybrid GA-fuzzy logic algorithms. According to Hsiao et al. (2004) the capacitor placement problem in distribution system is solved using combined fuzzy GA method. Three particular goals were considered; improve the voltage profile, minimize the total cost of energy loss and capacitor and maximize the margin loading of feeders.(