2,984 research outputs found

    Optimization and Integration of Electric Vehicle Charging System in Coupled Transportation and Distribution Networks

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    With the development of the EV market, the demand for charging facilities is growing rapidly. The rapid increase in Electric Vehicle and different market factors bring challenges to the prediction of the penetration rate of EV number. The estimates of the uptake rate of EVs for light passenger use vary widely with some scenarios gradual and others aggressive. And there have been many effects on EV penetration rate from incentives, tax breaks, and market price. Given this background, this research is devoted to addressing a stochastic joint planning framework for both EV charging system and distribution network where the EV behaviours in both transportation network and electrical system are considered. And the planning issue is formulated as a multi-objective model with both the capital investment cost and service convenience optimized. The optimal planning of EV charging system in the urban area is the target geographical planning area in this work where the service radius and driving distance is relatively limited. The mathematical modelling of EV driving and charging behaviour in the urban area is developed

    Optimal distributed generation planning in active distribution networks considering integration of energy storage

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    A two-stage optimization method is proposed for optimal distributed generation (DG) planning considering the integration of energy storage in this paper. The first stage determines the installation locations and the initial capacity of DGs using the well-known loss sensitivity factor (LSF) approach, and the second stage identifies the optimal installation capacities of DGs to maximize the investment benefits and system voltage stability and to minimize line losses. In the second stage, the multi-objective ant lion optimizer (MOALO) is first applied to obtain the Pareto-optimal solutions, and then the 'best' compromise solution is identified by calculating the priority memberships of each solution via grey relation projection (GRP) method, while finally, in order to address the uncertain outputs of DGs, energy storage devices are installed whose maximum outputs are determined with the use of chance-constrained programming. The test results on the PG&E 69-bus distribution system demonstrate that the proposed method is superior to other current state-of-the-art approaches, and that the integration of energy storage makes the DGs operate at their pre-designed rated capacities with the probability of at least 60% which is novel.Comment: Accepted by Applied Energ

    A review on economic and technical operation of active distribution systems

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    © 2019 Elsevier Ltd Along with the advent of restructuring in power systems, considerable integration of renewable energy resources has motivated the transition of traditional distribution networks (DNs) toward new active ones. In the meanwhile, rapid technology advances have provided great potentials for future bulk utilization of generation units as well as the energy storage (ES) systems in the distribution section. This paper aims to present a comprehensive review of recent advancements in the operation of active distribution systems (ADSs) from the viewpoint of operational time-hierarchy. To be more specific, this time-hierarchy consists of two stages, and at the first stage of this time-hierarchy, four major economic factors, by which the operation of traditional passive DNs is evolved to new active DNs, are described. Then the second stage of the time-hierarchy refers to technical management and power quality correction of ADSs in terms of static, dynamic and transient periods. In the end, some required modeling and control developments for the optimal operation of ADSs are discussed. As opposed to previous review papers, potential applications of devices in the ADS are investigated considering their operational time-intervals. Since some of the compensating devices, storage units and generating sources may have different applications regarding the time scale of their utilization, this paper considers real scenario system operations in which components of the network are firstly scheduled for the specified period ahead; then their deviations of operating status from reference points are modified during three time-intervals covering static, dynamic and transient periods

    Progresses in analytical design of distribution grids and energy storage

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    none4noIn the last years, a change in the power generation paradigm has been promoted by the increasing use of renewable energy sources combined with the need to reduce CO2 emissions. Small and distributed power generators are preferred to the classical centralized and sizeable ones. Accordingly, this fact led to a new way to think and design distributions grids. One of the challenges is to handle bidirectional power flow at the distribution substations transformer from and to the national transportation grid. The aim of this paper is to review and analyze the different mathematical methods to design the architecture of a distribution grid and the state of the art of the technologies used to produce and eventually store or convert, in different energy carriers, electricity produced by renewable energy sources, coping with the aleatory of these sources.openColangelo G.; Spirto G.; Milanese M.; de Risi A.Colangelo, G.; Spirto, G.; Milanese, M.; de Risi, A

    Reducing Voltage Volatility with Step Voltage Regulators: A Life-Cycle Cost Analysis of Korean Solar Photovoltaic Distributed Generation

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    To meet the United Nation’s sustainable development energy goal, the Korean Ministry of Commerce announced they would increase renewable energy generation to 5.3% by 2029. These energy sources are often produced in small-scale power plants located close to the end users, known as distributed generation (DG). The use of DG is an excellent way to reduce greenhouse gases but has also been found to reduce power quality and safety reliability through an increase in voltage volatility. This paper performs a life-cycle cost analysis on the use of step voltage regulators (SVR) to reduce said volatility, simulating the impact they have on existing Korean solar photovoltaic (PV) DG. From the data collected on a Korean Electrical Power Corporation 30 km/8.2 megawatts (MW) feeder system, SVRs were found to increase earnings by one million USD. SVR volatile voltage mitigation increased expected earnings by increasing the estimated allowable PV power generation by 2.7 MW. While this study is based on Korean PV power generation, its findings are applicable to any DG sources worldwide.11Nsciescopu

    Stochastic Modeling and Planning of Wind-Based Distributed Generators in Distribution System

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    The increasing strain on the Earth resulting from pollution, climate change, and finite resources has established the development of renewable energy sourcing methods, such as wind, solar and geothermal energy. By reorganizing the power system structures, and the growth in customer demand, the development of Distributed Generation (DG) play a vital role in the power system planning. Furthermore, because of the inexhaustibility and cleanliness of the renewable DG units, they are inevitably the key to a sustainable energy supply infrastructure. Nevertheless, the random nature associated with the renewable DG units produces specific challenges that have to be addressed to accelerate the expansion of the renewable DG units in the distribution system. Firstly, a new method for the determination of the wind speed distribution based on hourly wind speed data is proposed. Thus, instead of using only the well-known unimodal distributions such as Weibull and Rayleigh, a combination of probability density functions (PDFs) is taken into account, considering four sets of parameters in which each set represents a distribution. Furthermore, this model enhances the likelihood of the estimated wind speed probabilities. The maximum likelihood estimation (MLE) method for finite mixture models through the expectation-maximization (EM) algorithm is used to estimate the optimal parameters of the mixture distribution. Then two types of error measurements assessed the performance of each unimodal and multimodal distribution. As a result, the mixture of Gamma (MoG) distribution returned the most accurate results. Secondly, the results of wind speed modeling will be used in the siting and sizing wind-based DG units. The methodology addresses a probabilistic generation load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities. The objective of siting and sizing formulation is to minimize the annual energy losses of the system as well as keeping the system constraints such as voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units in an acceptable limit

    Planning of PEVs Parking Lots in Conjunction With Renewable Energy Resources and Battery Energy Storage Systems

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    The last few decades have seen growing concerns about climate change caused by global warming, which is cause primarily by CO2 emissions. Thus, the reduction of these emissions has become critically important. One of the effective methods for achieving this goal is to shift towards green electricity energy resources and green vehicles in transportation. For these reasons, the goal of the work presented in this thesis was to address the challenges associated with the planning of plug-in electric vehicles (PEVs) parking lots in combination with renewable energy sources (RES) and battery energy storage systems (BESS) in power distribution networks. This thesis introduces a new planning technique that aims to minimize the overall capital and operational costs, taking into consideration the operational aspects of distribution networks, such as 1) coordinated PEV charging, 2) smart inverter control of renewable distributed generation (DG) units, and 3) smart scheduling of BESS. Moreover, a new model for the PEV coordinated charging demand is introduced in this work. Due to the complexity of the proposed planning approach, a combination between metaheuristic technique and deterministic optimization techniques have been utilized to manage both the planning and operational aspects respectively

    Multi-objective optimal battery placement in distribution networks

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    Due to high penetration of renewable energy resources in today\u27s electricity generation, considerable voltage fluctuations are witnessed in power systems. As an attempt to solve this issue, in this study, multi-objective optimal placement and sizing of distribution-level battery storage system is performed using semidefinite programing. Placement of one or multiple battery system is studied under various objectives including the cost, voltage regulation, reactive power dispatch, renewable resource curtailment, and minimum network power losses. Power flow equations are solved in the form of semidefinite constraints and the rank constraint is ignored. Additionally, combination of these objectives to form a multi-objective problem and regularization of the number of battery sites are studied. Finally, simulation results are provided to analyze the proposed formulation --Abstract, page iii

    Modified Taguchi-Based Approach for Optimal Distributed Generation Mix in Distribution Networks

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    In this paper, a new two-stage optimization framework is proposed to determine the optimal-mix integration of dispatchable Distributed Generation (DG), in power distribution networks, in order to maximize various techno-economic and social benefits simultaneously. The proposed framework incorporates some of the newly introduced regulatory policies to facilitate low carbon networks. A modified Taguchi Method (TM), in combination with a node priority list, is proposed to solve the problem in a minimum number of experiments. Nevertheless, the standard TM is computationally fast but has some inherent tendencies of local trapping and usually converges to suboptimal solutions. Therefore, two modifications are suggested. A roulette wheel selection criterion is applied on priority list to select the most promising DG nodes and then modified TM determines the optimal DG sizes at these nodes. The proposed approach is implemented on two standard test distribution systems of 33 and 118 buses. To validate the suggested improvements, various algorithm performance parameters such as convergence characteristic, best and worst fitness values, and standard deviation are compared with existing variants of TM, and improved genetic algorithm. The comparison shows that the suggested corrections significantly improve the robustness and global searching ability of TM, even compared to meta-heuristic methods
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