The deployment of prosumers with distributed energy resources (DERs) has facilitated the prosumer-centric transactive market, giving rise to the consequent necessity for the coordination between ...prosumers and the distribution networks. This paper proposes an incentive-based expansion planning method considering virtual peer-to-peer (P2P) transaction among prosumers, which is characterized as a tri-level planning-operation-transaction framework. Each prosumer optimizes its internal response of DERs and external P2P transaction jointly, formulating virtual P2P transaction. Under such a paradigm, the distribution company (DISCO) identifies the optimal expansion planning in the network assets, while the independent distribution system operator (IDSO) is responsible for the optimal operation of the expanded distribution networks. To derive appropriate incentives for each prosumer, the DISCO and IDSO allocate long-term investment network charges and short-term operation network charges on prosumers, along with the designed financial transmission rights coupling multiple time scales. Through such incentives, self-profit driven virtual transactions can relieve operation problems and postpone expansion planning, acting as a short-term alternative. Moreover, a risk-based approach is proposed for prosumer to flexibly change strategy according to different risk preference. Finally, results from the case study demonstrate the superiority and effectiveness of the proposed method in the collaborative application of virtual transaction in the expansion planning.
The active distribution network has witnessed an increasing penetration of distributed generation (DG) while the stochasticity and variability arising from DGs also impose significant challenges on ...system operation. To mightily accommodate the uncertainty of DG, we introduce a distributionally robust chance-constrained dynamic reconfiguration approach for a three-phase unbalanced distribution network. The proposed framework optimizes the switching cost and the expected power supply cost from upstream grid, and stipulates that the chance constraints hold under the worst-case distribution within a novel ambiguity set, which incorporates the Wasserstein distance and the first-order moment. Then we develop tractable and scalable solution methods to tackle the expected objective function and chance constraints. As a result, the proposed model is reduced to a mixed-integer linear programming problem that can readily be implemented. Numerical experiments are carried out on the IEEE 34-bus and 123-bus test systems to demonstrate the effectiveness and efficiency of the suggested approach.
Distribution networks are evolving into active meshed networks with bidirectional power flow as the penetration of distributed generation (DG) sources is increasing. This necessitates the use of ...directional relaying schemes in these emerging active distribution networks. However, conventional directional overcurrent (OC) protection will not be adequate to protect these networks against the stochastic nature of renewable DGs and the changing network architectures. Hence, this study proposes an adaptive directional OC relay algorithm that determines optimal protection settings according to varying fault currents and paths induced by the DGs in active meshed distribution networks. The proposed algorithm consists of a two-phase approach that deduces: (i) optimal floating current settings through a fuzzy decision-making module, and (ii) optimal floating time settings through an optimisation algorithm. Extensive case studies are implemented on the modified power distribution networks of IEEE 14-bus and IEEE 30-bus by varying the type, location, and size of DGs. The results validate the ability of the proposed protection scheme to capture the uncertainties of the DGs and determine optimal protection settings, while ensuring minimal operating time.
The conventional distribution network is undergoing structural changes and becoming an active grid due to the advent of smart grid technologies encompassing distributed energy resources (DERs), ...aggregated demand response and electric vehicles (EVs). This establishes a need for state estimation-based tools and real-time monitoring of the distribution grid to correctly apply active controls. Although such new tools may be vulnerable to cyber-attacks, cyber-security of distribution grid has not received enough attention. As smart distribution grid intensively relies on communication infrastructures, the authors assume in this study that an attacker can compromise the communication and successfully conduct attacks against crucial functions of the distribution management system, making the distribution system prone to instability boundaries for collapses. They formulate the attack detection problem in the distribution grid as a statistical learning problem and demonstrate a comprehensive benchmark of statistical learning methods on various IEEE distribution test systems. The proposed learning algorithms are tested using various attack scenarios which include distinct features of modern distribution grid such as integration of DERs and EVs. Furthermore, the interaction between transmission and distribution systems and its effect on the attack detection problem are investigated. Simulation results show attack detection is more challenging in the distribution grid.
The integration of high proportions of distributed energy resources and the soaring development of 5G base stations (BSs) could lead to operational issues such as grid congestion in distribution ...networks. Meanwhile, 5G BSs can also serve as the flexible resources to support the distribution network. In this regard, this paper proposes a novel method to eliminate distribution network congestion with spatial-temporal migration of multiple base stations (BSs). First, the collaborative structure of the distribution network operator (DNO) and mobile network operator (MNO) is presented and the event-driven congestion management framework of the distribution network with multiple BSs is illustrated. Secondly, the specific spatial-temporal migration models of multiple BSs are established, which contain traffic migration, BS sleeping, and dispatchable capacity of the BS backup energy storage system. Then, the event-driven adaptive congestion management model is proposed, which includes congestion detection, congestion response and elimination model, and the step-wise algorithm of the congestion response is proposed. Finally, the modified IEEE 33-node and IEEE 123-node distribution system are adopted for case studies, from numerical analysis we can draw that, the proposed congestion management method can alleviate the congestion issue of the distribution network effectively while reducing costs of both DNO and MNO.
Soft normally open points (SNOPs) connected to distribution networks are instrumental in maintaining uninterrupted power supply and improving power quality during the fault period. In order to ...achieve the optimal service restoration scheme, a novel bi-level service restoration model based on the robust optimization method is proposed in this paper. The upper level of the proposed model aims at minimizing the risk of load loss. The switch statuses and range of power transmitted by SNOP terminals can be obtained. In the lower level of the model, the interval robust optimization method is adopted to cope with the uncertainties of DGs and loads. If there are no optimal solutions, the upper level model needs to be solved once more to adjust the network topology. Finally, a test system is established to verify the effectiveness of the proposed model and solution method. The effects of forecasting errors, the DG penetration, and the ratio of single terminal capacity of SNOP to line capacity on the optimization results are analyzed.
In the traditional dc distribution networks with both a low-voltage dc (LVdc) and a medium-voltage dc (MVdc) bus, dc units, such as photovoltaics solar, storage devices, and dc loads, are connected ...to the LVdc bus through LVdc converters, such as dc/dc boost converters and bidirectional buck-boost dc/dc converters. In this approach, no galvanic isolation is provided and two power conversion stages are needed between the dc units and the MVdc grid, hence leading to a high number of converters and higher costs. To address these shortcomings, this article proposes a novel multiport dc solid-state transformer (MDCSST) to interface these dc units directly to the MVdc bus. Multiple modules are connected in series on the medium-voltage side to the MVdc bus, whereas dc units are independently connected on the low-voltage side of the MDCSST. Compared with a traditional dc distribution network, the proposed scheme connects dc units to the MVdc bus without an extra converter or an LVdc bus, therefore, saving cost and reducing the number of converters. In addition, dc units are galvanically isolated by high-frequency transformers. The main challenge of the MDCSST is to resolve the voltage-imbalance problem on the MVdc side, which is caused by the dc units' power differences. An LC branch is used to balance the voltages among the modules and to transfer their differential powers. Simulations and experiments were carried out to validate the proposed approach and verify the theoretical analysis.
Planning the distribution network of the future involves forecasting the most likely scenario to make appropriate investment decisions. Many uncertainties concerning, e.g. the evolution of ...conventional loads, renewable production and electric vehicles (EVs) make it difficult to predict the location of the distribution network's weaknesses (overvoltages, undervoltages and overcurrents) and their occurrence. In some cases, alternative solutions such as demand response (DR) and reconfiguration can remove the constraints and prevent expensive network investment. This study proposes a two-stage algorithm that is able to give the probability that no technical constraints will appear as a function of the reinforcement cost with and without using DR and/or reconfiguration. The first stage of the algorithm consists in running Monte Carlo simulations based on realistic scenarios for loads, EVs and renewable production development provided by French governmental roadmaps. The cost of reinforcement per line and per hour of constraints enables selection of the feeders, where DR (solved with linear programming) and/or reconfiguration (exhaustive research) will be implemented in the second stage of the algorithm to remove these constraints. The methodology is applied to a real part of a French distribution network.
Accurate harmonic state estimation (HSE) is necessary to mitigate harmonic issues in power distribution networks. However, existing HSE methods face difficulties in solution of state equation that ...the measured data is insufficient with limited monitors. Therefore, this study proposes a HSE algorithm for distribution networks based on multi-measurement data. Firstly, a harmonic source location method based on mutual information and distribution network partition is proposed to reduce the number of state variables and to solve the state equation. Thus, HSE with low resolution (15 min) is realized. Secondly, a HSE method with enhanced resolution is developed. This method establishes maximum entropy principle models for harmonic currents injected into buses, calculates the probability density function (PDF) of the harmonic current, and realizes optimal interpolation of the harmonic data to enhance the resolution of the HSE (3 min) according to the PDF. Finally, the applicability and effectiveness of the proposed method are verified using an IEEE-33 test system simulation and a real power system in South China.
The increasing penetration of photovoltaic (PV) systems presents significant impacts on distribution network (DN) operations. To this end, an accurate evaluation of PV hosting capacity (PVHC) can ...help utilities to carry out PV capacity planning and configuration more effectively, ensuring the efficiency, economy, and reliability of DNs. First, the definition of interval overvoltage probability (IOP) is introduced and the IOP based PVHC evaluation method is presented. Next, this method is improved considering PV and load uncertainties, where the interval arithmetic (IA) and affine arithmetic (AA) are both applied to deal with uncertainties. In addition, the overvoltage severity is taken into account on the basis of IOP, and the concept of interval overvoltage risk (IOR) is proposed. A practical 55-bus rural feeder in China is used to illustrate the advantages of the proposed method compared with the conventional method, and also to verify the value in decision-making of PV planning for utilities. Moreover, the sensitivity of interval valued PVHC against the number of Monte Carlo simulation (MCS) and width of PV installation capacity interval (PICI) is analyzed. And the impacts of on-load tap changer (OLTC) tap positions and static var compensator (SVC) configurations are also explored. Finally, the proposed method is tested on the NYSEG 292-bus system to validate its adaptability on a larger and unbalanced system.
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