Distribution systems commonly operate with a radial topology, so all models of optimization problems in these distribution systems should consider radiality in their formulation. This work presents a ...literature review, a critical analysis, and a proposal for incorporating the radiality constraints in mathematical models of optimization problems for radial distribution systems. The objective is to show that the radiality constraints on such optimization problems can be considered in a simple and efficient way. The reconfiguration and expansion planning problems of distribution systems are used to test and verify the proposed radiality constraints. A generalization of radiality constraints is also examined.
This study presents a loss formula-based simultaneous reconfiguration and distributed generation (DG) sizing algorithm for active power loss minimisation in distribution networks. A new heuristic ...technique based on the exact loss formula for reconfiguration is proposed. The exact loss formula-based analytical approach is used for DG sizing and siting. The proposed algorithm is tested on 33-, 69-, 84- and 136-bus distribution systems. The simulation results demonstrate the effectiveness of the proposed approach to obtain the best solution. The impact of the initial voltage selection on this approach is analysed. The results are suggesting that it requires no load flow solution and it is the unique feature of this approach. The proposed approach can be used as a primary analysis tool for active distribution network real-time operation and planning. The proposed method further extended to the multi-objective approach using the weighted sum technique.
The problem of state estimation for unobservable distribution systems is considered. A deep learning approach to Bayesian state estimation is proposed for real-time applications. The proposed ...technique consists of distribution learning of stochastic power injection, a Monte Carlo technique for the training of a deep neural network for state estimation, and a Bayesian bad-data detection and filtering algorithm. Structural characteristics of the deep neural networks are investigated. Simulations illustrate the accuracy of Bayesian state estimation for unobservable systems and demonstrate the benefit of employing a deep neural network. Numerical results show the robustness of Bayesian state estimation against modeling and estimation errors and the presence of bad and missing data. Comparing with pseudo-measurement techniques, direct Bayesian state estimation via deep learning neural network outperforms existing benchmarks.
To deal with the heavy operational expenditures of the fifth-generation (5G) telecom service providers (TSPs), powering 5G base stations (BSs) with renewable energy (RE) and stimulating a good ...interaction between the RE-BS and the smart grid is recognized as an effective and practical solution. However, the existing researches on the interaction between RE-BSs and the smart grid mainly study from the perspective of the TSPs, ignoring the operational constraints of the grid. On the other hand, with the rapid development of integrated energy systems, the integrated operation of the power and water distribution system attracts growing attention. And recently, water-cooling has been introduced as a promising energy-saving technique for 5G-BSs, but few efforts have been spent investigating the interaction between the BSs, the power, and the water distribution system. This paper considers the water-cooled 5G-RE-BSs enabled by an integrated electricity-water distribution system (IEWDS), which is managed by the integrated electricity-water service provider (IEWSP). Coordination mechanisms between the TSP and the IEWSP are investigated, and the optimal model with two coordinated operation modes of the IEWDS, incorporating operation constraints of both the IEWDS and the 5G-BS, is proposed. Case studies on two IEWDS sample systems validated the benefits of coordination and the effectiveness of the proposed coordination methods.
•A water-cooled 5G-BS is modeled as a micro integrated electricity-water system.•The energy & water interaction between 5G-BSs and IEWDSs is studied.•Two coordinated mechanisms between 5G-BSs and IEWDS are proposed.•Two coordinated operation models with detailed operation constraints are proposed.
In order to help flexible multi-state switch (FMSS) access the power system, a reliability evaluation method for multi-terminal interconnected power distribution systems with FMSS is proposed. First, ...according to the physical structure and operation mode of FMSS, a reliability model of FMSS is established. Then, by exploring how FMSS access strategy changes the system operation mode as well as network structure, a load recovery method for disconnected side is designed and the factors affecting the system reliability are refined. Finally, the sequential Monte Carlo is applied to evaluate the reliability of the multi-terminal interconnected distribution system with FMSS, and the influence of FMSS access strategy on the system reliability is quantitatively analysed in two different systems. The cases verify the effectiveness of the method, and the results show that: (i) the access of FMSS and the proposed load recovery strategy can significantly enhance the system reliability, (ii) the access position, capacity and reliability of FMSS affect system reliability, (iii) the improvement of system reliability is optimal when the FMSS with a large capacity connected to the end of the system, and close to important loads. This research can provide theoretical support for the planning of flexible interconnected power distribution system.
•The utilization of P2G plants in electricity and gas distribution networks has been analyzed.•Medium pressure gas network can be used as an intraday storage means for SNG.•A low gas demand implies ...coordinated P2G operation to optimize the whole multi energy system.•Only in the best-case scenario is the SNG cost comparable with the cost of natural gas.
Distributed generation, based on the exploitation of Renewable Energy Sources (RES), has increased in the last few decades to limit anthropogenic carbon dioxide emissions, and this trend will increase in the future. However, RES generation is not dispatchable, and an increasing share of RES may lead to inefficiencies and even problems for the electricity network. Flexible resources are needed to handle RES generation in order to support the delicate electricity generation and demand balance. Energy conversion technologies (P2X, Power to X) allow the flexibility of energy systems to be increased. These technologies make a connection between different energy sectors (e.g., electricity and gas) possible, and thus create new synergies within an overall multi-energy system. This paper analyzes how the P2G technology can be used at the distribution network level (both gas and electricity) to optimize the use of RES. In fact, in order to coordinate P2X resources, it is necessary to take into account the whole multi-energy scenario, and not just the electrical side: it therefore becomes fundamental to recognize the pros and cons that Balancing Service Providers (BSPs), composed of a number of P2G plants (representing the Balancing Responsible Providers, BRPs), may have when offering services to an electricity network. Moreover, the convenience of the decarbonization of the gas grid has been evaluated through the calculation of the levelized cost of Synthetic Natural Gas (LCSNG) for cost scenarios for the years 2030 and 2050, considering different assumptions about the cost of the surplus utilization of RES. The results show that LCSNG may vary from 47 to 319 €/MWh, according to the different configurations, i.e., only in the best-case scenario is the SNG cost comparable with the cost of natural gas, and hence does the P2G technology result to be profitable.
This paper presents a method for quantifying and enabling the resiliency of a power distribution system using analytical hierarchical process and percolation theory. Using this metric, quantitative ...analysis can be done to analyze the impact of possible control decisions to pro-actively enable the resilient operation of distribution system with multiple microgrids and other resources. Developed resiliency metric can also be used in short term distribution system planning. The benefits of being able to quantify resiliency can help distribution system planning engineers and operators to justify control actions, compare different reconfiguration algorithms, and develop proactive control actions to avert power system outage due to impending catastrophic weather situations or other adverse events. Validation of the proposed method is done using modified CERTS microgrids and a modified industrial distribution system. Simulation results show topological and composite metric considering power system characteristics to quantify the resiliency of a distribution system with the proposed methodology, and improvements in resiliency using two-stage reconfiguration algorithm and multiple microgrids.
•A new two-level, planning framework for optimal integration of DERs.•The provision of energy as well as ancillary services models are introduced.•Various real-life objectives considering system ...security and stability are proposed.•The advantages and applicability demonstrated and supported by case studies.
The increased penetration of renewable energy sources has prompted the integration of battery energy storage systems in active distribution networks. The energy storage systems not only participate in the backup power supply but also have the potential to provide various distributed ancillary services. In this paper, a new bi-level optimization framework is developed to optimally allocate the intense wind power generation units and battery energy storage systems with the provision of central and distributed ancillary services in distribution systems. Two battery energy storage systems and one shunt capacitor are strategically allocated for coordination of wind power generation. One of the battery is deployed at grid substation to participate in central ancillary services whereas second is participating in distributed ancillary services. At level-1, all the distributed energy resources are optimally allocated while minimizing the annual energy loss of distribution systems. Whereas, level-2 performs hourly optimal energy and ancillary services management of distributed resources deployed at level-1. The objectives considered at level-2 are the minimization of hourly load deviation, reverse power flow towards the grid, power loss, and node voltage deviation. The proposed framework is implemented on a real-life Indian 108-bus distribution system for different cases and solved by using a genetic algorithm. The comparison of simulation results reveal the promising advantages of the proposed optimization framework. It provides more energy loss and demands deviation reduction, improved system voltage and power factor at higher wind penetration as compared to the cases in which distributed ancillary services are ignored in the planning stage.
An essential component of smart grid applications is the ability to solve the power flow (PF) problem in real-time. As numerical methods are too slow, the use of neural networks (NNs) is rapidly ...increasing. Graph Neural Networks (GNNs) and their variants have become one of the leading methods to learn graph representations. Power systems and in particular, distribution systems can be represented as graphs, and are characterized by often topology changes, which makes the consideration of the topology structure to be an important aspect when searching for a solution approach. Although GNNs have promising results for certain applications such as computer vision ones, considering its limitations, it still has a long way to go until becoming a leading candidate for PF based applications. This paper highlights the existing gaps and challenges in fully accepting ANNs and particularly GNNs as real-time solution engines for the PF problem in DSs. These gaps are analyzed under three categories: suitable architectures for the solution of the PF problem in DS, explicit vs. implicit incorporation of the DS topology information impact on the models’ generalization, and the limiting factors for GNNs implementation aimed at the solution of the PF problem in DSs. The paper also includes a discussion, suggestions and insights of overcoming these gaps in future research.
•State-of-the-art ANN based solutions for the power flow problem are reviewed.•Discussing barriers of adopting GNNs as a valid method for DSs PF based applications.•Incorporation of the DS topology information impact on the models’ generalization.•Insights and suggestions of overcoming these gaps in future research are presented.
High-impedance faults (HIFs) in electrical power distribution systems produce a very random, non-linear and low-magnitude fault current. The conventional overcurrent (OC) relaying-based distribution ...system protection schemes find difficulty in detecting such low-current HIFs. In this study, a simple two criteria-based protection scheme is proposed for detection and isolation of HIFs in multi-feeder radial distribution systems. It utilises one-cycle sum of superimposed components of residual voltage for HIF detection and the maximum value of one-cycle sum of superimposed components of negative-sequence current for faulted feeder identification. The performance of the proposed scheme is evaluated for a wide variety of possible test cases by generating data through power systems computer-aided design/electro-magnetic transient design and control software. Results clearly show that the proposed scheme can assist conventional OC relay for detection and isolation of HIFs in distribution systems with any grounding connections in a more reliable and faster way.
PDF
