Content uploaded by Jan Von Appen
Author content
All content in this area was uploaded by Jan Von Appen on Mar 20, 2015
Content may be subject to copyright.
A preview of the PDF is not available
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.
Content may be subject to copyright.
... 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.
... 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.
... Besides the capacity of large power plants connected to the transmission network, the installed capacity of smaller distributed generators (DGs), e.g., PV power plants have increased [2]. The decrease in prices has made the PVs more available to the end-users, leading to a high installed capacity in low-voltage networks, which in some countries can be 70% of total PV capacity [3]. Since the price of other low-carbon (LC) technologies, e.g., battery storage [4], is also decreasing, it is expected that the share of LC technologies will be significantly higher than it is today. ...
With the increasing integration of new technologies, power system operators are facing new operational and planning challenges. Most of these changes are caused by power electronics devices of low carbon (LC) units, resulting in more frequent violations of limits defined in the standards, such as the unwanted occurrence of higher-order harmonics. These aspects indicate that an open source tool, capable of analyzing and estimating future impacts of the above-mentioned phenomena and technologies, would be of great benefit. The paper presents the development of a Phyton-based open source tool as an extension of the existing pandapower library. The upgrade includes the capability of balanced and unbalanced harmonic analysis for LC impact assessment. The technical background and mathematical formulations implemented in the newly developed tool are explained in detail and benchmarked against existing commercial tools showing high accuracy, i.e., the median deviation between the results calculated by the developed and the commercial tool is no larger than 0.21% in the worst-case scenario. In addition to verification, the developed tool is used for the analysis of a real-world network with a high share of LC technologies. The source code of the tool is made available for verification and future updates.
... On the other hand, RPF could also be a result of the drastic reduction in the local load demand to the point of excess power in the network which then flows backward [18]. RPF is dangerous in the distribution network as it leads to voltage peaks above acceptable margins [19], and also critically affects the sensitivity and parameters of protective device coordination, hence negatively affecting power quality [20]. ...
Over the past years, the penetration of photovoltaic (PV) systems into the distribution network has experienced significant augmentation as the pressure to reduce greenhouse gas emissions into the atmosphere keeps increasing while the prices of the solar components keep reducing. Despite the benefits PV systems bring to the distribution network, the high penetration of this technology into the distribution network could lead to reverse power flow (RPF) when the PV systems produce more than the local loads require. This RPF could result in the malfunctioning of protective devices and their coordination. This research addresses this problem by utilizing electric vehicles (EVs) that are currently revolutionizing the transport sector. Here, the charging of EVs during the day is intelligently controlled to mitigate RPF as a result of the excess power produced by the PV systems. Resolving RPF is achieved through a control system that measures the power flow on each phase of the main grid substation. If at any instance negative power is detected (reverse power), quantified EVs needing recharge are instantly incorporated into the network for charging through the automatic closure of the power switches of the required number of charging points with EVs whose total power demand equals the amount of reverse power detected. The excess power is hence absorbed and stored by the EVs. The proposed method is tested on an expanded IEEE 13 node test feeder and simulated using ETAP software. Simulation results show the effectiveness of the proposed method in eliminating RPF which occurs from 10:00 am to 12:00 noon by connecting the required number of EVs during that timeframe. The proposed method involves the distribution network operators working in synergy with the transport sector to effectively solve the problem of RPF in the distribution network.
... However, the PV output is very intermittent and unstable as it is a weather-dependent energy source [5,7]. As a result of the intermittency and the instability, increasing PV panel instalments jeopardise the frequency of the alternating current in the electrical grids [8]. For a continuous growth in the PV instalments as well as minimal usage of conventional energy sources in power generation, it is of utter importance for a grid manager to possess information on the energy production of PV panels, hence knowledge on received radiation. ...
Increasing photovoltaic (PV) instalments could affect the stability of the electrical grid as the PV produces weather-dependent electricity. However, prediction of the power output of the PV panels or incoming radiation could help to tackle this problem. It has been concluded within the European Actions “Weather Intelligence for Renewable Energies” framework that more research is needed on short-term energy forecasting using different models, locations and data for a complete overview of all possible scenarios around the world representing all possible meteorological conditions. On the other hand, for the Mediterranean region, there is a need for studies that cover a larger spectrum of forecasting algorithms. This study focuses on forecasting short-term GHI for Kalkanli, Northern Cyprus, while aiming to contribute to ongoing research on developing prediction models by testing different hybrid forecasting algorithms. Three different hybrid models are proposed using convolutional neural network (CNN), long short-term memory (LSTM) and support vector regression (SVR), and the proposed hybrid models are compared with the performance of stand-alone models, i.e. CNN, LSTM and SVR, for the short-term GHI estimation. We present our results with several evaluation metrics and statistical analysis. This is the first time such a study conducted for GHI prediction.
... For example, based on German feed-in tariff law, one of the following two options should be employed in the PV units with an active power of less than 30 kWp: (1) restricting their reactive power output to 70% of their installed capacity and (2) equipping with a remote control interface to enable the DSO to send the required temporal power reduction signals. On the other hand, PV units with active power more than 30 kWp must be controlled remotely [19]. ...
In the power system, energy management systems (EMSs) balance the energy sources and energy consumption at the minimum possible cost. Unlike the EMS, which is basically an energy-focused unit, since the 1970s the distribution management system (DMS) has been developed to manage the distribution operations. One of the most important requirements for a smart grid transition is the DMS, which provides the basis for safe and efficient modeling, operation, and direct field activities. The application functions that provide network model analysis and capability can be the heart of DMS. The DMS functions can be categorized into three groups: system monitoring, decision support, and control actions. The hardware and software designs of the DMS, as well as its associated characteristics and interaction with other subsystems in a power grid, are discussed. Some new requirements and functions for operating and controlling the system are proposed to be integrated into the DMS.
Renewable energy is one of the most abundant energies in our planet. In order to satisfy the world demand of electrical energy, solar and wind energy may be used. Identical to all other types of power generation plants, the integration of these renewable energy sources in smart power grid has an impact on its operation. Thus, when the electrical power is injected into the power grid by these energy sources, the system electrical parameters must be well monitored for synchronization purpose. This can be accomplished with the aid of synchro-phasors measurement units. The phase angle of the utility is a critical parameter for the operation of power devices feeding power into the grid such as PV and wind energy inverters. There are many techniques to obtain the grid phase angle such as the zero-crossing detection and the orthogonal phase locked loop. This research work discusses the use of PMUs (Phasor Measurement Unit) for providing this important parameter to system synchronization in the case of high penetration of solar or wind energy in the power grid.
India is country with abundant solar energy availability. The annual solar energy output exceeds the total energy output of India's non renewable energy sources. As increasing installation of renewable energy sources into the grid. The fluctuations of power based on operating climate conditions like solar insulation and temperature is highly depends as it is not possible to limit such installations with time the penetration level of renewable sources will increase to meet demand with green energy. This paper proposed a flexibly power point tracking (FPPT) control of active power in photovoltaic system to achieve reserve capacity with Power Limiting Control (PLC) which will provide high stability to existing system without overloading it thus a proper integration to the grid and to mitigate adverse negative effects of high level integrations are possible with modified grid codes in stand of replacement of existing grid . Matlab/Simulink software package is used to make the model and effectiveness of the propose system is tested with Simulink environment..
The inclusion of photovoltaic systems in distribution networks has raised the importance of the prediction of photovoltaic power for safe planning and operation. Artificial neural networks (ANNs) have been used in this task due to its capacity of representing nonlinearities. However, the profile of the data used may affect the forecast accuracy. This manuscript reports on a comparative analysis of the performance of four neural network models for photovoltaic power forecast regarding their input dataset. Four sets composed of photovoltaic power data (local measurements) and external weather data (remote measurements) were used, and the networks were validated through actual measurements from a photovoltaic micro plant. The ANN that dealt with only weather data showed a good level of accuracy, being a useful tool for the feasibility analysis of new photovoltaic projects. In addition, the approach that used only photovoltaic power data has excelled and can be used in electric sector companies.
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.
Progress in Photovoltaics: Research and Applications, 27th EU PVSEC, special issue, frankfurt, germany, 2012. t. stetz, f. marten, and m. Braun, "improved low voltage grid-integration of photovoltaic systems in germany
- Kraiczy
- S Braun
- Schmidt
t. stetz, m. Kraiczy, m. Braun, and s. schmidt, "technical
and economical assessment of voltage control strategies in
distribution grids," Progress in Photovoltaics: Research and
Applications, 27th EU PVSEC, special issue, frankfurt,
germany, 2012.
t. stetz, f. marten, and m. Braun, "improved low voltage
grid-integration of photovoltaic systems in germany," IEEE
Trans. Sustainable Energy, vol. 3, no. 4, 2012.
t. Bülo, D. mende, g. Bettenwort, D. geibel, t. Degner,
a. seibel, J. p. da costa, W. Kruschel, K. Boldt, f. sutter,
t. Hug, B. Engel, and p. Zacharias, "Voltage control in active, intelligent distribution network," in Proc. 27th European Photovoltaic Solar Energy Conf., frankfurt, germany,
2012, pp. 4076-4082.