Location Of Distributed Generation Units Research Articles

Distribution networks reliability assessment considering distributed automation system with penetration of DG units and SOP devices

The electric utility industry is moving towards a deregulated and competitive market to meet customer expectations. So, system performance and reliability assessments are getting targeted more than before. Several performance measures of reliability are developed in the literature. In this research, the NEPLAN Simulator reliability analysis module is used to determine all the reliability indices in different cases of study considering the effect of the Advanced Distributed Automation System (ADAS). The analysis also benefits from the presence of Penetration of Distributed Generation (DG) units and Soft Open Points (SOP) to enhance system reliability alongside power quality. Therefore, this paper provides a methodology based on a cost/benefit study for distribution networks to define the best location of DG units and SOP devices that leads to better reliability indices. The objectives of the study are demonstrated and investigated through Bus 4 of the standard reliability Roy Bollington Test System (RBTS). NEPLAN uses a tool to apply the Reliability Centered Maintenance (RCM) strategy, which leads to a substantial reduction of maintenance expenses. Simulation results indicate a significant reduction in system reliability cost by 65.8% with significant enhancement in the average of all reliability indices and at each load point too such as Customer Average Interruption Duration Index (CAIDI) which is improved from 40.899 to 29.883, Energy not supplied also is declined by 52.34%. It is also worth saying that, even using DG units or SOP devices separately leads to positive results but the best outcomes are obtained with an appropriate combination of both.

Integrated voltage control and maintenance insurance planning for distribution networks considering uncertainties

Distributed generation (DG) is a promising solution to climate change problems related to rapidly increasing electric power consumption. However, the increasing penetration of DG units poses challenges in enhancing the distribution network reliability owing to their intermittent nature. This paper proposes an integrated voltage control and maintenance insurance planning model for power system reliability under uncertainties in demand loads and active power output of DG units. Voltage control is executed to solve the power quality issue by optimally coordinating the reactive power outputs of the DG units and the active power outputs of storage batteries (SBs). A maintenance insurance scheme is applied to ensure the operating conditions of DG units and SBs in a continuous manner without unexpected interruptions. The reliability indices represented by the voltage deviation cost and expected interruption cost are employed in the proposed planning model to minimize the total power system cost. The decisions include the number and location of DG units and SBs, the reactive and active power of DG units and SBs, respectively, as well as the preventive maintenance cycle and insurance coverage level. A robust fuzzy programming model based on type-2 fuzzy numbers is proposed to obtain the optimal solution in the planning horizon. The application of the proposed model is examined using an empirical case study. The results indicated that the voltage control and maintenance insurance can aid in enhancing the distribution network reliability by reducing the related cost by approximately 26.09%.

Optimal placement and sizing of distributed generation with small signal stability constraint

In recent decades, galloping growth of distributed generation (DG), and its vital role from technical, financial, and environmental point of view, has made it more prominent that DG and its utilization need to be analyzed meticulously. Since most DG units’ output power is DC or is not in accordance with network frequency, they need to be connected to the network via power electronic interface. Therefore, the behavior of power electronic interface and their low inertia can affect distribution system’s small signal stability and optimal size and location of DG unit consequently. In this paper, dynamic models for Inverter-Based DG unit (IBDG), network branches, and loads are utilized in order to scrutinize impacts of small signal stability constraint on optimal size and location of IBDG in radial distribution system (RDS). Similar to many previous studies, a genetic algorithm has been implemented to find optimal size and location of IBDG with the aim of total active power loss minimization. Simulation results on the IEEE 33-bus test system show that, DG placement studies without small signal stability consideration, can lead to inaccurate outcomes which have deleterious impacts on small signal stability.

Solution of distributed generation allocation problem using a novel method

<p>In this paper, A novel optimization technique called whale optimization algorithm (WOA) is modified, used and implemented to find the best possible solution to the problem of optimal locating and sizing of Distributed Generation (DG) resources such as photovoltaic cells, fuel cells and kVAR compensators in radial distribution feeders. The modified technique is used for the first time to solve this kind of optimization problem which includes optimal sizing and location of DG units in radial distribution feeder.</p><p>The proposed method is applied to two different test distribution feeders (15 bus and 33 bus test systems) using different DG types and the acquired results are analyzed and compared to other modern optimization methods to confirm that they give the best results, lowest system real power losses and highest voltage profile improvement among the other modern methods implemented on the same test systems.</p>

Optimal Allocation of Distributed Generation With Optimal Sizing of Fault Current Limiter to Reduce the Impact on Distribution Networks Using NSGA-II

Nowadays, the presence of distributed generation (DG) units in the distribution network is increasing due to their advantages. As well as these advantages, there are some problems, such as increasing the level of short circuits in buses and disturbing the protection operation of the network. The main objective of this paper is optimal using of fault current limiters (FCLs) in series with DG units to reduce the negative impacts of the DG units. The method of simultaneously determining the optimal location and size of DGs and the optimal size of FCLs is proposed in this paper. By appropriate allocation of DG units in the distribution network, a considerable reduction in the size of fault current limiters can be achieved. The locations of DG units are considered to be discrete variables and the sizes of FCLs and DGs to be continuous variables, and a nondominated sorting genetic algorithm (NSGA-II) is used to reduce losses and optimize the sizes of fault current limiters. The proposed method is implemented on two test networks and the results demonstrate the efficiency of the method.

Protection Method for Radial Distribution Systems With DG Using Local Voltage Measurements

This paper presents a voltage-based protection method for distribution systems with distributed generation (DG). Considering the fact that any system fault is associated with a voltage dip at the faulted line ends, a novel protection relay characteristic is formulated from an extensive analysis of voltage behavior during fault conditions. The proposed method is independent of type, size, and location of DG units, as well as grid-connected or islanded (stand-alone) mode of operation of the distribution system. Moreover, the method is communication-less and uses only the local voltage magnitude to determine the relay operating time, hence, a low-cost protection method is provided. A threshold voltage level is defined outside the nominal voltage range. However, if under a fault condition the voltage dip is still within the nominal range, a current starter is used to trigger the relay. The effectiveness of the proposed method is verified by several simulation tests carried out on low voltage (LV) and medium voltage (MV) distribution systems under different fault condition and DG size and location for grid-connected and islanded modes of operation. The simulation results show the protection method is selective with appropriate speed, and the protection settings are independent of the distribution system modes of operation.

Adequate Topology for Efficient Energy Resources Utilization of Active Distribution Networks Equipped With Soft Open Points

Active distribution networks concerned with providing efficient control technologies for large-scale integration of distributed generation (DG) units into the distribution systems. This research proposes a methodology for distribution networks reconfiguration by controlling number, sharing, size, and location of DG units. Also, the soft-open points (SOPs) are added instead of the tie line switches. The SOPs are benefited with its high capability in controlling active/reactive power flow to enhance transmission system performance. The main target of this work is to increase the efficiency of energy utilization through minimizing the power system losses and improving system voltage profile while preserving all system constraints within permissible limits with reliable and flexible networks in normal and abnormal conditions with a suitable penetration level of DG. A modified particle swarm optimizer is developed to find the best system configuration, size, and placement of DG units as well as the size and allocation of SOPs. Research methodology is tested on two standards: the IEEE 33-node and 69-node distribution networks under different operating cases. This paper compares the obtained results with those in the literature to prove the capabilities of the proposed work. Finally, the suggested work pursues the optimal number of DG units with their appropriate penetration levels and selects the most convenient location of SOPs for adequate network reconfiguration.

Optimization of radial unbalanced distribution networks in the presence of distribution generation units by network reconfiguration using harmony search algorithm

This paper presents a new approach for solving the rearrangement of the unbalanced distribution network. Objectives such as reducing power losses, improving the voltage profile and increasing the voltage stability index of the system are also pursued in this article. In the other part of this paper, we have rearranged the distribution network by using the optimal location of dispersed production units. Harmony search algorithm is used to achieve these goals simultaneously, as well as the optimal location of distribution generation units in the distribution network. Performing a rearrangement in the presence of optimal distribution generation units positions leads to far better results. A fast load distribution technique called the bus injection to branch current and branch current to bus voltage has been used to perform online rearrangement. In solving the stated target functions, the voltage constraints, line flow capacity and the radial limitation of the distribution network are also considered. Then, separately, we explain the target functions described in the article. The proposed method on the standard system is IEEE 25-Bass test which is done in two scenarios including: (1) rearrangement of unbalanced distribution network without the presence of distribution generation units, (2) rearrangement of unbalanced distribution in the presence of distribution generation units. The results obtained at each scenario of simulation were compared with each other and with the results obtained before the rearrangement. Finally, the best and most effective results are presented. Simulation is done using MATLAB software.

Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

The demand of electricity is soaring rapidly. Distributed genera-tion (DG) is one of the most suitable alternatives to fulfill this swellingdemand of energy. DG is a small scale generation which is directly in-stalled in the distribution network or at load centre. Optimal allocationof DG is a vital factor in improving the voltage profile of the system andin reduction of total power losses. In this article, a detailed study of threedifferent methods for DG allocation and sizing has been discussed. Thefirst method is based on Newton Raphson load flow based technique todeduce the optimal location of DG in two different IEEE bus systems inMATLAB software. The next methodology is based on particle swarmoptimization (PSO) technique where a multi-objective function is beingminimized. The objective function has been modified and PSO has beenimplemented to attain optimal size and location of DG unit. The thirdmethod considered is based on human opinion dynamics evolution-ary multi-objective optimization technique which is used to obtain thebest possible size and location of DG unit in IEEE 14 and IEEE 30 bussystems. The human opinion dynamics method shows superiority inminimizing the size and location muti-objective function, over the othermethods considered herein.

Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

The demand of electricity is soaring rapidly. Distributed generation (DG) is one of the most suitable alternatives to fulfill this swelling demand of energy. DG is a small scale generation which is directly installed in the distribution network or at load centre. Optimal allocation of DG is a vital factor in improving the voltage profile of the system and in reduction of total power losses. In this article, a detailed study of three different methods for DG allocation and sizing has been discussed. The first method is based on Newton Raphson load flow based technique to deduce the optimal location of DG in two different IEEE bus systems in MATLAB software. The next methodology is based on particle swarm optimization (PSO) technique where a multi-objective function is being minimized. The objective function has been modified and PSO has been implemented to attain optimal size and location of DG unit. The third method considered is based on human opinion dynamics evolutionary multi-objective optimization technique which is used to obtain the best possible size and location of DG unit in IEEE 14 and IEEE 30 bus systems. The human opinion dynamics method shows superiority in minimizing the size and location muti-objective function, over the other methods considered herein.

Adaptive planning approach for customer DG installations in smart distribution networks

The planning of active network management (ANM) schemes for distribution systems with distributed generation (DG) does not consider the random participation of customer-owned DGs. This study analyses and addresses the impact of the integration of customer-owned DG on the planning of ANM schemes and maximum DG penetration limits. The random customer DG installations are incorporated by considering sets of events where in each event the number, size and location of DG units are randomly generated. The events, in a set, are chronologically ordered and used to represent a possible scenario of customer-owned DG installations. A two-phase planning approach is proposed where the problem is formulated as a mixed-integer non-linear programming problem with an objective of determining the optimal ANM scheme for maximising the utility DG penetration considering customer DG installations. Several case studies are conducted on a generic 33 kV UK distribution network, including a comparison with the one-time planning approach. The results show that the optimal ANM scheme will vary with the number, locations and sizes of customer DGs and thus for utilities to achieve maximum DG penetration, it is recommended to adaptively control and equip DG units with the capability of switching between various ANM schemes.

Simultaneous Planning of Renewable/ Non-Renewable Distributed Generation Units and Energy Storage Systems in Distribution Networks

The increased diversity of different types of energy sources requires moving towards smart distribution networks. This paper proposes a probabilistic DG (distributed generation) units planning model to determine technology type, capacity and location of DG units while simultaneously allocating ESS (energy storage systems) based on predetermined capacities. This problem is studied in a wind integrated power system considering loads, prices and wind power generation uncertainties. A suitable method for DG unit planning will reduce costs and improve reliability concerns. Objective function is a cost function that minimizes DG investment and operational cost, purchased energy costs from upstream networks, the defined cost to reliability index, energy losses and the investment and degradation costs of ESS. Electrical load is a time variable and the model simulates a typical radial network successfully. The proposed model was solved using the DICOPT solver under GAMS optimization software.

Distributed Generation Placement in Distribution Network Based on Power-Flow Relations

Installing Distributed Generation (DG) influences distribution network stability and losses. The aim of the Distributed Generation placement (DGP) is to provide the best locations and sizes of DG units to optimize electrical distribution network operation and planning taking into account DG capacity constraints. In this paper a really formula based on Power flow for obtaining DGP and sizing to improve the performance of the distribution network is offered. The aim of this really formula is to eliminate complex and time-consuming algorithms in solving DGP problems. Using the proposed method, one can easily and without complex calculations obtains the size and location of DG units on the network. The proposed method has been tested on several networks and the test results show its effectiveness. The benefit of the proposed method is its low computational burden as well as its simplicity of implementation.

Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches

Integration of renewable energy based distributed generation (DG) units provides potential benefits to conventional distribution systems. The power injections from renewable DG units located close to the load centers provide an opportunity for system voltage support, reduction in energy losses, and reliability improvement. Therefore, the location of DG units should be carefully determined with the consideration of different planning incentives. This paper presents a comparison of novel, combined loss sensitivity, index vector, and voltage sensitivity index methods for optimal location and sizing of distributed generation (DG) in a distribution network. The main contribution of the paper is: (i) location of DGs based on existing sensitivity methods, (ii) proposing combined power loss sensitivity based method for DG location, (iii) modified Novel method for DG location, (iv) comparison of sensitivity methods for DG location and their size calculations, and (v) cost of losses and determining cost of power obtained from DGs and the comparison of methods at unity and lagging power factors. The results show the importance of installing the suitable size of DG at the suitable location. The results are obtained with all sensitivity based methods on the IEEE 33-bus and 69-bus systems.

GA Based Optimal Placement of DGs for Loss Reduction and Reliability Improvement in Distribution Networks with Time Varying Loads

The distributed generation (DG) locations have significant impacts on network reliability and loss. This paper presents a method for optimal DG allocation and sizing in distribution systems in order to reduce network loss and improve system reliability at the lowest cost. For this purpose, a multi-objective cost function considering active power loss, reliability index and DG cost is used to find the optimal size and location of DG units. Also, a load duration curve including four load levels with different weighting factor is considered. Moreover, the optimization technique that is based on Genetic Algorithm (GA) is implemented. In this paper, ECOST index is considered for reliability evaluation in the cost function and also, the effects system reconfiguration, is also considered for reliability assessment. To evaluate the proposed algorithm, the IEEE 33-bus and 69-bus test systems are employed and the results obtained reveal the effectiveness of proposed method.

Sizing and siting of distributed generation in distribution systems for voltage improvement and loss reduction

The integration of distributed generation (DG) into the distribution system brings conspicuous technical and economic benefits to the grid. Yet installation of non optimized sizes of DGs at arbitrary locations can result in degraded voltage profile and increased system losses. This would consequently drive cost escalation, creating an effect against the desired. It is therefore expedient that the sizing and location of DG units should be prudently planned and determined. This paper presents an analytical technique to determine the optimal size and siting of DGs in a distribution system for active power loss reduction and voltage profile improvement. DG unit sizing and siting are calculated using a sensitivity index that combines the exact loss formula and voltage sensitivity coefficients. Investigation is carried out on the IEEE 13 bus test feeder to validate the effectiveness of the proposed method. Aspects related to the connection of non-dispatchable renewable DG to the distribution network and the use of energy storage, as a representative of smart grid technologies, is also discussed.