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Time in the Sun: The Challenge of High PV Penetration in the German Electric Grid
Abstract and Figures
Energy supply systems are facing significant changes in many countries around the globe. A good example of such a transformation is the German power system, where renewable energy sources (RESs) are now contributing 25% of the power needed to meet electricity demand, compared with 5% only 20 years ago. In particular, photovoltaic (PV) systems have been skyrocketing over the last couple of years. As of September 2012, about 1.2 million PV systems were installed, with a total installed peak capacity of more than 31 GWp. During some hours of 2012, PV already contributed about 40% of the peak power demand. It seems that Germany is well on the way to sourcing a major portion of its energy needs from solar installations. PV must therefore provide a full range of services to system operators so as to replace services provided by conventional bulk power plants.
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... From nearly 1 GW in 2001, solar PV capacity has increased exponentially to 707.5 GW in 2020 [22]. This sudden growth was made possible through incentive programs, declining costs of the mass production of PV panels and the investments in carbon-free power sources [23][24][25][26][27]. Integrating growing levels of PV farms to the electric grid, however, is not a straightforward task given the intermittent nature of the solar irradiance [28]. ...
... According to (25) and separating this equation for the two axes "d" and "q", the stator currents can be written as (26) and (27) for each axis. ...
The move towards a greener energy mix to fight climate change propels investments in converter-interfaced resources such as wind and photovoltaics, energy storage systems and electric vehicles. The ongoing evolution of the power system is occurring at a very fast pace, challenging transmission and distribution system operators to seek solutions that are not only adequate for this moment but also for future scenarios. Ongoing research in the fields of power electronics, power systems and control aims at developing control strategies that will help the energy transition to occur, while keeping a stable, secure and reliable power system. The objective of this paper is to present a critical review of the control strategies developed for grid-connected power converters found in renewable energy systems, energy storage systems and electric vehicles. The impact of grid-connected converters on the stability of power grids is also reviewed, highlighting the promising control strategies for enhancing system stability.
... The increased penetration of RESs and their independent control gives to the system many advantages, such as increased available power, lesser generation from conventional power sources, increased power reliability, etc.. However, the increased penetration of RESs in the feeder may give rise to some power quality issues, in which variation in voltage level due to the intermittent nature of the RES is of major concern, especially today, when many of the loads connected in the distribution system require constant power for their better operation and behave like Constant Power Loads (CPLs) [4][5][6][7]. The power consumed by a CPL remains constant regardless of the voltage at the point of common coupling. ...
Increasing installation of Renewable Energy Sources (RESs) in microgrids and distribution system feeders benefits the power system in many ways, such as increasing power availability and reliability, but they also cause various power quality issues, such as overvoltage and undervoltage, due to their intermittent nature. The sensitive loads, such as Constant Power Load (CPL), are affected by these voltage fluctuations. The approach proposed in this paper is to install a Dynamic Voltage Regulators (DVR) adjacent to the RES to suppress the voltage issue caused by it while leaving the sensitive load operation unharmed. The proposed concept is duly endorsed with analysis and simulations in MATLAB/Simulink environment.
... Standing out is the impact of high photovoltaics (PV) proliferation, but also of other grid-connected devices such as electric vehicle supply equipment (EVSE) [2]. In case of generation outdoing demand locally, bidirectional power flows on different voltage levels as well as voltage rises are the consequences [3]. If the voltage is lifted too much this can lead to voltage band violations, which consist of voltages above or below the admissible limits. ...
The electrical energy system is undergoing major changes due to the necessity for more sustainable energy generation and the following increased integration of novel grid-connected devices, such as inverters or electric vehicle supply equipment. To operate reliably in novel circumstances, as created by the decentralization of generation, power systems usually need grid supportive functions provided by these devices. These functions include control mechanisms such as reactive power dispatch used for voltage control or active power reduction depending on the voltage. As the main contribution of this work, an approach for the development of the detection of misconfigured (e.g., wrongly parameterized control curve) grid devices using solely operational data is proposed. By generating and analyzing operational data of power distribution grids, a Deep Learning-based approach is applied to the detection problem given. An end-to-end framework is used to synthesize and process the data as well as to apply machine learning techniques to it. The results offer insights into the applicability and possible ways to improve the proposed solution and how it could be employed by grid operators. The findings show that DL methods, in contrast to traditional machine learning, can be used for the problem at hand and that the framework developed offers the necessary tools to fine-tune and scale the solution for broader usage.
... With the spread of distributed energy resources connected to the distribution level of the electric system, operating the power grid is becoming an increasingly complex task that requires automated control down to the low voltage grid [1]. To this purpose, measurements are essential to unlock system awareness. ...
The ramping trend of cheap and performant single board computers (SBC) is growingly offering unprecedented opportunities in various domains, taking advantage of the widespread support and flexibility offered by an operating system (OS) environment. Unfortunately, data acquisition systems implemented in an OS environment are traditionally considered not to be suitable for reliable industrial applications. Such a position is supported by the lack of hardware interrupt handling and deterministic control of timed operations. In this study, the authors fill this gap by proposing an innovative and versatile SBC-based open-source platform for CPU-independent data acquisition. The synchronized measurement unit (SMU) is a high-accuracy device able to perform multichannel simultaneous sampling up to 200 kS/s with sub-microsecond synchronization precision to a GPS time reference. It exhibits very low offset and gain errors, with a minimum bandwidth beyond 20 kHz, SNR levels above 90 dB and THD as low as −110 dB. These features make the SMU particularly attractive for the power system domain, where synchronized measurements are increasingly required for the geographically distributed monitoring of grid operating conditions and power quality phenomena. We present the characterization of the SMU in terms of measurement and time synchronization accuracy, proving that this device, while low-cost, guarantees performance compliant with the requirements for synchrophasor-based applications in power systems
... In this type of control scheme, several agents have their own local control policies [61]. This scheme implies that the coordination between agents is done in an automated manner, locally in each bus where it is needed, and without a centralized operator, which may optimize local grid operation [98,116]. Cao et al. [31] used a multi-agent deep RL-based approach for a distribution system with high penetration of PV. ...
This paper presents a review of up-to-date Machine Learning (ML) techniques applied to photovoltaic (PV) systems, with a special focus on deep learning. It examines the use of ML applied to control, islanding detection, management, fault detection and diagnosis, forecasting irradiance and power generation, sizing, and site adaptation in PV systems. The contribution of this work is three fold: first, we review more than 100 research articles, most of them from the last five years, that applied state-of-the-art ML techniques in PV systems; second, we review resources where researchers can find open data-sets, source code, and simulation environments that can be used to test ML algorithms; third, we provide a case study for each of one of the topics with open-source code and data to facilitate researchers interested in learning about these topics to introduce themselves to implementations of up-to-date ML techniques applied to PV systems. Also, we provide some directions, insights, and possibilities for future development.
... Despite the low current rate of PV and battery co-adoption, a growing number of consumers are co-adopting these technologies according to the data from Tracking the Sun (Barbose et al., 2021). Large penetration of PV and battery co-adopters can also be potentially disruptive and impose challenges to the electric grid management such as balancing the supply and demand of the power grid with the presence of decentralized and less predictable consumer electricity importing and exporting behaviors (Appen et al., 2013;Tran et al., 2019). An understanding of how electricity demand is affected by PV and battery co-adoption is central to determining the grid-level and consumer-level (private and external) benefits and costs of co-adoption that may justify government intervention and bear directly on resource planning of utilities and utility regulators (Hill et al., 2012). ...
This study provides an empirical assessment of how adopting battery storage units can change the electricity consumption patterns of PV consumers using individual-consumer level hourly smart meter data in Arizona, United States. We find that on average after adding batteries, PV consumers use more solar electricity to power their houses and send less solar electricity back to the grid. In addition, adding battery storage reduces electricity needed from the grid during system peak hours, helping utilities better flatten the load curves. Most importantly, we find a large degree of heterogeneity in the changes in electricity consumption patterns due to adopting battery storage that are not consistent with engineering or economic principles such as those not maximizing consumers’ economic benefits. Such heterogeneous changes imply that utilities and policymakers need to further study the underlying behavioral reasons in order to maximize the social benefits of battery storage and PV co-adoption.
The rapid development of distributed photovoltaic (PV) systems poses great challenges to the integration capability of distribution networks. Traditionally, the transfer capacity of power distribution equipment is calculated as the maximum loading that prevents overheating under the assumption of extreme weather conditions. Dynamic thermal rating (DTR), which evaluates equipment capacity based on real-time weather conditions, could enhance the transfer capacity to improve distributed PV integration. Through case studies in Texas, Switzerland and China, we show that the application of DTR on power distribution equipment could increase installed PV capacities by 15%-27% and improve net revenues by 4%-27%. We also find that the application of DTR would be positively affected by climate change and is more profitable under the PV policies with higher tariffs for the surplus generation fed into the grid. Compared to energy storage systems, DTR provides a more cost-competitive option to enhance the integration capability of distribution networks.
Modern distribution grids are complex systems that need advanced management for their secure and reliable operation. The Information and Communication Technology domain today offers unprecedented opportunities for the smart design of tools in support of grid operators. This paper presents a new philosophy for the digitalization and automation of distribution grids, based on a modular architecture of microservices implemented via container technology. This architecture enables a service-oriented deployment of the intelligence needed in the Distribution Management Systems, moving beyond the traditional view of monolithic software installations in the control rooms. The proposed architecture unlocks a broad set of possibilities, including cloud-based implementations, extension of legacy systems and fast integration of machine learning-based analytic tools. Moreover, it potentially opens a completely new market of turnkey services for distribution grid management, thus avoiding large upfront investments for grid operators. This paper presents the main concepts and benefits of the proposed philosophy, together with an example of field implementation based on open source components carried out in the context of the European project SOGNO.
This work discusses the technical and economical benefits of different active and reactive power control strategies for grid-connected photovoltaic systems in Germany. The aim of these control strategies is to limit the voltage rise, caused by a high local photovoltaic power feed-in and hence allow additional photovoltaic capacity to be connected to the mains. Autonomous inverter control strategies, which do not require any kind of data communication between the inverter and its environment, as well as an on-load tap changer for distribution transformers, is investigated. The technical and economical assessment of these strategies is derived from 12-month root mean square (rms) simulations, which are based on a real low voltage grid and measured dc power generation values. The results show that the provision of reactive power is an especially effective way to increase the hosting capacity of a low voltage grid for photovoltaic systems.
The installed capacity of photovoltaic systems has recently increased at a much faster rate than the development of grid codes to effectively and efficiently manage high penetrations of PV within the distribution system. In a number of countries, PV penetrations in some regions are now raising growing concerns regarding integration. Management strategies vary considerably by country - some still have an approach that photovoltaic systems should behave as passive as possible while others demand an active participation in grid control. This variety of grid codes also causes challenges in learning from 'best practice'. This paper provides a review of current grid codes in some countries with high PV penetrations. In addition, the paper presents a number of country-specific case studies on different approaches for improved integration of photovoltaic systems in the distribution grid. In particular, we consider integration approaches using active and reactive power control that can reduce or defer expensive grid reinforcement while supporting higher PV penetrations.
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