Distribution Network Level Research Articles

Optimal fuzzy switch placement to increase automation level of electric distribution network considering asset management principles

Since distribution sector is inherent into high amount of failures, distribution companies (DISCOs) are responsible of attaining an acceptable value for the reliability indices and otherwise they will face up to complaints. So they are usually obligated by regulators to invest on reliability improvement of network. But this investment on reliability is usually from the DISCO’s viewpoint and is also irrespective of customer satisfaction level. In other words, customers are not at the same level of sensitivity to interruptions but DISCO improves the reliability of network without considering the differences in importance degree of loads and their level of reliability requirement. On the other hand DISCOs attempt to reduce their investment costs as much as possible. This paper introduces a novel approach in the field of joint switch placement that can reduce the switch cost from the perspective of asset management policies. To this end, two switch placement plannings in different types of strategies are performed to compare their results. Firstly as witch placement is performed based on reducing the total energy not supplied (ENS) of the system. Then by revising the strategy, a fuzzy switch placement is performed from the DISCO’s point of view which just considers the total ENS of load points most sensitive to interruptions known as important or critical loads. Furthermore, by meeting the related constraints, the reliability of low sensitive customers is disregarded. This is a load importance based planning which can result in switch cost reduction relative to the amount achieved in previous strategy and implies the management of risks associated with reliability and respective constraint. Fuzzy method and new switching mechanism in fuzzy environment of network are implemented to modeling and controlling the risks associated to ENS of critical loads and also the ENS of system.

Electric Vehicle Charging and Batteries Swapping Management Strategy with Photovoltaic Generation in Business Districts

The intermittent characteristics of photovoltaic generation present a challenge in its promotion and application in urban loads on the distribution network level. Integrated construction of photovoltaic generation, battery storage stations, and electric vehicles (EVs) provides a reasonable solution for photovoltaic applications in cities. With the increase in EVs, business districts (BDs) have become popular for EV charging and parking. By considering photovoltaic power and commuter demand, a new BD framework is proposed in this paper; this includes a battery swapping area, a quick charging area, and a slow charging area. Moreover, based on a multi-agent model, an EV charging management strategy is proposed. The feasibility of the BD framework and the rationality of the energy management strategy are verified in a simulation of 96 time slots. The EV charging management strategy realizes power shifting in the slow charging area, and, with the enhanced use of photovoltaic power, the total cost of EV charging can be decreased in BDs.

Reliability enhancement of distribution networks using ESSs ancillary services: A probabilistic MILP methodology

This paper proposes a stochastic mixed integer linear programming (MILP) approach aiming at improvement of the reliability level of electric distribution network through a contingency-based energy storage systems (ESSs) incorporation, considering ESSs ancillary services and control sequences in service restoration. Further, charging stations installed in each ESSs are supposed to be purchased from various ESSs service providers with different charging/discharging rates. The proposed fitness function aims to simultaneously minimize the expected total cost of reliability (ETRC) and the expected system average interruption duration index (ESAIDI), to deal with economic and technical reliability aspects, respectively. The ETRC includes total cost of interruption and the total ESSs incorporation cost. In addition, the uncertainties in the restoration process in presence of the ESSs, including distribution system conditions and the available power of the cooperated ESSs during service restoration process are considered by several prospective scenarios. The effectiveness of the proposed methodology is investigated using a standard reliability test system (RBTS-4). The convergence of the proposed MILP approach is compared to the other methodologies presented in recent studies that proves the higher tractability of the proposed approach.

The value of local electricity - A choice experiment among German residential customers

Renewable resources are often owned by residential customers who do not actively participate in electricity markets yet. To better integrate these decentralized resources into the energy system, market signals must reach the customers. Local energy markets (LEMs) are a promising concept to provide these market signals, and balance generation and demand at distribution network level. We examined the importance of design parameters for LEMs with an adaptive choice-based conjoint study from a customer perspective. Two surveys (a Germany-wide panel of 417 respondents and a regional survey of 239 respondents) show that economic design parameters (monthly cost and investments) are most important for German households to participate in LEMs. However, the sum of non-economic design parameters (interaction frequency, supplier, electricity source, and data privacy) levels with the importance of monthly cost without investment. Results show, that compared to the German average the regional customers are willing to pay a slight price premium on their monthly costs if regional electricity is offered on the LEM. Our results show suitable early adopters for LEMs to be large (>2 persons) residential households with young (≤60 years) inhabitants. Overall, regulatory niches and subsidies allowing LEMs to offer discount prices should be exploited.

Collaborative Optimization of Distributed Scheduling Based on Blockchain Consensus Mechanism Considering Battery-Swap Stations of Electric Vehicles

The proliferation of electric vehicles and active distribution network has brought many uncertainties to the power system. If the power system involves battery-swap stations of electric vehicles, it is difficult to ensure the data security during the distributed scheduling. To solve the problem, this paper sets up a collaborative optimization model for distributed scheduling based on blockchain consensus mechanism, considering the battery-swap stations. The power system was divided into three levels: the transmission network level, the distribution network level and the battery-swap station level. Next, the objective functions were constructed to minimize the generation cost and daily load variance on each level, and the optimal scheduling plan for the power system was solved through multi-level collaborative optimization. The blockchain consensus mechanism was adopted to verify the accuracy of the transaction data, and the production data of all entities were encoded by hash function before storage, such that the data are tamper resistant and traceable. The example analysis shows that our model can effectively reduce the generation cost, lower the daily load variance, and enhance system stability. The research findings shed new light on maintaining the optimization efficiency and data confidentiality of modern power network.

Probabilistic Short-Circuit Current in Active Distribution Networks Considering Low Voltage Ride-Through of Photovoltaic Generation

The probabilistic short-circuit current (PSCC) of photovoltaic generation is determined by the voltage sag at the grid connection and the low voltage ride-through of the unit during the grid fault, while the voltage sag and the low voltage ride-through are both stochastic. According to short-circuit current characteristics and Thevenin equivalent circuit in the transient state, this paper analyzes the changing trajectory of the equivalent internal potential of photovoltaic generation during the period of low voltage ride-through. To deal with the uncertainty of low voltage ride-through, the probability density function by the maximum entropy method is used to characterize the stochastic process of low voltage disconnection of photovoltaic generation. Based on the fault information, the calculation method of PSCC in active distribution network considering the uncertainty of low voltage ride-through of photovoltaic generation is proposed. Two cases of 9-node and 34-node distribution network are used to verify the effectiveness of the method. The obtained PSCC results can reasonably reflect the actual short-circuit current level of the active distribution network.

Modelling of large-scale electric vehicles charging demand: A New Zealand case study

Due to increasing electric vehicles (EVs) uptakes, power system distribution network will have to accommodate the increased load level for charging EVs. Thus, the importance of a robust power system especially in the distribution network level is indisputable. During the planning or reinforcement stage of distribution networks, it is paramount to have some estimations and analyses done on system-wide EV charging loads that will be placed in the network. Thus, this paper systematically investigates the EV fleet composition, market shares, and charging patterns within New Zealand (NZ) area. A multivariate probabilistic modelling of dependent random variables and cumulative distribution functions is adopted for the accurate estimation of aggregated EV charging demands. Several vehicle travel survey data sets are utilised to quantitatively determine charging behaviours and driving patterns of EVs. The developed methodology based on Monte-Carlo simulation (MCS) is utilised to generate results close to the real use-cases daily power demand, which can be further utilised in the analysis of EV charging strategies. In addition, non-smart and smart EV charging strategies are introduced to mitigate impacts of the large-scale EV deployment and to guarantee the charging completion for each EV.

A combined probabilistic modeling of renewable generation and system load types to determine allowable DG penetration level in distribution networks

A combined probabilistic modeling of renewable generation and system load types to determine allowable DG penetration level in distribution networks

<italic>Fast</italic>-TFM—Multifrequency Phasor Measurement for Distribution Networks

To effectively manage the growing number of distributed energy resources, more extensive monitoring is needed at distribution network levels, where a challenging combination of constraints and cost-effectiveness requirements must be taken into account. In this paper, we consider the idea of combining accurate phasor measurement with the capability to analyze harmonic and interharmonic phasors. This creates the need to deal with multiple phasor components having different amplitudes, including interharmonics with unknown frequency locations. For this purpose, we propose an enhanced compressive sensing-based algorithm for the estimation of Taylor–Fourier coefficients in a multifrequency dynamic phasor model. We characterize its accuracy in harmonic and interharmonic phasor measurement and discuss reporting rate and latency performance. We show that very good accuracy can also be achieved as a standard phasor measurement unit, allowing to combine multiple functions into a promising new-generation measurement, monitoring, and diagnostic device.

Voltage Stability of Low-Voltage Distribution Grid with High Penetration of Photovoltaic Power Units

Voltage stability analysis of power distribution systems with high photovoltaic (PV) penetration is a challenging problem due to the stochastic generation of a solar power system. Voltage stability is an important benchmark for defining PV’s penetration level in active distribution networks considering loading capacity. The massive integration of PV power units, the effect of distribution system characteristics, like high ratio of R/X, and the reported collapses in power networks come up in serious studies that investigate their impact and upcoming problems on distribution networks. Therefore, this paper proposes analytical voltage stability and it is implemented on IEEE 34 nodes radial distribution systems with 24.9 kV and 4.16 kV voltage levels. In this regard, in addition to given properties in stability and power loss analysis, a penetration coefficient for PVs is considered. Simulation results prove that the applied method can illustrate the positive and negative effects of PV in distribution networks.

Hierarchical and decentralized optimization method based on multi-agent system for multiple AC/DC hybrid microgrids

AC/DC hybrid microgrids (MGs) have been developed rapidly in recent years due to their efficient integration and management of large-scale distributed energy resources. How to achieve the optimal operation and coordinated control of AC/DC hybrid MGs has become crucial. A multi-agent system (MAS) based hierarchical and decentralized method for coordination operation of multiple AC/DC hybrid MGs is proposed. First, a structure of AC/DC hybrid MGs including wind turbines, photovoltaics, micro-hydro, and biogas generators is designed, which aims at reducing the power conversion loss. Second, a three-level MAS including distribution network (DN) level, MG level, and distributed generation (DG) level is presented. At the DG level, the DG agents obtain the optimal results from the MG agent. At the MG level, the independent optimization is implemented based on the mixed integer linear programming, and the consensus algorithm is utilized to realize the coordination of MG with adjacent MGs through the communication among MG agents when there is imbalance power. At the DN level, the DN agent performs power exchange with AC/DC hybrid MGs to balance the load demand when needed. Finally, the distributed energy management platform is developed by the Java Agent Development Framework platform to simulate the optimal operation of AC/DC hybrid MGs. The results show the rationality and availability of the proposed optimization method.

Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level

This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.

Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level

Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level

Determining the consequential life cycle greenhouse gas emissions of increased rooftop photovoltaic deployment

Abstract Increased power flows on electricity distribution networks, caused by growing photovoltaics (PV) uptake, can result in the implementation of solutions to maintain network function. This study takes a consequential life cycle assessment (LCA) approach to assess the greenhouse gas emissions (GHG) of aggregated PV electricity generation at the distribution network level. The study also considers how future changes in the manufacturing phase of Chinese and Malaysian PV modules, over the period of increasing PV deployment, may affect their GHG emissions. The study finds rooftop PV life cycle values of 21–107 gCO2e/kWh, for various UK PV output yield estimates and module types (Chinese made mono-crystalline (c-Si) and multi-crystalline silicon (Mc-Si), and Malaysian made cadmium telluride (CdTe)) installed in 2015. Prospective assessment of proposed future material efficiency and grid decarbonisation reduces the range to 21 to 87 gCO2e/kWh for modules installed after 2030. Consequential life cycle emissions from network solutions to accommodate growing PV generation shows increased GHG emissions attributable to PV by up to 13% (c-Si and Mc-Si) and 17% (CdTe) where 100% of network users connected install rooftop PV. There is however only a negligible increase in emissions if

Evaluation of Low-Voltage Distribution Network Index Based on Improved Principal Component Analysis

In order to evaluate the development level of the low-voltage distribution network objectively and scientifically, chromatography analysis method is utilized to construct evaluation index model of low-voltage distribution network. Based on the analysis of principal component and the characteristic of logarithmic distribution of the index data, a logarithmic centralization method is adopted to improve the principal component analysis algorithm. The algorithm can decorrelate and reduce the dimensions of the evaluation model and the comprehensive score has a better dispersion degree. The clustering method is adopted to analyse the comprehensive score because the comprehensive score of the courts is concentrated. Then the stratification evaluation of the courts is realized. An example is given to verify the objectivity and scientificity of the evaluation method.

Comprehensive Evaluation of Smart Grid Development Level Under Electricity Market Layout

The smart grid is the latest trend and complex scientific issue in the development of power systems in the world today. With the new round of power system reform and the deregulation of the power market, comprehensive and scientific evaluation of the development level of the smart grid plays an important role in achieving the overall goal of smart grid construction. This paper constructed a comprehensive evaluation index system from the aspects of safety and reliability, economy, intelligence level and sustainability of smart distribution network. Then the comprehensive evaluation model of AHPTOPSIS intelligent distribution network was established. Finally, an empirical study on the development level of smart distribution networks of four power companies in a province was carried out, and corresponding conclusions were drawn.

Reactive power management by distribution system operators concept and experience

In Germany, the majority of renewable generation is connected to the distribution network level which includes low-voltage up to high-voltage (HV) level. The infeed of this power can cause an unacceptable voltage rise. The required additional network equipment, e.g. lines, generates reactive power if they run idle. Reactive power is also required to transport this power in the transmission network. If distribution system operators (DSO) control the reactive power locally, the decentralised generators (DGs) can contribute to reduce the mentioned problems. In this study, a concept of a reactive power management system is presented as it is developed by a joint work of five DSO in Germany. Results of the practical implementation of the first stage are demonstrated. Algorithms to improve the system in a second stage are presented. DGs in the HV level can be used to compensate the reactive power from the lower-voltage levels and even improve the balance to the transmission system. An overall optimisation combined with a local voltage limiting functionality essential to use a high portion of the potential by still keeping the network in a safe operating condition.

Centralized control of district heating networks during failure events using discrete adjoint sensitivities

Real-time control of district heating networks in the case of failures requires for accurate and fast strategies able to guarantee thermal comfort to all connected users. In this paper, we demonstrate a control framework that responds to these essential requirements. We minimize a global measure of discomfort based on a smooth maximum approximation. The optimization problem is solved through a gradient-based algorithm that can be naturally integrated with distributed meter readings leading to high accuracy of both forward and sensitivity analysis. Objective function gradients are computed by a discrete adjoint method, which is fast and nearly insensitive to the dimensionality of the optimization problem. The proposed framework is tested with numerical experiments on a reference medium-size distribution network in Turin. Results show that the thermal comfort of most critical users increases quickly, yielding to a nearly homogeneous discomfort distribution at the end of the optimization process. Studying the effect of the inlet pressure head on the optimized system performance reveals that a centralized operation results in increased robustness of the network and allows reducing backup pumping equipment. Furthermore, applying the proposed framework at the distribution network level yields remarkable benefits also in case of failures in the main transportation network.

Real-Time Integration of Intermittent Generation With Voltage Rise Considerations

In the modern electric power grid, a commonly observable recent phenomenon is the increasing penetration of renewable generation sources especially at the distribution network (DN) level. The traditional DN is not designed for bidirectional power flow induced by these volatile sources and, therefore voltage rise is a major concern. In order to enable mass renewable integration into any type of existing radial DN without requiring expensive line/bus upgrades and avoiding adverse effects of voltage rise, these generation sources (with possible nonconvex discrete output levels) must be dispatched in real-time while taking into account nonconvex voltage constraints. Ubiquitous connectivity between power components is available in today's grid due to the cyber-physical nature of these devices. We leverage this to propose a distributed algorithm based on principles of population games for efficient dispatch that minimizes dependence of the DN on the main grid for sustainable system operation. Theoretical and simulation studies show that the proposed algorithm allows for the seamless coexistence of a large number of renewables that are highly responsive to fluctuations in demand and supply with strong convergence properties while successfully mitigating voltage rise issues.

Assessment Method for Substation Capacity Credit of Generalized Power Source Considering Grid Structure

This paper presents the concept of the generalized power source in an active distribution network. After the energy storage system (ESS), distributed generators (DG), and demand-side controllable load are connected to the active distribution network, part of the system load can be undertaken by these ESS, DG, and controllable load instead of relying on the capacity of the substation, which greatly improves the reliability of the system. The above-mentioned distributed energy resources in the active distribution network are collectively referred to as the generalized power source (GPS). Substation credible capacity refers to the capacity of the GPS to supply the distribution network that is equivalent at the high voltage distribution network level when considering the faults of the main transformer, 110 kV lines, and circuit breakers. Considering the uncertainties and control strategies of GPS, this paper takes a specific distribution area as the background to study its substituted substation capacity. Based on a sequential Monte Carlo evaluation framework and the principle of constant reliability, an evaluation method of the GPS credible capacity is proposed. In order to verify the effectiveness of the method proposed in this paper, the credible capacity of various typical connection modes of a high voltage distribution network is quantitatively analyzed in the case study, which can provide a reference for the capacity planning of an active distribution network substation and grid structure selection.