The connection of distributed generation sources to the distribution network has negative effects on the network protection such as; a false trip of non-directional overcurrent relays. In this study, ...an offline method is proposed to overcome the false trip issue. In this method, the false trip is modelled as a new set of coordination constraints in the optimal coordination problem. For establishing false trip constraints, pickup current setting and characteristic type of relays are selected in addition to the time multiplier setting. Considering false trip constraints in the coordination problem increases the operating time of relays. Therefore, the optimisation is applied to obtain the settings of non-directional overcurrent relays in order to reduce their operating times in addition to resolving the false trip. Also, three new approaches are defined for pickup current selection based on pickup current range. A combination of genetic algorithm and linear programming technique is used to access optimised responses. Finally, the proposed method is implemented on a sample radial distribution network and the results demonstrated that the occurrence of the false trip was prevented and also the operating time of the relays was reduced to an acceptable level.
Early cable faults are becoming more prevalent in urban distribution networks. In this paper, the mechanism of grounding line current signal generation and propagation in cables with early faults is ...analyzed to help understand the relationship among each frequency component, the fault location, and fault resistance, based on which we propose a novel distance estimation method for early faults in three-core cables using multiple amplitude ratio fusion within a selected frequency band. By combining the amplitudes of different frequency components, this approach reduces the reliance on accurate extraction of the amplitude of a single-frequency component, which is particularly suitable for detecting sub-cycle early faults. Simulation analysis and field test results demonstrate the proposed method's high accuracy in estimating the fault distance. Moreover, it is less susceptible to variations in fault conditions. These findings show that the proposed method is effective in addressing the challenge of early cable fault distance estimation in distribution networks.
With the increasing penetration of distributed energy resources (DERs) in the active distribution network (ADN), how to enable joint planning of DERs under the uncertainty of distributed generations ...(DGs) has become a challenging problem. This study establishes a two-stage joint planning model considering doubly-fed induction generator, photovoltaics (PVs) with the ancillary services of PV inverter, distributed energy storage systems and different types of controllable loads in the ADN. To address the uncertainties of DGs, a two-stage data-driven distributionally robust planning model is constructed. The proposed model is solved in a ‘master and sub-problem’ framework by column-and-constraint generation algorithm, where the master problem is to minimise the total cost and find the optimal planning decision under the worst probability distributions, and the sub-problem is to find the worst probability distribution of given uncertain scenarios. Besides, the original mixed-integer non-linear planning problem is converted into a mixed-integer second-order cone programming problem through second-order cone relaxation, Big-M and piecewise linearisation method. The numerical results based on 33-bus system verify the effectiveness of the proposed model.
In this study, extensive dynamic simulation studies are carried out to explore the impact of synchronous machine (SM)-based distributed generation (DG) integration on existing radial fuse–recloser ...protection infrastructure. Furthermore, dynamic simulation studies are also conducted to highlight the use of superconducting fault current limiters (SFCLs) to mitigate such an impact. These studies have included the effects of SM-based DG sources on fuse–recloser coordination and recloser sensitivity adequacy. In addition, a comparison between the performances of two different SFCL types has been also offered. The dynamic results of these investigations have shown that the presence of SFCLs has prevented any excessive fault current contribution from SM-based DG sources, as a result, it has restored the fuse–recloser coordination and recloser sensitivity adequacy. Within the frame of reference of the study is the dynamic simulations of a test benchmark that have been conducted using the PSCAD/EMTDC software.
Renewable distributed generation (DG) is likely to be actively controlled in future distribution networks to mitigate voltage issues resulting from high penetrations. This requires understanding the ...corresponding dependencies between voltage magnitudes and DG active/reactive power outputs. One approach to compute these dependencies is to use classical sensitivity methods such as those based on the Jacobian matrix inverse. However, updating the latter involves extensive remote monitoring. This paper presents a novel approach to produce voltage sensitivities applying the surface fitting technique on data based solely on the knowledge of network characteristics; making it suitable for decentralized DG control. To assess the benefits, comparisons with classical methods are carried out using the 16-bus UK GDS test network (1-min resolution simulations) considering a decentralized voltage control algorithm that simultaneously caters for the active and reactive power outputs of a single DG plant. The robustness of the proposed approach is also investigated considering changes in network parameters. Finally, the use of coordinated time delays is proposed to cater for multiple DG plants. Comparisons with a centralized optimization demonstrate that the combined use of the proposed voltage sensitivity approach and decentralized control algorithm is an effective and implementable candidate to actively manage renewable DG plants.
The transition towards Time of Use (ToU) tariffs has become a promising solution for addressing power system challenges resulting from increased installations of renewable energy systems. ToU tariffs ...encourage residential Battery Energy Storage System (BESS) adoption to reduce customers' bills through maximizing energy storage during low-price intervals (e.g., middle of the day). However, simultaneous BESS charging affects diversity of load, which may lead to the violation of distribution networks constraints. Traditional network management with conservative fixed and static power limits leads to inefficient network capacity use since they do not consider changes in network operating conditions and status of BESS facilities. Specially, these approaches do not allow higher import limits when proportion of BESS facilities are in idling state. To better allocate the capacity of distribution networks to active BESS facilities (charging/discharging), this work introduces an independent storage operator to coordinate BESS control actions by employing time-varying and adaptive power limits. For this purpose, a Mixed Integer Linear Programming (MILP) algorithm is proposed for storage operator to manage BESS facilities while respecting network constraints and customers' desired bills. At each time step, the algorithm decides power limits for active BESS facilities based on predefined linear functions. These functions are generated offline by using Optimal Power Flow (OPF) to establish relationships between power limits and number of active BESS. The application of the algorithm using a real Jordanian distribution network demonstrates its effectiveness to allow a larger number of customers achieving their desired bills compared to using fixed power limits.
•Uncoordinated charging of batteries under ToU tariff violates network constraints.•Introducing storage operator for coordinating batteries in distribution networks.•Storage Operator is modelled by Mixed-Integer Linear Programming (MILP).•Managing batteries is based on predefined time-varying and adaptive power limits.•Storage operator optimizes network capacity to maximize customers' satisfactions.
Rapidly increasing distributed energy resources (DERs) bring more fluctuating output power to the distribution network and put forward a higher requirement on local regulation resources for ...maintaining the network's balance. Heating, ventilation, and air conditioning (HVAC) loads account for more than 40% of power consumption in modern cities and have huge regulation potential as flexible loads. However, HVACs equipped with inverter devices have rarely been studied for providing regulation services in the local electricity market (LEM), even though they have exceeded regular fixed-speed HVACs. To address this issue, this article proposes a real-time LEM and a distribution network's optimization framework to exploit the regulation potential of inverter-based HVACs considering multiple DERs. This LEM can avoid iterations in real time and significantly decrease the difficulty related to the participation of small end-users in urban distribution networks. Moreover, in this article, we propose a transactive capacity evaluation method to assist end-users in deciding their inverter-based HVACs regulation capacities in the real-time LEM, which considers buildings' thermal features, users' multiple comfort requirements, and dynamic ambient temperature. On this basis, a multilevel bidding strategy is developed for inverter-based HVACs to decrease energy cost, increase fluctuating DERs local utilization rate, and alleviate the distribution network's congestion. Finally, a realistic distribution network is utilized to verify the effectiveness of the proposed methods.
The flexibility evaluation of distribution networks has attracted significant research attention with the increasing penetration of renewable energy. One particular gap in existing studies is that ...little attention has been paid to the probabilistic characteristics of uncertain regions. In this study, a novel sequential flexibility evaluation method is proposed based on the feasibility analysis of the uncertain region of photovoltaic active power and load demand. The model features the uncertain region with probabilistic characteristics, which is essential for analysing the impact of probabilistic characteristics of uncertain variables (PCUVs) on flexibility evaluation. The sequential direction matrix is adopted to reflect the major factor of flexibility shortage. The evaluation procedure is modelled as a bi-level optimisation problem. Demonstrated by the simulation results, the flexibility index is larger by considering the PCUV. Furthermore, the elements in the sequential direction matrix indicate that the photovoltaic power during midday is the major cause of flexibility shortage.
This study introduces a probabilistic optimisation model for allocation of renewable distributed generations (DGs) in radial distribution networks. The methodology is based on a probabilistic ...generation – load model that combines all possible operating conditions of the wind-based DG units as well as load levels with their probabilities. A multiobjective performance index is extracted that is formulated as a combination of two indices, namely energy losses reduction and voltage improvement. Besides, a probabilistic AC optimal power flow is used to determine the optimal allocation of wind DG and maximise the multiobjective performance index. Two alternative control approaches of the future smart grids, i.e. area based under load tap changer control and adaptive power factor control, are assessed to maximise potential benefits and expand the penetration level of DGs. At first, this problem is formulated as a mixed-integer non-linear programming (MINLP) which leads to a computationally NP-hard problem. Accordingly, the obtained MINLP problem is relaxed and reformulated in the form of a well-suited second-order cone programming problem which is computationally efficient scheme to be solved. The implementation of the proposed framework on 4-bus and IEEE 33-bus radial distribution systems shows the performance of the proposed optimisation mechanism.
-The interesting properties of natural gas as well as the growing electric power demand worldwide have led to increasing attention to natural-gas-based distributed generation applications in electric ...distribution systems. This paper goes over the interdependency between a residential natural gas network and an electric distribution network that are coupled via fuel cells. The modeling of the gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the gas and electric distribution networks, subject to their model constraints. In addition to this, in order to capture the probabilistic nature of the optimization problem under study, the K-means clustering algorithm is applied to the gas and electricity demands to determine hourly load states and their corresponding probabilities. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution feeder and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.
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