Reliability is an essential factor in distribution networkt expansion planning. However, standard distribution reliability assessment techniques rely on quantifying the impact of a pre-specified set ...of events on service continuity through the simulation of component outages, one at a time. Due to such a simulation-based nature, the incorporation of reliability into distribution network expansion planning has customarily required the application of heuristic and metaheuristic approaches. Recently, alternative mixed-integer linear programming (MILP) models have been proposed for distribution network expansion planning considering reliability. Nonetheless, such models suffer from either low computational efficiency or over-simplification. To overcome these shortcomings, this paper proposes an enhanced MILP model for multistage reliability-constrained distribution network expansion planning. Leveraging an efficient, yet accurate reliability evaluation model, proposing a customized technique for effectively imposing radial operation, as well as utilizing pragmatic measures to model reliability-related costs are the salient features of this work. In this respect, practical reliability-related costs are considered based on reliability incentive schemes and the revenue lost due to undelivered energy during customer outages. The proposed planning approach is tested on four networks with 24, 54, 86, and 138 nodes to illustrate its efficiency and applicability.
As the penetration of variable renewable generation increases in power systems, issues, such as grid stiffness, larger frequency deviations, and grid stability, are becoming more relevant, ...particularly in view of 100% renewable energy networks, which is the future of smart grids. In this context, energy storage systems (ESSs) are proving to be indispensable for facilitating the integration of renewable energy sources (RESs), are being widely deployed in both microgrids and bulk power systems, and thus will be the hallmark of the clean electrical grids of the future. Hence, this article reviews several energy storage technologies that are rapidly evolving to address the RES integration challenge, particularly compressed air energy storage (CAES), flywheels, batteries, and thermal ESSs, and their modeling and applications in power grids. An overview of these ESSs is provided, focusing on new models and applications in microgrids and distribution and transmission grids for grid operation, markets, stability, and control.
This paper presents a comprehensive approach to improve the daily performance of an active distribution network (ADN), which includes renewable resources and responsive loads (RLs), using ...distribution network reconfiguration (DNR). The optimization objectives considered in this work can be described as (i) reducing active losses, (ii) improving the voltage profile, (iii) improving the network reliability, and (iv) minimizing the operation costs. The proposed approach also accounts for the probability of renewable resource failure given the information collected from their initial state at the beginning of each day. Furthermore, solar radiation variations are estimated based on past historical data, and the impact of the performance of renewable resources such as photovoltaics (PVs) is determined hourly based on a Markov model. Since the number of reconfiguration scenarios is very large, stochastic DNR (SDNR) based on the probability distance method is employed to shrink the scenarios set, before a self-adaptive modified crow search algorithm (SAMCSA) is introduced to find an optimal scenario. Finally, the IEEE 33-bus radial distribution system and the 86-bus Taiwan Power Company (TPC) system are investigated as two case studies to verify the effectiveness of the proposed method.
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.
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.
In this article, a novel distributed coordinated control framework is proposed to handle the uncertain voltage violations in active distribution networks. It addresses the problem of coordination of ...different types of devices in a distributed manner. In our control design, on-load tap changers (OLTCs) are firstly employed to handle the potential voltage violations based on the prediction of renewable outputs and load variations. During real-time operation, once an unmanageable voltage violation is detected, the reactive power of distributed energy resources (DERs) will be coordinated immediately to provide fast corrective control. The control schedules of OLTCs are calculated by solving a multitime-step constrained optimization problem via the alternating direction method of multipliers, whereas the reactive power injections of DERs are determined by a novel online distributed algorithm. The effectiveness of the proposed control framework is verified on the modified IEEE 34-bus and 123-bus test feeders.
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.
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.
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.
This paper proposes a real-time coordinated scheduling method for active distribution networks (ADNs) with soft open points (SOPs) and plug-in electric vehicles (PEVs) via multi-timescale framework ...under uncertainties. Specifically, this method is achieved with day-ahead pre-scheduling and intra-day corrective control stages by coordinating various flexible resources at different timescales. The day-ahead stage is designed to reduce operational cost, regulate voltage profile and avoid risk exposure through joint scheduling of traditional devices, SOPs and PEVs on hourly basis. In intra-day corrective control stage, an hour is further divided into two timescales. The slow-timescale scheduling (STS) aims to corrective coordination of SOPs and across-time-and-space energy transmission of PEVs, and nested within the STS, the fast-timescale scheduling optimally coordinates the active & reactive power of SOPs and PV inverters to handle fast voltage fluctuations as well as against real-time uncertainties. The formulated three models are all transformed into second-order cone programming problems via sample weighted average approximation (SWAA), linearization and conic relaxation, which can be thus efficiently solved. Case studies based on three modified distribution systems (including two IEEE test systems and one actual distribution network) are performed to verify the effectiveness of the proposed method.
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