Design of Ancillary Services for Battery Energy Storage Systems to Mitigate Voltage Unbalance in Power Distribution Networks

power system, voltage unbalance issues are expected to exacerbate. Single{phase connectedphotovoltaic (PV) panels may cause unequal three{phase power ows, resultingin unbalanced grid currents and voltages. In addition, the random charging behaviour ofPlug{in Hybrid Electric Vehicles (PHEVs) equipped with single{phase on{board chargersis expected to further contribute to voltage unbalance rise as the number of thesedevices grows. If voltage unbalance increases to unacceptable levels, it may have adverseeects on power system operation and on the equipment connected to it. Traditionally,the phase swapping technique has been deployed by distribution system operators forvoltage unbalance mitigation, while other mitigating techniques include the deploymentof power electronics-based devices. The majority of the devices reported in the literatureare based on three-phase congurations, including series and parallel active power lters,unied power quality conditioners (UPQCs), static synchronous compensators (STATCOMs)and, more recently, three-phase distributed generation (DG) inverters.This research proposes the use of single-phase battery energy storage systems (BESSs)for the provision of phase balancing services, which has been considered only in a few literatureworks, with most of these research papers focusing on three-phase BESSs. In thisthesis, a novel control strategy is proposed for single-phase BESS units to compensatevoltage unbalance by injecting both active and reactive power simultaneously. The proposedapproach is based on the coordinated operation of three independent single-phaseBESS inverters using local voltage and current measurements.Initially, a comprehensive literature review is performed with the following aims: arobust classication of the ancillary services currently oered by BESSs, harmonisation ofthe notation found in the literature for ancillary services, and identication of potentialfuture applications of BESSs to power grids with large number of Low Carbon Technologies(LCTs). Then, the eectiveness of the proposed voltage unbalance compensationmethod is validated in the simulation environment, where two realistic models of distributionsystems are developed. Next, the impact of increasing PV and EV penetrationlevels on voltage unbalance for a typical UK distribution system is assessed based on adeterministic approach. The control strategy is validated experimentally by carrying outHardware-In-The-Loop (HIL) tests. Finally, an equivalent model of the distribution systemand BESS inverter is derived, which allows to carry out a preliminary probabilisticstudy to cater for the uncertainties related to the location and size of the PVs and EVs,and to evaluate the voltage unbalance levels without and with the BESSs controlled toprovide voltage unbalance compensation.It is concluded that the proposed BESS control system may eectively reduce thevoltage unbalance levels under various loading and generating conditions

Battery Energy Storage Systems in the United Kingdom: A Review of Current State-of-the-Art and Future Applications

The number of battery energy storage systems (BESSs) installed in the United Kingdom and worldwide is growing rapidly due to a variety of factors, including technological improvements, reduced costs and the ability to provide various ancillary services. The aim of this paper is to carry out a comprehensive literature review on this technology, its applications in power systems and to identify potential future developments. At first, the main BESSs projects in the UK are presented and classified. The parameters provided for each project include rated power, battery technology and ancillary services provided, if any. In the next section, the most commonly deployed ancillary services are classified and described. At the same time, the nomenclature found in the literature is explained and harmonised. The second part of the paper focuses on future developments and research gaps: ancillary services that currently are not common but that are likely to be deployed more widely in the future will be described, and more general research topics related to the development of BESSs for power system applications will be outlined

Voltage Unbalance Mitigation by Novel Control of BESS Single–phase Inverters

A voltage unbalance compensation method usingthree single–phase battery energy storage systems (BESSs) isproposed in this paper. A novel control strategy based on orthogonalsignal generation is presented to regulate active and reactivepower injection from the BESS inverters. A modified version ofthe ’IEEE 13 node’ benchmark three–phase distribution system isbuilt in MATLAB / Simulink and three case studies are illustratedto verify the effectiveness of the proposed compensation method

Coordinated Control of Three Single–Phase BESS Inverters Using Local Measurements to Mitigate Voltage Unbalance

Abstract—This paper proposes a control algorithm for single-phase battery inverters to provide voltage unbalance compensation in distribution networks with high penetration of photovoltaic panels and electric vehicles. A typical distribution system is studied to quantify the impact of single-phase loads and generating units on voltage unbalance levels, and identify the conditions that lead to the highest voltage unbalance. Voltage unbalance compensation is then performed by regulating active and reactive power exchange between three single-phase battery energy storage units and the power grid. The proposed control strategy consists of an upper level control system to coordinatethe three units by sending active and reactive power reference signals, and a BESS control system to regulate active and reactive power exchange between each single-phase inverter and the grid. Simulation results show that the effectiveness of this approach depends on the location where the energy storage units are installed. The positive impact of the proposed methodology on balancing the power flow and reducing the transformer zero sequence current is also demonstrated. Finally, Hardware-In-The-Loop (HIL) experiments are carried out to provide validation of the control algorithm in real-time

Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach

A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies

Soil moisture content estimation based on Sentinel-1 and auxiliary earth observation products. A hydrological approach

Summarization: A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies.Presented on: Sensor