Optimisation-based Approaches for Evaluating the Aggregation of EVs and PVs in Unbalanced Low-Voltage Networks

214 p.In the near future, it is expected that the distribution system operators face different technical challenges derived from the massification of electric mobility and renewable energy sources in the low voltage networks. The purpose of this thesis is to define different smart coordination strategies among different agents involved in the low voltage networks such as the distribution system operator, the aggregators and the end-users when significant penetration levels of these resources are adopted. New models for representing the uncertainty of the photovoltaic output power and the connection of the electric vehicles are introduced. A new energy boundary model for representing the flexibility of electric vehicles is also proposed. In combination with the above models, four optimisation models were proposed as coordination strategies into three different approaches: individual, population, and hybrid. The first model was defined at the aggregator level, whereas the other models were proposed at the distribution system operator level. Complementary experimental cases about the proposed optimisation model in the individual-based approach and the quadratic formulation in the hybrid approach for the PV power curtailment were carried out to test its response in real-time. Simulations results demonstrated that the proposed coordination strategies could effectively manage critical insertion levels of electric vehicles and photovoltaic units in unbalanced low voltage networks

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

This study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.This work was supported by TECNALIA funding through the 2017 PhD scholarship programme. TECNALIA is a "CERVERA Technology Centre of Excellence" recognised by the Ministry of Science and Innovation. The authors also would like to thank the Basque Government (GISEL research group IT1191‐19) and the UPV/EHU (GISEL research group 18/181) for their support in this work, as well as the TU Dortmund University for allowing the use of its facilities to obtain the results described in this paper. Dr. Kalle Rauma would like to thank the support of the German Federal Ministry of Transport and Digital Infrastructure through the project Parken und Laden in der Stadt (03EMF0203). The work of Kalle Rauma was also supported by the European Union's Horizon 2020 Research and Innovation Programme through SENDER project under grant agreement no. 95775

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

This study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.This work was supported by TECNALIA funding through the 2017 PhD scholarship programme. TECNALIA is a "CERVERA Technology Centre of Excellence" recognised by the Ministry of Science and Innovation. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work, as well as the TU Dortmund University for allowing the use of its facilities to obtain the results described in this paper. Dr. Kalle Rauma would like to thank the support of the German Federal Ministry of Transport and Digital Infrastructure through the project Parken und Laden in der Stadt (03EMF0203). The work of Kalle Rauma was also supported by the European Union's Horizon 2020 Research and Innovation Programme through SENDER project under grant agreement no. 957755

Optimal Coordination of PV Active Power Curtailment and EVs Charging among Aggregators

With the growing adoption of electric vehicles (EVs) and residential photovoltaic (PV) systems around the world, the distribution system operators (DSOs) are facing several technical challenges on their network planning and operation, particularly on low-voltage grids. As the aggregators are intermediary actors at that system level, they are a promising figure to coordinate these devices in an aggregated manner to help to mitigate adverse effects like overloading of network assets. However, to do so, proper coordination techniques among these entities and the DSO should be developed to avoid further investments in new network assets. In this context, a centralised coordination strategy among aggregators at the DSO level is proposed. By employing a linear programming model, the optimal export limit of PV and charging profile for each aggregator is dictated by the DSO, maintaining the operational limits of the network assets. A case study on two aggregators with moderate and critical penetration levels was carried out. Results show that, by controlling the aggregated export limit of PV power and the aggregated charging rate of EVs, high penetration levels can be integrated into current networks with minor or no need for reinforcing network infrastructure.The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this wor

A Straightforward Methodology to Obtain the Power Coefficients Matrices for Unbalanced Distribution Networks to be Used in Flexibility Markets

The objective of the paper is to address the congestion problem in a specific distribution line by means of sensitivity coefficients seeking an intelligent a ctivation of t he available flexibility, based not only on economic a spects but also on the efficient use of flexibility. This paper proposes a straightforward methodology to obtain the sensitivity coefficient matrices for the unbalanced distribution networks, employing the perturb-and-observe (P & O) approach to assure an efficient usage of flexible resources. This means that a small change in the active power value of a particular flexibility provider, either load or generator, is applied to evaluate the power variation, therefore the loading variation, in every line of the system. The paper shows how these coefficients can be implemented in at heoretical energy market by the market operators by validating its application in an unbalanced network case and then compared with a real balanced distribution network. The simulations have been carried out in DIgSILENT PowerFactory through its API in Python.H2020, 824414, CoordiNe

Aplicación de los sistemas fotovoltaicos conectados a la red: estado del arte

This paper outlines all necessary concepts to successfully implement a photovoltaic system as an alternative in a distributed generation scheme. For this purpose, it is made a short state of the art in which basic concepts are addressed, from a solar cell operation to smart grid concepts applied on demand management. Likewise, a review of the different regulatory frameworks in Colombia is entailed, especially those related to distributed generation, due to the lack of these ones. It is necessary to make a comparison with other regulations from other countries, such as Germany, Spain and USA, in order to obtain a suitable work model. Finally, a photovoltaic system connected into the low tension grid is used as an alternative in distributed generation systems, due to the fact that with this system energy balances can be performed, in case that countries where this alternative is implemented may not have an adequate regulatory framework established, so that users will not have problems with regulatory entities.En este trabajo se describen todos los conceptos necesarios para lograr implementar un sistema fotovoltaico como alternativa para ser utilizado como generador distribuido. Para ello, se realiza un pequeño estado del arte en el cual se manejan conceptos básicos, desde el funcionamiento de una celda solar hasta conceptos de redes inteligentes aplicados en la gestión de la demanda. Asimismo, se abarca un repaso sobre los marcos regulatorios existentes en Colombia, donde se habla de generación distribuida debido a la falta del mismo. Es necesario comparar tales regulaciones con los diferentes marcos regulatorios existentes en otros países, como Alemania, España y EE.UU., para obtener un modelo de trabajo idóneo. Finalmente, se decide utilizar un generador fotovoltaico conectado a la red de baja tensión como alternativa en los sistemas de generación distribuida, ya que con estos se pueden realizar balances energéticos, esto en caso de que en el país en donde se emplee esta alternativa no se tenga establecido un marco regulatorio adecuado, de manera que el usuario no tenga problemas con las entidades regulatorias actuales

A review of the population-based and individual-based approaches for electric vehicles in network energy studies

The growing trend of introducing electric vehicles (EVs) into power systems to reduce the environmental emissions in the transport sector is gaining significant attention among electrical power system agents for two reasons: the potential grid services the EVs can offer in an aggregated manner and the possible undesirable effects of massive integration in grid operation that can increase the requirement for investment in new assets. In this context, the aggregator is the representative entity that needs to maximise the benefits in the management of these sizeable quantities of vehicles while fulfilling the requirements of grid services requested by the distribution system operator. In this study, we review the concept of EV aggregators and their potential services to the distribution network. Several studies related to EVs aggregation modelling have been analysed and classified into three groups: individual-based, population-based, and hybrid approaches. We present the current status of EVs aggregation modelling as well as future research trends. Furthermore, we discussed the performance comparison of EVs models from several manufacturers utilised in network integration studies, likewise the most relevant databases and surveys. Finally, we arranged and annexed the most relevant mathematical expressions of the reviewed approaches, thereby simplifying the comprehension of the methods.We would like to gratefully acknowledge that this study was made possible with the help of TECNALIA funding through a PhD scholarship. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work

New energy bound-based model for optimal charging of electric vehicles with solar photovoltaic considering low-voltage network's constraints

This paper introduces a linear programming (LP)-based optimisation method of charging electric vehicles (EVs) in a decentralised fashion. It exploits the available photovoltaic (PV) power to charge EV batteries while maintaining the low-voltage (LV) network within its operational limits. A new energy-bound model is implemented in order to meet the connected EVs energy requirements. This model highlights two main aspects: first, the proposed formulation seeks to compute both the upper and lower energy boundaries from the arrival energy and no from zero. Second, the charging power is dynamically adjusted by combining a fixed and variable charging rate to assure the technical limits of the network. This means maximising power delivered to all EVs for a given period by optimising the charging rate of each EV connected. Besides, a network sensitivity analysis technique is developed to manage voltage and loading constraints. The accuracy of the proposed linear approximation was tested simulating two cases (moderate and high penetration level of PVs and EVs) on a real LV feeder. Results over a set of simulations for winter and summer seasons demonstrate that this method can be effectively implemented as a charging strategy and for energy planning studies.This work was supported by TECNALIA funding through its PhD scholarship program. The authors also would like to thank the Basque Government (GISEL research group IT1191-19) and the UPV/EHU (GISEL research group 18/181) for their support in this work

Centralised coordination of EVs charging and PV active power curtailment over multiple aggregators in low voltage networks

Publisher Copyright: © 2021 Elsevier LtdWidespread application of residential photovoltaic (PV) systems and electric vehicles (EVs) has led the distribution system operators (DSOs) to face new technical challenges such as overloading and significant voltage variations, especially on low voltage (LV) grids. This adverse effect may be mitigated by employing the aggregators as intermediary actors to coordinate the operation at the distribution level. Therefore, this paper proposes a centralised coordination strategy to mitigate both PV and EV impacts, such as voltage rising/dropping at noon or evening, respectively, by defining the optimal export limit of PV power and EVs charging among multiple aggregators at the DSO level. The latter is in charge to dictate the optimal aggregated signals to every aggregator by employing a mixed-integer quadratic programming (MIQP) approach. The aggregated PV power is evenly managed for each aggregator by weighting. Two convex optimisation models are defined to satisfy both power and voltage constraints of the LV network. Each proposed optimisation approach can be utilised when there is or no detailed information about the LV network topology. The concepts discussed in this paper are tested on a real low voltage network considering a critical penetration level of EVs and PVs.This work was supported by TECNALIA funding through its Ph.D. scholarship program. The authors also would like to thank the Basque Government, Spain (GISEL research group IT1191-19) and the UPV/EHU, Spain (GISEL research group 18/181) for their support in this work. This work was supported by TECNALIA funding through its Ph.D. scholarship program. The authors also would like to thank the Basque Government, Spain (GISEL research group IT1191-19) and the UPV/EHU, Spain (GISEL research group 18/181) for their support in this work. Supplementary data related to this research can be found at https://data.mendeley.com/datasets/yf4s297sty/1.Peer reviewe