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    Convergence of rule-of-thumb sizing and allocating rules of distributed generation in meshed power networks
    (Pergamon-Elsevier Science Ltd, 2012) Ugranli, Faruk; Karatepe, Engin
    This paper presents different approaches to find out and address some rules for distributed generation (DG) integrated mesh type networks, which can be used in the management of future power systems. There are so many influencing factors of efficiency in the integration of DG that we need to analyze these influencing factors obviously. Hence, carefully planning plays a key role in tackling these challenges in the future power systems. In contrast to the majority of existing observations, we focus on the case where the underlying states are multiple and single DG allocations with changing conditions. In several previous studies, the best single bus has been investigated under the specified conditions. However, it follows from the results of this study that all issues concerning DG strongly depend on power network structure and DG locations, and it is worth to note that the best location changes with penetration levels. Also, it is observed that the all buses show different characteristics in terms of DG integrations under the different cases, moreover their optimum size and power factor are different. It means that optimum bus in a network changes with the conditions. On the other hand, the problematic buses can be occurred in voltage profile after the DG integration. As a result, an investigation of rule of thumb approach is performed for evaluation of performance enhancement of DG integrated meshed networks. The results are also used to discuss the integration of DG management strategies under various operating conditions. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.
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    Long-term Performance Comparison of Multiple Distributed Generation Allocations Using a Clustering-based Method
    (Taylor & Francis Inc, 2012) Ugranli, Faruk; Karatepe, Engin
    Distributed generation is becoming a part of the strategic plans of electricity providers for effective system management. The proper planning of multiple distributed generation units plays an important role in modern power systems to offer a highly reliable system. Computation of power flows is one of the major tasks in system planning studies. Conventional load flow analysis methods are impractical to evaluate every possible or probable combination of loads and different allocations of distributed generation units because of the extremely large computational effort required. This article proposes an expansion method to perform load flow analysis with consideration of multiple distributed generation integration and load uncertainties. The proposed approach offers a method to handle the impacts of all possible allocations of distributed generation units without increasing computational efforts. The impacts of placement and penetration level of multiple distributed generation on power losses, voltage deviation, and line capacity are investigated under load uncertainty over a long-term period on the IEEE 57-, IEEE 30-, IEEE 14-, and 9-bus networks for future planning study purposes. The study results indicate that the proposed method has significantly reduced the computational efforts while maintaining a high degree of accuracy in evaluating various possible scenarios in which multiple distributed generation units have to be integrated into the grid.
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    MILP Approach for Bilevel Transmission and Reactive Power Planning Considering Wind Curtailment
    (Ieee-Inst Electrical Electronics Engineers Inc, 2017) Ugranli, Faruk; Karatepe, Engin; Nielsen, Arne Hejde
    In this study, two important planning problems in power systems that are transmission expansion and reactive power are formulated as a mixed-integer linear programming taking into account the bilevel structure due to the consideration of market clearing under several load-wind scenarios. The objective of the proposed method is to minimize the installation cost of transmission lines, reactive power sources, and the annual operation costs of conventional generators corresponding to the curtailed wind energy while maintaining the reliable system operation. Lower level problems of the bilevel structure are designated for the market clearing which is formulated by using the linearized optimal power flow equations. In order to obtain mixed-integer linear programming formulation, the so-called lower level problems are represented by using primal-dual formulation. By using the proposed method, power system planners will be able to find economical investment plans by considering the balance between wind power curtailment and the installation of transmission lines and reactive power sources.
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    Multi-objective transmission expansion planning considering minimization of curtailed wind energy
    (Elsevier Sci Ltd, 2015) Ugranli, Faruk; Karatepe, Engin
    This paper proposes a new multi-objective transmission expansion planning (TEP) in order to find optimum location of lines/transformers by considering intermittent nature of wind power and variable load structure. To reveal the benefit of wind power in the context of TEP, curtailed wind energy is considered as one of the objective functions besides the sum of the investment costs and penalty for energy not supplied (ENS). By this way, a trade-off between investment cost and curtailed wind energy is established using fuzzy satisfying approach while maintaining the adequacy of power system. The multi-objective nature of the proposed method is handled by using the Non-dominated Sorting Genetic Algorithm-II combined with the DC-optimal power flow which is performed several times to obtain curtailed wind energy and ENS. The nature of load and wind power is incorporated into the methodology by using agglomerative hierarchical clustering to reduce computational effort. The proposed methodology is illustrated on the different configurations of modified IEEE-RTS 24 bus test system. Numerical case studies indicate the effectiveness of the proposed method for reduction of total investment cost in TEP of power systems with wind power integration. (C) 2014 Elsevier Ltd. All rights reserved.
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    Multiple-distributed generation planning under load uncertainty and different penetration levels
    (Elsevier Sci Ltd, 2013) Ugranli, Faruk; Karatepe, Engin
    The penetration of distributed generation (DG) in power system is continually increasing. Hence, there is a need to investigate the potential benefits and drawbacks of DGs when integrating DG units in existing networks. The challenge of identifying the optimal locations and sizes has triggered research interest and many studies have been presented in this purpose. Different analytical techniques have been developed to minimize power losses for single-DG unit integration. If DG units are integrated at nonoptimal locations, the power losses increase, resulting in increased cost of energy. The novelty of this paper lies in studying the optimal placement of multiple-DG units in order to minimize power losses. In this study, an optimality criterion is investigated to minimize losses by including load uncertainty, different DG penetration levels and reactive power of multiple- DG concept. The simulation results show that it is not possible to form an analytical equation for optimum planning of DG in terms of load distribution, penetration level and reactive power. Due to the complexity of the multiple-DG concept, artificial neural network based optimal DG placement and size method is developed. The proposed method is implemented to the IEEE-30 bus test network and the results are presented and discussed. The results show that the proposed method can be applied to a power network for all possible scenarios. (C) 2012 Elsevier Ltd. All rights reserved.
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    Multiple-distributed generation planning under load uncertainty and different penetration levels
    (Elsevier Sci Ltd, 2013) Ugranli, Faruk; Karatepe, Engin
    The penetration of distributed generation (DG) in power system is continually increasing. Hence, there is a need to investigate the potential benefits and drawbacks of DGs when integrating DG units in existing networks. The challenge of identifying the optimal locations and sizes has triggered research interest and many studies have been presented in this purpose. Different analytical techniques have been developed to minimize power losses for single-DG unit integration. If DG units are integrated at nonoptimal locations, the power losses increase, resulting in increased cost of energy. The novelty of this paper lies in studying the optimal placement of multiple-DG units in order to minimize power losses. In this study, an optimality criterion is investigated to minimize losses by including load uncertainty, different DG penetration levels and reactive power of multiple- DG concept. The simulation results show that it is not possible to form an analytical equation for optimum planning of DG in terms of load distribution, penetration level and reactive power. Due to the complexity of the multiple-DG concept, artificial neural network based optimal DG placement and size method is developed. The proposed method is implemented to the IEEE-30 bus test network and the results are presented and discussed. The results show that the proposed method can be applied to a power network for all possible scenarios. (C) 2012 Elsevier Ltd. All rights reserved.
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    Optimal wind turbine sizing to minimize energy loss
    (Elsevier Sci Ltd, 2013) Ugranli, Faruk; Karatepe, Engin
    The integration of renewable distributed generation (DG) in power systems has been increasing day by day. One of the most promising DG technologies is wind turbine among the renewable sources. Therefore, the optimization of DG whose the output power is varying with time is very crucial for the future power systems. However, it is difficult to establish a suitable objective function by taking into account of time varying characteristics. In this paper, a methodology based on weighting factors is proposed in order to minimize energy loss by finding the optimal sizes of wind turbines. The optimization is carried out by using the genetic algorithm with utilizing power flow analysis. The contribution of this paper is to allow considering the time varying characteristics of both load and wind-generation profile in a pairwise manner without violating the harmony of correspondence between load and generation profile. In addition, the proposed methodology is merged with the fuzzy-c means clustering to reduce execution time and allow long term planning due to the fact that the computational burden of the genetic algorithm is substantially high. The proposed methodology is applied to the IEEE-30 bus test system for 4 days and annual energy loss minimization scenarios. The results show that energy loss can be reduced significantly by using the proposed methodology. (C) 2013 Elsevier Ltd. All rights reserved.
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    Power System Planning for Maximizing Intermittent Energy Sources using AC Model
    (Ieee, 2013) Ugranli, Faruk; Karatepe, Engin
    As installed capacity of wind power has been increasing in the last decade, power system planners are exposed to the several challenges, with regard to the drawbacks for wind power usage because of the existing infrastructure. The transmission expansion planning (TEP) and reactive power planning (RPP) should be specified by considering the maximization of wind power usage as well as meeting load growth. In this study, a new methodology for TEP and RPP is proposed to minimize wind energy spilled due to the power system constraints such as voltage and transmission line limitations. For this reason, the power flow equations of AC model should be used. Because of the intractable nature of large scale optimization problems, the backward search approach is utilized. AC optimal power flow based economic dispatch is solved to determine optimal dispatches. The proposed methodology is illustrated on the IEEE-24 bus reliability test system to demonstrate the results.
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    Power System Planning for Maximizing Intermittent Energy Sources using AC Model
    (Ieee, 2013) Ugranli, Faruk; Karatepe, Engin
    As installed capacity of wind power has been increasing in the last decade, power system planners are exposed to the several challenges, with regard to the drawbacks for wind power usage because of the existing infrastructure. The transmission expansion planning (TEP) and reactive power planning (RPP) should be specified by considering the maximization of wind power usage as well as meeting load growth. In this study, a new methodology for TEP and RPP is proposed to minimize wind energy spilled due to the power system constraints such as voltage and transmission line limitations. For this reason, the power flow equations of AC model should be used. Because of the intractable nature of large scale optimization problems, the backward search approach is utilized. AC optimal power flow based economic dispatch is solved to determine optimal dispatches. The proposed methodology is illustrated on the IEEE-24 bus reliability test system to demonstrate the results.
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    Transmission Expansion Planning Considering Maximizing Penetration Level of Renewable Sources
    (Ieee, 2013) Ugranli, Faruk; Karatepe, Engin
    Recently, integration of intermittent sources into the power systems has gained most interest in distributed generation environment. Among the others, wind based generation is the most promising renewable based technology. The volatility of these sources requires the careful planning of power systems. This paper proposed a novel genetic algorithm based method to determine the optimal trade-off between wind energy spilled and transmission line investment by deciding the location of new transmission lines. By this way, power system planners can avoid overinvestment of transmission lines while providing maximum usage of wind turbines. The proposed method is illustrated using the IEEE 24 bus reliability test system.
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    Transmission Expansion Planning Considering Maximizing Penetration Level of Renewable Sources
    (Ieee, 2013) Ugranli, Faruk; Karatepe, Engin
    Recently, integration of intermittent sources into the power systems has gained most interest in distributed generation environment. Among the others, wind based generation is the most promising renewable based technology. The volatility of these sources requires the careful planning of power systems. This paper proposed a novel genetic algorithm based method to determine the optimal trade-off between wind energy spilled and transmission line investment by deciding the location of new transmission lines. By this way, power system planners can avoid overinvestment of transmission lines while providing maximum usage of wind turbines. The proposed method is illustrated using the IEEE 24 bus reliability test system.
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    Transmission Expansion Planning for Wind Turbine Integrated Power Systems Considering Contingencies
    (Ieee, 2014) Ugranli, Faruk; Karatepe, Engin
    Increasing penetration level of wind turbines in power systems reveal new challenges for the power system planners. Transmission expansion planning is one of the most important planning problems to maintain secure and reliable operation of power systems. In this study, a new transmission expansion planning methodology considering N-1 contingency conditions is proposed to find the location of new transmission lines while minimizing investment cost and curtailed wind energy. To deal with the uncertainty of load and output power of wind turbines, fuzzy clustering based probabilistic method is used for determination of load and wind scenarios. Proposed methodology uses the DC-power flow equations based optimal power flow and integer genetic algorithm to determine the locations of new assets and it is applied to the modified IEEE 24-bus test system.
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    Transmission Expansion Planning for Wind Turbine Integrated Power Systems Considering Contingency
    (Ieee-Inst Electrical Electronics Engineers Inc, 2016) Ugranli, Faruk; Karatepe, Engin
    Integration of wind turbines introduces new challenges in terms of planning criteria. In this study, a new transmission expansion planning methodology considering N-1 contingency conditions is proposed to minimize investment cost and curtailed wind energy over planning period. To deal with the uncertainty of load and output power of wind turbines, probabilistic method based on clustering is used for determination of load and wind model. To incorporate the wind power curtailment into the proposed methodology, optimal power flow which uses DC-power flow equations is utilized by including cost functions of generators and overall optimization is carried out by using an integer genetic algorithm. Finally, the proposed methodology is applied to the modified IEEE RTS 24-bus test system by considering different case studies in order to show the effects of including cost functions.
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    Voltage band based global MPPT controller for photovoltaic systems
    (Pergamon-Elsevier Science Ltd, 2013) Gokmen, Nuri; Karatepe, Engin; Ugranli, Faruk; Silvestre, Santiago
    This paper presents a new maximum power point tracking algorithm for PV systems useful in case of non-uniform irradiance conditions. This algorithm takes into account the number of bypass diodes in a PV string to calculate the voltage bands associated with the peak power points that appear in the power voltage characteristic of the PV system. The main contribution of this study is to state that the global maximum power point can be tracked by considering only the possible voltage bands which can be found by using the proposed analytical equation in a simple manner. The algorithm is based in the evaluation and analysis of these voltage bands and in the selection of the PV system voltage related to the maximum power point of work. The proposed algorithm has been validated by means of simulation and also in an experimental study. (C) 2013 Elsevier Ltd. All rights reserved.