Local Grid Research Articles

Research on Community Grid Management Mode Based on System Database Processing

In the process of urbanization, living and working areas are increasing, and the population is also increasing, which makes community management more difficult and reduces the life quality of residents. In order to improve the quality of community management, this paper briefly introduced the concept of community grid management mode based on the system database and conducted a case study on Taocheng District, Hengshui City, Hebei Province. The local community grid management mode used in the area was introduced; moreover, the effectiveness of the community grid management mode was evaluated using the framework of the analytic hierarchy process. The results showed that with the full implementation and improvement of the community grid management mode, the efficiency, effectiveness, and benefits of the community management significantly improved.

Advanced Local Grid Control System for Offshore Wind Turbines with the Diode-Based Rectifier HVDC Link Implemented in a True Scalable Test Bench

Diode-based HVDC link technology is considered an alternative to reduce the cost and complexity of offshore HVDC platforms. When this technology is used, the AC grid of the wind farm must be created artificially. This paper proposes an advanced frequency control method that permits forming an AC grid voltage system to connect offshore wind turbines to a diode-based HVDC link rectifier. The proposed algorithm can be easily implemented in the wind farm’s overall Power Plant Controller (PPC) without any change in the commercial wind turbine firmware. All wind turbines receive reactive power targets from the PPC to maintain the frequency and amplitude of the offshore AC line, delivering the maximum active power generated by the wind. A novel black start method is proposed to establish the wind farm’s local AC grid voltage system. The control method has been implemented and proved in an experimental setting. The black start has been successfully verified, and the frequency control algorithm shows excellent experimental results.

A novel ensembling of deep learning based intrusion detection system and scroll chaotic countermeasures for electric vehicle charging system

The usage of Electric vehicle (EVs) has been exponentially growing due to its focus on eco-friendly means of transport, distributed charging platform and user dictated supporting infrastructures. The EVs are charged by the charging stations which equipped with Electric Vehicle Supply Equipment (EVSE) that contains Internet enabled computers. These systems are considered to be more important for controlling the function such as charging electric vehicles, authorization and smart connection to the local power grid using different wireless technologies such as green WIFI, Bluetooth and even 5 G. The cyber-attacks such as DoS and DDoS attacks can violate integrity, confidentiality and availability of the EVSE resources. Hence the intelligent Intrusion Detection System (IDS) is required to ensure the system for the robust and trustworthy deployment of EVSE resources. To meet the above challenge, this paper proposes new composite and intelligent system which contains the deep learning based IDS and high random chaotic generators to safeguard the data against the different cyber-attacks. The proposed IDS has been modelled based on Gated Recurrent Units (GRU) and counter measures are performed by adopting the Enhanced Chaotic Scroll attractor keys (ECSA). The contribution of this research paper is as follows: Novel Dataset Preparation for EVSE under different attack scenarios, Implementation of high accurate multi-objective accurate GRU based IDSs, Design of Enhanced Chaotic Countermeasure Encryption Schemes for the counterfeiting the attacks in Internet Enabled EVSE system. The extensive experimentation has been carried out into two important phases. In first phase algorithm centric metrics such as prediction accuracy, time of detection, whereas in second phase key centric metrics such as Number of Changing Pixel Rate (NPCR), Unified Averaged Changed Intensity (UACI), Key sensitivity and entropy are calculated and compared with the other existing methodologies. Results demonstrates that the proposed ensemble system has outperformed than the other methodologies and proves its strong place in designing the more secured Internet Enabled EVSE systems.

A low-carbon peak-load regulation trading strategy for large-scale wind power integration using information gap decision theory

It is critical for power system to uphold operation security while considering the cooperation of thermal power and new flexible resources, such as energy storage and demand response (DR). This paper investigates the integration of carbon emission trading with peak-load regulation trading to analyze the effects of carbon change generated using thermal power, energy storage, and demand response, and builds a deterministic multisource low-carbon peak-load regulation trading optimization model. To describe wind power uncertainty, we apply information gap decision theory (IGDT) to quantify the information gap between the predicted and actual data of wind power; subsequently, we construct a multisource low-carbon peak-load regulation trading optimization model based on IGDT considering the uncertainty. Finally, a local power grid in Northwest China is considered as a case study, and we establish regular, low-carbon, stochastic and comprehensive four peak-load regulation scenarios to analyze the impact of carbon emissions trading, energy storage, and DR involved in wind power peak-load regulation trading. The results show the following. (1) The individual application of the energy storage system (ESS) and DR can reduce peak-load regulation cost by 4.64% and 7.68%, respectively, whereas a 8.38% reduction is achieved when they are applied together. (2) When considering the uncertainty of wind power, the grid connected power of wind power is reduced by 2.15% and the total peak shaving cost is increased by 10%. With the increase in uncertainty, the cost of peak shaving trading scheme is always lower than the expected value, indicating that the IGDT method is effective. (3) When the price of the carbon emission trading ranges from 85–95 CN¥/t, the peak-load regulation cost of thermal power units are compensated; moreover, the peak-load regulation cost of wind power and allowable uncertainty reach optimum values when the acceptable price is less than 80 CN¥/t in the worst scenario. In summary, the ESS and DR can enhance the flexibility of the system for peak-load regulation, thus increasing wind power grid connection, and carbon emissions trading can improve the net economy of peak-load regulation of thermal power units. The IGDT method can describe the uncertainty risk of wind power output and establish a peak-load regulation trading scheme that satisfies the expectations of decision makers with different risk attitudes. The peak-load regulation trading scheme must carefully consider the carbon emission trading price: if the carbon emission trading price is excessively high, it will result in a retaliatory grid connection of wind power to compensate for the carbon trading costs, and the system cost will increase rapidly.

Power-to-gas as an option for improving energy self-consumption in renewable energy communities

Renewable Energy Communities (RECs) have been introduced by the Renewable Energy European Directive (REDII) in order to allow their members to collectively produce, consume, store and sell renewable energy. With the distributed generation deployment, the electricity injection into power grids has to be limited. Thereby, the RES management has to maximise the local energy self-consumption (SC). The present work deals with Power-to-Gas (PtG) application for blending hydrogen in the local gas grid for maximising the energy-SC, comparing it with traditional electric batteries (PtP). Moreover, this study investigate how SC-based tariffs for RECs can represent an indirect incentive for hydrogen production. To do so, a case study, consisting of 200 dwellings, has been analysed. Four PV configuration have been considered for evaluating different RES excess conditions. PtP and PtG systems have been implemented and compared each other. The hydrogen production cost has been assessed exploiting the renewable electricity incentive scheme.

A Road Test for Vehicle-to-Grid Tech: Utrecht leads the world in using EVs for grid storage

Unlike those you may have grown accustomed to seeing, many of these stations don't just charge electric cars—they can also send power from vehicle batteries to the local utility grid for use by homes and businesses.

Influence of local grid refinement on prediction of impinging jet heat transfer using Scale-Resolving-Simulation methods

A fine near-wall resolution plays a crucial role in simulations of unsteady heat transfer from a wall. A generation of fine structured grids for a complex domain is cumbersome and requires an enormous number of grid points and a local grid refinement is a possible technique for a grid point reduction. The present study addresses numerical simulations of impinging jet heat transfer on locally refined computational grids using the Scale-Resolving-Simulation methods (DES, LES and PANS). The study is performed at a Reynolds number Re = 23000 and two nozzle-plate distances H/D = 2 and H/D = 6. DES and the PANS model with f k = 0.25 predicted results closest to experimental data. However, DES significantly over-predicted heat transfer at the location r / D = 1 − 2 in the small nozzle-plate distance case ( H / D = 2). The decrease of physical resolution in the PANS model resulted in the over-prediction of heat transfer close to the nozzle axis. In conclusion, the influence of the local refinement in the perpendicular direction was rather low compared to the longitudinal direction. Moreover, the local grid refinement improved results predicted by LES and DES in the small nozzle-plate distance case.

An inter-city energy migration framework for regional energy balance through daily commuting fuel-cell vehicles

Spatiotemporal energy interaction and sharing are promising solutions to penetrate renewable energy, enhance grid power stability, and improve regional energy flexibility. However, the current literature is restrained in a small-scale neighborhood level, without considering inter-city energy migration through spatiotemporal complementarity between renewable-abundant regions (like suburb or countryside areas) and demand-shortage regions (like city centers). In this study, the energy interaction boundary is extended from a neighborhood scale to an inter-city scale, to maximize the renewable energy penetration, demand coverage, and reduce regional energy imbalance. This study firstly proposes a holistic framework on inter-city transportation-based energy migration, consisting of a residential community with rooftop photovoltaic systems and electrical batteries, an office building, hydrogen vehicles (HVs), a hydrogen (H2) station, and local power grids, for the energy transmission between building groups in spatially different regions through the daily commuting of HVs. Optimal grid-regulation strategies are thereafter proposed and adopted to stabilize the grid power and reduce energy costs. Parametric analysis on energy trading strategies and prices has been conducted, to improve the participation motivations of different stakeholders. Results indicate that, compared to the reference case with isolated buildings and vehicles, the transportation-based energy migration framework covers 23.2 % of the office energy demand and elevates the community’s renewable self-use ratio from 72.7 % to 98.6 %. Meanwhile, the maximum grid-export power in the renewable-abundant region (suburb residential community) and the annual grid-import power in the demand-shortage region (city-center office) are reduced by up to 86.9 % (from 155.7 to 20.4 kW) and 29.4 % (from 49.0 to 34.6 kW), respectively. Moreover, even considering the fuel cell degradation cost of HVs, the transportation-based energy migration framework reduces the operating costs of the office building and HVs (the H2 cost and the fuel cell degradation cost) by 16.4 % (from $52791.3 to $44154.7) and 1.7 % (from $27172.5 to $26707.4), respectively. Afterward, compared to the reference case, the peak-shaving and load-shaping grid-regulation strategies can decrease the peak grid-export power of the community by about 71.6 % (from 155.7 to 44.2 kW), and the maximum grid-import power of the office by 23.7 % (from 49.0 to 37.4 kW), respectively. Furthermore, the transportation-based energy migration framework is economically feasible, only when the renewable export price for H2 production is 0.07 $/kWh, the onsite-renewable-generated H2 lower than 6.5 $/kg for the HV owners, and the vehicle-to-building electricity lower than 0.3 $/kWh for the office building. This study provides a novel inter-city energy migration framework with hydrogen networks to enhance district energy sharing, improve regional energy balance and reduce carbon emission, together with frontier guidelines on energy trading prices to promote participation motivations from different stakeholders.

Modeling fracture transient flow using the Embedded Discrete Fracture Model with nested local grid refinement

Transient flow around hydraulic fractures is an important topic in the study of tight reservoirs. In this work, the Embedded Discrete Fracture Model (EDFM) is combined with nested local grid refinement (LGR) to improve its accuracy for simulating near-fracture transient flow. An automatic grid refinement procedure is developed to iteratively conduct LGR around complex fractures. In each iteration, the cells intersected by or close to fractures are selected and refined. The size of the refinement region and the level of refinement can be adjusted. Through this process, the cell size in the near-fracture region is reduced rapidly, while the total cell count remains at a relatively low level. An analysis of the optimal refinement ratio for regular Cartesian grids is also conducted. Furthermore, the EDFM is implemented in grids with nested LGR, and connections between the matrix and fractures are properly determined to compute the transmissibility factors as input for reservoir simulators.The developed methodology is first verified against a logarithmic LGR model for different fracture orientations, and the results show that different flow regimes can be reliably simulated. Subsequently, the flow regimes for non-orthogonal, non-parallel, and nonplanar hydraulic fractures are studied with this approach to illustrate the unique patterns of transient flow around complex fractures. This work provides a general and convenient method to perform transient analysis for reservoirs with complex fracture geometries.

Complete operational voltage assessment of Shandong pilot offshore wind project

AbstractThis article presents a thorough methodology for the voltage assessment of pilot offshore wind project in Shandong province, China. The results presented in this paper can be considered as the milestone of the offshore wind research in Shandong Province since there is still no grid codes for offshore wind power plant grid connection in the local electrical power grid. It mainly consists of three parts. In the first part, a detailed model of the offshore wind farm created in the DIgSILENT PowerFacotry simulation platform is presented, including wind turbines, power converters, transformers, submarine cables and relevant control schemes. In the second part, nonlinear time‐domain simulations were performed to analyze the wind farm's active power, reactive power, and voltage conditions under different wind scenarios. Based on the simulations results, a dynamic reactive power compensation system was proposed, and the consequence of the reactive power compensation was also demonstrated using nonlinear time‐domain simulations.

Modelling electric vehicles uptake on the Greek islands

For decades, the Greek islands have been facing challenges in terms of quality of power supply, increased carbon dioxide equivalent (CO2eq) emissions, and costs due to their reliance on oil-fired generation subsidised by the Greek state. In light of the recent reforms to decarbonise the islands' region while enhancing their local grids, this study investigates the impact of electromobility considering an autonomous electricity system supported by storage versus an interconnected one. Two Electric Vehicles (EVs) deployment scenarios coupled with several charging strategies have been modelled using the PLEXOS energy systems model. The results highlight that the Vehicle-to-Grid (V2G) scenarios demonstrate the most evident benefits for the islands' electricity systems, performing adequately under both the Autonomous and Interconnection scenarios concerning the economic and environmental impact. Such scenarios have the potential to reduce emissions by 8.5% while dropping costs up to 20% by 2040, when combined with the required renewables expansion plan. From the security of supply perspective, the results demonstrate improvements under the interconnected context accompanied by thermal generation restrictions without however eliminating power shortages recorded already in a non-EV case. The analysis also showcases an escalated impact on power shortages and curtailments during the maximum week, particularly when combined with an ambitious EV deployment. Yet, V2G may increase renewables share up to 7% in 2040. In this context, EVs could mobilise the additional deployment of 600 MW renewables by 2040 if interconnections with the mainland are realised. Assuming islands continue operating as autonomous electricity systems, the additional capacity to accommodate may reach 720 MW.

Multi-objective control of isolated power systems under different uncertainty approaches

This paper proposes and compares a set of multi-objective supervisory controllers for an isolated power system including a gas turbine operating in load following mode as a dominant source of generation, a battery energy storage system, and stochastic renewable generation. It analyzes their capability to coordinate the gas turbine and energy storage to provide isochronous speed control, achieving fast frequency regulation for the local grid, while the gas turbine can still operate with minimum deviation from its optimal loading and the storage system can follow a pre-scheduled reference state of charge trajectory. In more detail, we consider and compare different control strategies to handle model and disturbance uncertainties, including stochastic model predictive control under various parametrizations of the scenario approach, and robust control under the H∞ paradigm. The various controllers are compared against a benchmark, i.e., a deterministic predictive control strategy. Instead of point-to-point comparisons for some arbitrary cases (i.e., worst-case or expected), empirical distributions of the controller’s performance for the whole probability spectrum are derived, leading to more accurate and representative comparisons. The analyzed performance indicators are nominal dynamic performance, constraint violation probabilities, and expected system operation performance. The results indicate the clear superiority of stochastic control over both robust and deterministic control in dealing with both parametric and disturbance uncertainty. Moreover, choosing an appropriate parametrization is shown to be essential to achieve both good nominal performance and lower violations probability, indicating that the superiority of stochastic control comes with the drawback of needing user-defined tuning from the designer.

Private vs. public value of U.S. residential battery storage operated for solar self-consumption

SummaryCompensation structures for residential solar are evolving toward a model that incentivizes using battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner provide customer bill savings up to $20–30 per kWh of storage capacity annually, but virtually no grid value. Relative to market-based dispatch, this value gap remains across customers and will become more severe over time, insofar as increased renewable energy penetration leads to more volatile wholesale prices. This inefficiency primarily stems from residential batteries largely sitting idle on peak days. We show that incentivizing storage customers to respond to market prices, particularly on peak days, would enhance both private and public value. Unconstrained grid discharging increases exports to distribution networks, but 50–70% of the potential market value could be achieved without materially degrading solar self-consumption levels or increasing local grid stress.

Hosting Capacity of the Power Grid for Electric Vehicles - A Case Study on a Swedish Low Voltage Grid

Hosting capacity (HC) is described as the maximum amount of new production or consumption that can be added to the grid without causing a violation. In this case study, a deterministic approach is used to investigate the HC of electric vehicle (EV) charging in a low-voltage grid, containing 13 detached single-family houses. It investigates how different parameters affect the HC, and what is causing the violation in the grid. Two different performance indices (PI) are used in the study: power cable overloading and voltage drop. The local grid is simulated for one year for four cases and the HC is derived for these. The cases are distinguished by two different violation thresholds for the voltage drop and two different implementation orders of the location of the charging. The results show that the HC of the grid is 6-11 EVs charging simultaneously. The difference in HC is primarily due to variation in the baseload through the year and location of charging. The cable between the substation and the first cable cabinet was the major contributor to the fault, and the PI causing the violation differed depending on what case was used.

Distributed Control of Distributed Energy Resources in Active Power Distribution System for Local Power Balance With Optimal Spectral Clustering

This article proposes a distributed control architecture for distributed energy resources (DERs) that include photovoltaics (PVs) and battery energy storage systems (BESSs). The control architecture is based on the virtual clustering of DERs to provide power balance (minimizing the net load (generation load) in each cluster) in each cluster considering the state of charge of the BESS. First, the architecture designs a spectral clustering to develop optimal clusters based on the number of DERs that provide clusters with minimum power transfer between clusters. Then, an error-minimization-based optimal control architecture provides sufficient set points to the BESS intending to provide power balance. The novelty of the proposed clustering is that it provides a distributed dynamic model of the grid with measurements that are stable and scalable. The control approach not only provides an optimal set point for the BESS but also takes into account the state of charge and provides intercluster balance. This framework can also manage the local grid effectively as the distribution is dynamic considering the state of the BESS and the number of DERs. The distributed control objectives are efficient and scalable. The architecture is tested on the IEEE 123-bus system and the IEEE 8500-bus system and observed that the approach provides effective power balance and outperforms the existing methods.

Optimal Distributed Frequency and Voltage Control for Zonal Electricity Markets

Zonal pricing is a well-suited mechanism to incentivize grid-supporting behavior of profit-maximizing producers and consumers operating on a large-scale power system. In zonal electricity markets, local system operators create individual price zones, which provide appropriate price signals depending on local grid conditions such as an excess or shortage of electrical energy in certain regions. In this paper, a real-time zonal pricing controller for AC power networks is presented that ensures frequency and voltage stability as well as Pareto efficiency of the resulting closed-loop equilibria. Based on a dynamic network model that takes line losses and power exchange with adjacent price zones into account, distributed continuous-time control laws are derived which require only neighbor-to-neighbor communication. Application to a real-time congestion management strategy illustrates how spatially and temporally differentiated prices enable grid-supportive operation of the participants without interventions by a superordinate control authority. Effectiveness of different zonal pricing concepts compared to an isolated grid operation is demonstrated through simulations on the IEEE-57 bus system.

A graph-rotation model for optimal ship routing in ice conditions

Ship independent navigation in ice-infested waters is a risky operation. However, it is widely practiced in the Northern Baltic and other freezing regions. Up to now, there is no conventional algorithmic approach, which provides robust and efficient routes for winter navigation. In the article, we propose a new graph method for algorithmic finding of a route in the complicated environment. This method is based on a concept of local grid rotation and provides optimal routes in sense of its length and number of direction changes. Unlike Dijkstra and A*, the new method allows finding a short route with minimum number of zig-zags, which ensures distance from shores. The presented method is computationally rather efficient and employs extended wave algorithm which has been developed earlier by the authors. We provide the case study of finding an efficient route in ice conditions of the Baltic Sea given by an ice chart. Calculations are performed for a vessel with Ice2 class travelling to Gulf of Bothnia. The route found by the new method is compared with the globally shortest path evaluated by Dijkstra's algorithm on a graph with advanced grid. The new algorithm provided much smoother route with nearly the same travel distance.

Techno-Economic Analysis and Optimisation of Campus Grid-Connected Hybrid Renewable Energy System Using HOMER Grid

This study aimed to conduct a techno-economic performance and optimisation analysis of grid-connected PV, wind turbines, and battery packs for Syiah Kuala University, situated at the tip of Sumatra island in the tsunami-affected region. The simulation software Hybrid Optimisation Model for Electric Renewables (HOMER) was used to analyse and optimise the renewable energy required by the institution. The methodology began with the location specification, average electric load demand, daily radiation, clearness index, location daily temperature, and system architecture. The results revealed that the energy storage system was initially included in the simulation, but it was later removed in order to save money and optimise the share of renewable energy. Based on the optimisation results, two types of energy sources were chosen for the system, solar PV and wind turbine, which contributed 62% and 20%, respectively. Apart from the renewable energy faction, another reason for the system selection is cost of energy (CoE), which decreased to $0.0446/kWh from $0.060/kWh. In conclusion, the study found that by connecting solar PV and wind turbines to the local grid, this renewable energy system is able to contribute up to 82% of the electricity required. However, the obstacle to implementing renewable energy in Indonesia is the cheap electricity price that is mainly generated using cheap coal, which is abundantly available in the country.

Study of novel steam assisted gravity drainage multilateral wells with dynamic gridding

SAGD (steam assisted gravity drainage) performance and its stream chamber growth are primarily determined by the vertical permeability of a reservoir. To deal with inter-bedded shale (IBS)-isolated intervals in bitumen reservoirs and improve steam chamber conformance, novel multilateral (MLT) wells with laterals and/or vertical legs in their trajectories are drilled to penetrate IBS. PetroChina Canada LTD. (PCC) has implemented MLT wells as a technology trial to evaluate potential mitigation to the presence of IBS in its MacKay River SAGD Project. Taking into account both accuracy and efficiency, dynamic local grid refinement (DLGR) is incorporated into the description of the mass and heat transfer phenomena in the vicinities of MLT wells. Also, to represent MLT injection and production wells as open hole branches, their lateral properties are adjusted by considering pore-scale mechanisms of fluid flow and heat transfer. With all these novel features established, the impacts of MLT wells on steam chamber growth and oil recovery are evaluated. It is discovered that MLT wells are conducive to increasing both injectivity and productivity due to the improvement of contact and drainage areas. Besides, how MLT wells perform with various steam operation strategies, geological parameters, injection pressure and NCG (non-condensable gas) wind-down scenarios is assessed.

Mathematical Model of a Local Grid with Small Modular Reactor NPPs

The technical and economic processes of the Local Grid, regional electricity system comprising small modular reactor nuclear power plants, renewable electricity generators, and electricity storage systems are investigated. Smart grid technologies are used in the management of such a system. In relation to the electricity system, the Local Grid acts as a consumer or producer of electricity depending on the price situation in the wholesale market and its own ability to balance the volume of electricity generation-consumption.
 The Local Grid market is considered to be perfect, otherwise the wholesale electricity market is characterized by imperfect competition. The mathematical model of the Local Grid is offered. The presented model adequately reproduces the characteristics of the interaction between the local market and the wholesale market. The mathematical model is generated in the form of the commitment problem for small modular reactors and electricity storage systems. The model reflects the technological limitations for the loading modes of small modular reactors and units of the energy storage system, which operate in the modes of direct and reverse energy conversion. In particular, the model reflects the shunting modes and start-shutdown modes of small modular reactors and charge-discharge modes of energy storage system units, which together determine flexibility of the operation modes for the entire power system. The commitment problem of small modular reactors of a nuclear power plant, units of the electricity storage system, and transmission lines connecting the Local Grid with the power system is a mixed integer programming problem with an objective function of minimized system costs.
 Cluster integer functions are used to reduce the dimensionality of the problems of mathematical modeling the loading modes of the Local Grid in the descriptions for the sets of the same type small modular reactors, as well as the same type energy storage units. The Local Grid model reproduces the modes of its disconnection from the system operator's network to increase nuclear safety in the event of a natural disaster or hostilities. The results of computational experiments on modeling the commitment modes of the local electrical grid are presented.
 The experiments used standard data on the volume of electricity consumption and its production from renewable energy sources. The results of the computational experiment confirm the adequacy of the suggested mathematical model for the Local Grid. The presented model is suitable for the use both independently – to analyze Local Grid functioning - and in combination with the models of electric power industry - to determine the impact of the Local Grids on the electricity system.
 The article is developed based on the results of the research carried out under target program “Support of State-Priority Research and Scientific and Technical (Experimental) Solutions of the Department of Physical and Technical Problems of Energy of the NAS of Ukraine for 2022 – 2023” with program expenditure classification code 6541230 (applied research).