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Lessons Learnt from Real-Time Monitoring of the Low Voltage Distribution Network Antimo BARBATO, Alessio DEDÈ, Davide DELLA GIUSTINA, Giovanni MASSA, Andrea ANGIONI, Gianluca LIPARI, Ferdinanda PONCI, Sami REPO
Abstract—Up to now, the evolution of the distribution network toward the smart grid model has been essentially focused on two non-intersecting areas: medium voltage network automation and smart metering. The former one is mainly focused on improving the quality of service, studying and deploying fault location, isolation and service restoration systems, while the latter has been addressed to improve the customer relationship management, promote the customer awareness and enable new smart home services. In most cases a deep investigation of the low voltage network has been left disregarded, even if it represents the asset bridging the medium voltage level up to final customers. This network segment is probably the most affected by regulatory actions promoting intermittent renewable generations, distributed storage, heat pumps and the growing diffusion of electric vehicles utilization. The paper describes a field demonstrator of the FP7 European project IDE4L, where an extensive analysis of the low voltage network has been performed by means of an innovative use of smart meters and the installation of sensors on the medium-tolow voltage substation. Index Terms--smart grid, low voltage network, smart metering, distributed measurement system.
I. INTRODUCTION
T
HE transition towards smart grids has gradually taken place in several areas of Distribution Networks (DNs). Solutions and systems already applied in transmission networks have been progressively integrated at the Medium Voltage (MV) level of DNs, scaled-down in terms of features and costs to meet their requirements. A typical example of such evolution is represented by the increase in monitoring and control technologies for MV level applications [1]. Fault Location, Isolation and Service Restoration (FLISR) technologies are one of those that have gained sustained attention in the past few years. FLISR solutions have been investigated from both a theoretical and practical viewpoint and they are now at a deployment stage [2], [3]. The overall interest of Distribution System Operators A. Barbato, A. Dedè, D. Della Giustina, and G. Massa are with are with Unareti SpA, Via Lamarmora 230, 25124 Brescia, Italy (e-mail:
[email protected]). A. Angioni, G. Lipari and F. Ponci are with RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany (e-mail:
[email protected]) S. Repo is with the Department of Electrical Energy Engineering, Tampere University of Technology, Tampere, FIN-33101 Finland (e-mail:
[email protected]). Contact author: Giovanni Massa.
(DSOs) to realize reliable MV networks is motivated by the opportunity to have reduce power losses and customer inconvenience from power disruptions. Moreover, in several countries, better performance is also encouraged by Performance-Based Regulation (PBR), in which incentives are tied to specific metrics of service quality [4]. The application of a similar approach to voltage quality is under evaluation by some regulation authorities [5] and some authors have already started to investigate this field [6]. Other than MV networks evolution, also smart metering initiatives have been promoted as a way to improve customers’ relationship management and to foster their awareness on their energy habits [7]. Indeed, awareness is considered a first significant step toward a better energy consumption [8]. Smart house services can then take advantage from the availably of customer’s energy data to boost this process, providing benefits for the whole energy system, too [9]. A significant portion of the whole electricity consumption is indeed related to houses, and a clever load management can greatly improve the power systems performance. To this end, Demand-Side Management (DSM) mechanisms [10] can be applied. These technologies are designed not just to reduce customers’ bills, to save energy or to improve customers’ comfort, but also to use energy in a more efficient way by means, for example, of load shifting to off-peak hours, demand adaptation to renewable sources supply, reactions to emergency conditions [12]. In smart grids studies and implementations, one of the least explored field is represented by the Low Voltage (LV) network, the infrastructure spanning from Secondary Substations (SSs) up to final customers. This segment is probably the most affected one by international regulatory changes that are promoting Renewable Energy Sources (RESs), as a way to reduce greenhouse gas emissions, diversify the energy supply, diminish the dependence on imported fuels and, more in general, allow the transition to more sustainable energy paradigms [13]. Despite these obvious benefits, the integration of RESs represents a major challenge: renewable generation is variable and uncertain [14]. Therefore, the wider and wider presence of RESs is making the management of the LV network more and more difficult [15]. Thus, monitoring the real operating conditions of the LV networks in terms of power flows, phase unbalances, voltage levels and other power quality indicators becomes essential to efficiently operate these kinds of networks.
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The paper describes a field demonstrator developed and deployed within the FP7 European project IDE4L [16], where an extensive analysis on a LV network has been performed. The IDE4L low voltage demonstrator, consisting of about 300 customers and more than 100 domestic PhotoVoltaic (PV) panels, has been focused on the innovative use of smart meters and advanced sensors on the medium-to-low voltage substation. Meters and sensors have been used to collect several data, among which current, voltage, power and energy values. The monitoring campaign of the LV networks has been carried out for more than one year and collected data have been analyzed to investigate the performance of the network as well as to identify and study specific phenomena, mainly associated to RESs. The main original content of the work is represented by the field demonstration of an innovative monitoring and control infrastructure pointed-out and implemented by the IDE4L project at the MV and LV distribution level. The remainder of this paper is organized as follows. Section II reviews previous works concerning low voltage monitoring. Section III presents the IDE4L European project within which this work has been carried out. Section IV describes the low voltage demonstrator designed and deployed within the project. Section V presents the results of the monitoring campaign in reference to smart meters data, while Section VI provides concluding remarks. II. SATE OF THE ART ON LOW VOLTAGE MONITORING The monitoring of the LV networks is becoming more and more important to overcome the challenges of present and future power grids. To this end, metering equipment installed at customers’ premises plays a key role. Traditional metering systems installed in European countries conceive billing and customers’ relation purposes only [17], [18]. However, these technologies cannot meet DSOs’ requirements for distributed measurement analysis and technical management the LV grid [19]. Various approaches have been proposed in recent years to define a new Smart Metering Infrastructure (SMI) [9], [20], taking also in account appliance scheduling [21], data mining for load analysis [22] and Demand Response [23]. SMIs are typically composed of three main blocks[24]: • metering devices at the consumers' premises, traditionally called Smart Meters (SMs) • communication infrastructure between the SMs on the consumers’ premises and the DSO back-end systems • Energy Data Management (EDM) systems of the DSO providing required data to billing and invoicing systems of the supplier and possibly to other systems and to consumers. Within the literature, two approaches can be found to design SMIs blocks. In the first case, the metering infrastructure is conceived as a vertical system deployed by the DSO, while in the second approach the basic idea is to
take advantage from customers owned smart home infrastructures [25]. Other than the architectural approach, the solutions proposed in the literature also make use of a wide range of technologies for the communication between metering devices and the back-end system of the DSO, such as Power Line Communication (PLC) and cellular networks (e.g. GPRS/UMTS) [26]. Despite different approaches, the second generation of smart meters and metering infrastructures is characterized by the use of standard protocols such as the DLMS/COSEM [27], [28]. In addition, they include smart sensors and provide near real-time measures (few minutes timescale). Despite the interest in smart metering, low voltage monitoring literature is quite limited and only some test experiences are found in the literature. In particular, the experimental validation of a voltage control mechanism for LV DNs using the available flexibility of smart devices within one household is presented in [29]. The developed control system only relies on communication between the different smart appliances within one single household, and only uses locally available measurements such as the household supply voltage. An overall architecture for smart grid communication and LV network monitoring, compliant with IEC 61850 standard is introduced by [30]. Within the work, smart meters are used as part of the LV network monitoring system. Within this paper, the SMI is implemented as part of and advanced smart grid architecture, in order to allow the deployment of advanced control algorithms and monitoring features at the LV level. The work represents the evolution of the approach presented in [30], reached by the IDE4L Project. III. IDE4L PROJECT The IDE4L project was focused on the investigation and development of new solutions and architectures to plan, manage and control future DNs. In details, the project covered the integration of Distributed Energy Resources (DERs) in DNs in order to reduce emissions, save energy, reduce network losses, improve network monitoring and controllability, utilize existing networks more efficiently and improve visibility of DERs to transmission system operators and aggregators. The project proposed also innovative smart solutions to design and operate DNs in order to guarantee continuity and quality of electricity supply. The conceptual development of the active DN and automation architecture, as well as the network management, have been the basis of the whole project. The main goal was to create a comprehensive concept and map for DSOs to start deploying and developing the active DN concept, based on existing technologies and solutions, to meet future requirements of DNs. The project has addressed some major challenges of future networks, which are much more complex than today’s passive networks. Indeed, even if the hosting capacity of passive networks can be increased by huge investments, the active network management could dramatically reduce them by applying the IDE4L approach
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and concept. Another aspect taken into consideration in the IDE4L project has been the coordination of network and energy market operations together with customers, which requires extended analysis of electricity system at all levels. Possible conflict of DERs participating in electricity market and distribution network technical constraints can be solved using algorithms and functionalities developed within IDE4L through the smart active network management. A smart automation infrastructure has been designed and realized in order to monitor LV and MV grids, to mitigate the fault effects in the DN. State estimation and load-production forecasting solutions have been implemented as well, in order to provide correct inputs to a power control system that is able to regulate the voltage in the network feeders by controlling several resources, such as controllable PV inverters or on-load tap-changer transformers. Three different demonstrators have been set up by DSOs in three different countries (Italy, Spain and Denmark) to test the integrated automation system and applications developed within the project in real networks. The demonstrators included large and small-scale PV panels, wind turbines, heat pumps and EVs located in urban and rural areas. The proof of the scalability and replicability of the proposed solutions has been provided based on specific key performance indicators computed and compared across the demo sites in order to demonstrate the feasibility of the project that could be applied in the near future all over Europe.
B C
±1.5% ±1.0%
TABLE II. THE ACCURACY CLASSES FOR REACTIVE POWER (SINGLE-PHASE METERS AND POLYPHASE METERS WITH BALANCED LOAD) DEFINED BY IEC 62053-23. Class
Accuracy 0.05*Iref
