Increasing PV hosting capacity in distorted distribution systems using passive harmonic filtering

Sakar, Selçuk; Balcı, Murat Erhan; Aleem, Shady H. E. Abdel; Zobaa, Ahmed F.

doi:10.1016/j.epsr.2017.03.020

Cited by 98 publications

(67 citation statements)

References 27 publications

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“…The basic approach used in the literature is the source impedance or the transfer impedance matrix [66][67][68][69][70]; for harmonic frequencies instead of for the negative-sequence voltage as in the case of unbalance [39] or the equivalent impedances for single-phase loads as in the case of overvoltage due to single-phase PV. Once the injected harmonic currents and the impedance values are known, the harmonic voltage distortion can be calculated as a function of the amount of new production or consumption.…”

Section: Calculation Methodsmentioning

confidence: 99%

Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment

2017

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After a brief historical introduction to the hosting-capacity approach, the hosting capacity is presented in this paper as a tool for distribution-system planning under uncertainty. This tool is illustrated by evaluating the readiness of two low-voltage networks for increasing amounts of customers with PV panels or with EV chargers. Both undervoltage and overvoltage are considered in the studies presented here. Probability distribution functions are calculated for the worst-case overvoltage and undervoltage as a function of the number of customers with PV or EV chargers. These distributions are used to obtain 90th percentile values that act as a performance index. This index is compared with an overvoltage or undervoltage limit to get the hosting capacity. General aspects of the hosting-capacity calculations (performance indices, limits, and calculation methods) are discussed for a number of other phenomena: overcurrent; fast voltage magnitude variations; voltage unbalance; harmonics and supraharmonics. The need for gathering data and further development of models for existing demand is emphasised in the discussion and conclusions.An international working group [22] recently presented a number of recommendations, key findings and open issues to be addressed because of the integration of solar power. Recommendations were given for a number of power-quality phenomena, including harmonics, supraharmonics, fast voltage variations (faster than 10-min time scale), slow voltage variations (slower than 10 min), overvoltage, flicker, and voltage unbalance. The hosting capacity approach, as was proposed by an international cooperation project in 2004 (see Section 2) is put forward in the report as an important tool for quantifying the impact of solar power on the power system. Additional work is needed, according to the report, for establishing suitable performance indices and corresponding limits.This paper consists of three main parts. It starts in Section 2 with an overview, partly from a historical insider perspective, of the hosting-capacity approach. This part also includes a discussion on different kinds of uncertainly. A hosting-capacity-based planning approach is presented in Section 3, applied in Section 4.1 through Section 4.6 and discussed in Section 4.7. The description and the application are for overvoltage and undervoltage as these are the phenomena, with the possible exception of overcurrent, for which the best calculation tools, performance indices and limits are available. The third part of the paper contains a detailed discussion about including other phenomena in hosting-capacity studies. For each phenomenon, performance indices, limits and calculation methods are discussed. Hosting CapacityThe term "hosting capacity" was coined in the context of distributed generation by André Even in March 2004 during discussions within the integrated European EU-DEEP project [23,24]. An approach for quantifying the hosting capacity was developed further by others within that same project [25]. The term "hosting capa...

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Section: Calculation Methodsmentioning

confidence: 99%

Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment

2017

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“…Regulation in many countries promotes new smart grid technologies that enable higher PV penetration in the network, so assessment of the most appropriate technology for a particular network has become crucial. Calculating network hosting capacity is important for the comparison of benefits introduced by different smart grid technologies [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data

et al. 2019

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There has been an increasing trend of integrating photovoltaic power plants (PVs). One of the important challenges for distribution system operators is to evaluate the total installed power of a PV that a particular network can host (or PV hosting capacity) while keeping voltage and element constraints within required limits. The major drawback of the existing methods for calculating PV hosting capacity is that they use the same installed power of the PV systems for all simulated PVs, as these methods do not use external data sources about building roofs. As a consequence, this has a significant impact on the final accuracy of the results. This paper presents a probabilistic methodology for calculating the PV hosting capacity in low voltage (LV) networks. The main contribution of this paper is the improved modeling of PV generation using actual building roof data when calculating the PV hosting capacity, as every building is treated according to its actual solar potential. Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. The simulation results presented in this paper prove that the proposed methodology increases the accuracy of the final PV hosting capacity calculations.Energies 2019, 12, 4086 2 of 15 capacity, various scenarios must be calculated for different PV locations and penetrations. This can provide a statistical description of the possible levels of PV penetration while voltages and element loadings are still within the required range.Many papers have dealt with this kind of problem. The obtained results are usually presented as a network violation probability, depending on the number of consumers with installed PVs or total nominal power of PVs in the network. The paper [7] described low voltage (LV) network planning based on the Monte Carlo approach, taking into account different random distributed generation (DG) locations. The probabilities of voltage levels and the maximum PV penetration limits were assessed. The study in Reference [8] proposed a similar approach, where the PV hosting capacity was evaluated considering the probability of voltage limit violation occurrences at the customer level, according to different PV power factors. The approach developed by the Electric Power Research Institute (EPRI) [9] also proposed a stochastic approach when creating PV deployment scenarios. The stochastic nature of the analysis takes into account the uncertainty in the size and location of the future PV systems [9]. In Reference [10], the work proposed a Monte Carlo-based technique to assess the impacts of different PV penetrations on LV networks, in order to estimate their corresponding hosting capabilities. Similarly, the authors in Reference [11] proposed a probabilistic methodology for evaluating the impacts of PVs, electric heat pumps, micro combined heat and power units, and electrical vehicles on network operation states. The authors in Reference [12] studied how to improve PV hosting capacity...

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“…The PHC results obtained are compared with the conventional deterministic HC (DHC) results, and it is found that the PHC levels are higher than those obtained by conservative HC procedures, practical rules of thumb, and the DHC approaches.Energies 2019, 12, 1018 2 of 23 penetration of DG may turn its advantages into disadvantages with possible operational hazards such as increased overvoltage risks, overloading of electrical equipment, and reversal power flows, with negative impacts on the network's protection schemes, and power quality (PQ) problems.Electrical systems are highly vulnerable to these risks when DG penetration exceeds the maximum allowable level that ensures safe and reliable operation, the so-called system hosting capacity (HC) limit. Simply, HC analysis is of paramount importance to modern network planners and operators, in order to gain clear insight into fast-changing electrical networks that are subject to the high penetration of DGs of intermittent and unpredictable natures [7,8]. In this context, electric utilities and DG investors have paid much attention to HC enhancements, to allow greater DG integration, while ensuring safe and reliable network operation.…”

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confidence: 99%

“…Electrical systems are highly vulnerable to these risks when DG penetration exceeds the maximum allowable level that ensures safe and reliable operation, the so-called system hosting capacity (HC) limit. Simply, HC analysis is of paramount importance to modern network planners and operators, in order to gain clear insight into fast-changing electrical networks that are subject to the high penetration of DGs of intermittent and unpredictable natures [7,8]. In this context, electric utilities and DG investors have paid much attention to HC enhancements, to allow greater DG integration, while ensuring safe and reliable network operation.…”

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confidence: 99%

Probabilistic Hosting Capacity Enhancement in Non-Sinusoidal Power Distribution Systems Using a Hybrid PSOGSA Optimization Algorithm

et al. 2019

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The high penetration of distributed generation (DG) units with their power-electronic interfaces may lead to various power quality problems, such as excessive harmonic distortions and increased non-sinusoidal power losses. In this paper, the probabilistic hosting capacity (PHC) due to the high penetration of photovoltaic units in a non-sinusoidal power distribution system is investigated. A C-type harmonic filter is proposed, to maximize the harmonic-constrained PHC. An optimization problem is formulated by using a Monte Carlo simulation, taking into account various uncertain parameters, such as the intermittent output power of the DGs, background voltage harmonics, load alteration, and the filter parameters’ variations. In addition, different operational constraints have been considered, such as the bus voltage, line thermal capacity, power factor, and individual and total harmonic distortion limits. A swarm-based, meta-heuristic optimization algorithm known as the hybrid particle swarm optimization and gravitational search algorithm (PSOGSA) has been examined for the optimal design of the proposed filter. Besides, other optimization algorithms were examined for validation of the solution. The PHC results obtained are compared with the conventional deterministic HC (DHC) results, and it is found that the PHC levels are higher than those obtained by conservative HC procedures, practical rules of thumb, and the DHC approaches.

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Increasing PV hosting capacity in distorted distribution systems using passive harmonic filtering

Cited by 98 publications

References 27 publications

Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment

Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment

Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data

Probabilistic Hosting Capacity Enhancement in Non-Sinusoidal Power Distribution Systems Using a Hybrid PSOGSA Optimization Algorithm

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