Analysis of Large Scale PV Systems with Energy Storage to a Utility Grid

With electric distribution network operators experiencing an exponential increase in distributed energy resource connections to the power grid, operational challenges arise attributable to the traditional methods of building distribution feeders. Photovoltaic (PV) solar systems are the major contributor due to recent technological advancements. Though this renewable energy resource is beneficial to human society, unfavorable electrical conditions can arise from the inherit variability of solar energy. Extreme variability of power injection can force excessive operations of voltage regulation equipment and potentially degrade customer voltage quality. If managed and controlled properly, battery energy storage systems installed on a distribution feeder have the ability to compliment solar generation and dampen the negative effects of solar generation. Now that customers are connecting their own generation, the traditional design assumption of load flowing from substation to customer is nullified. This research aims first to capture the maximum amount of generation that can be connected to a distribution feeder. Numerous deployments of generation scenarios are applied on six unique distribution feeders to conclude that hosting capacity is dependent on interconnect location. Then, existing controllers installed on voltage regulation equipment are modeled in detail. High resolution time series analysis driven from historical measurements is conducted on two contrasting feeders with specific PV generator deployments. With the proper modeling of on-load tap changer controls, excessive operations caused by extreme PV generation swings were captured. Several services that battery energy storage systems can provide when connected to an individual distribution feeder with significant PV generation include long term absorption of excessive PV generation, dynamic response to extreme PV generation ramping, and release of stored energy for system peak shaving. A centralized master energy coordinator is proposed with the ability to dispatch the battery system in such a fashion to implement each service throughout consecutive days of operation. This solution was built by integrating load and solar energy forecasting predictions in order to construct an optimum charging and discharging schedule that would maximize the asset’s lifespan. Multiple load and solar generation scenarios including a consecutive three day run is included to verify the robustness of this energy coordinator

Investigation into Photovoltaic Distributed Generation Penetration in the Low Voltage Distribution Network

Significant integration of photovoltaic distributed generation (PVDG) in the low voltage distribution network (LVDN) could potentially pose threats and challenges to the core activity of distribution system operators (DSO), which is to transport electrical energy in a reliable and cost-effective way. The main aim of this research is to investigate the active planning and operation of LVDNs with increased PVDG integration through steady state power system analysis. To address the impacts of voltage profile fluctuation due to power flow modification, this research proposes a probabilistic risk assessment of power quality (PQ) variations and events that may arise due to significant PVDG integration. A Monte Carlo based simulation is applied for the probabilistic risk assessment. This probabilistic approach is used as a tool to assess the likely impacts due to PVDG integration against the extreme-case scenarios. With increased PVDG integration, site overvoltage is a likely impact, whereas voltage unbalance reduces when compared with no or low PVDG penetration cases. This is primarily due to the phase cancellation between the phases. The other aspect of the work highlights the fact that the implementation of existing volumetric charges in conjunction with net-metering can have negative impacts on network operator’s revenue. However, consideration of capacity charges in designing the existing network tariff structure shows incentivising the network operator to perform their core duties under increased integration of PVDG. The site overvoltage issue was also studied and resolved in a novel way, where the active and reactive power of the PVDG inverters at all the PV installed premises were optimally coordinated to increase the PV penetration from 35.7% to 66.7% of the distribution transformer rating. This work further explores how deficiencies in both reactive power control (RPC) and active power control (APC) as separate approaches can be mitigated by suitably combining RPC and APC algorithms. A novel “Q” or “PF” limiter was proposed to restrict frequent switching between the two droop characteristics while ensuring a stabilizing (smoothened) voltage profile in each of the PV installed nodes. This novel approach not only alleviates the voltage fluctuation but also reduces the overall network losses

Spatio-Temporal Probabilistic Voltage Sensitivity Analysis - A Novel Framework for Hosting Capacity Analysis

Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefore, PV Hosting capacity (HC) is being used as a planning tool to determine the maximum PV installation capacity that causes the first voltage violation and above which would require infrastructure upgrades. Traditional methods of HC analysis are computationally complex as they are based on iterative load flow algorithms that require investigation of a large number of scenarios for accurate assessment of PV impacts. This paper first presents a computationally efficient analytical approach to compute the probability distribution of voltage change at a particular node due to random behavior of randomly located multiple distributed PVs. Next, the derived distribution is used to identify voltage violations for various PV penetration levels and subsequently determine the HC of the system without the need to examine multiple scenarios. Results from the proposed spatio-temporal probabilistic voltage sensitivity analysis and the HC are validated via conventional load flow based simulation approach on the IEEE 37 and IEEE 123 node test systems.Comment: 8 pages, 2 figures, discussion adde

Enhancing PV hosting capacity using voltage control and employing dynamic line rating

Photovoltaic (PV) system installation has encouraged to be further expedited to minimize climate change and thus, rooftop solar PV systems have been sparkled in every corner of the world. However, due to technological constraints linked to voltage and currents, the PV hosting capacity has been substantially constrained. Therefore, this paper proposes a competent approach to maximize PV hosting capacity in a low voltage distribution network based on voltage control and dynamic line rating of the cables. Coordinated voltage control is applied with an on-load tap changing transformer, and reactive power compensation and active power curtailment of PV inverters. A case study with probabilistic and deterministic assessments is carried out on a real Sri Lankan network to show how the PV hosting capacity is constrained. The findings revealed the capability of integrated voltage control schemes and dynamic line rating in maximizing hosting capacity. The study is expanded by incorporating the PV rephasing approach in conjunction with the aforementioned control techniques, and the effectiveness of PV-rephasing is clearly demonstrated. When compared to voltage control and conductor static rating, the combined rephasing, voltage control, and DLR yielded a 60% increase in PV hosting capacity

Edge-of-grid voltage control in distribution networks

As the electric power supply systems are undergoing major changes with the integration of renewables, the issues related to voltage regulation and system protection are arising. In this scenario, advanced voltage regulation technologies that provide voltage control at the grid-edge, that is at the low-voltage secondary side of the distribution circuit, have emerged as a potential solution to address the shortcomings of traditional voltage control practices in distribution systems. In this work, these technologies are modeled and algorithms are developed to strategically deploy them, tune their control parameters, and evaluate their voltage regulation performance. A two-stage optimization framework is proposed for optimal placement and real-time control of the low-voltage static var compensators to minimize the energy losses while maintaining the voltage regulation. Integration of high levels of distributed generation such as photovoltaic (PV) systems impacts the voltage regulation by causing steady-state voltage variations and transient voltage fluctuations. This work further develops a procedure to tune the control parameters of PV smart inverters to mitigate these voltage issues. Furthermore, the PV penetration levels in a distribution network can be increased without creating voltage problems by dynamic controlled reactive power absorption at several strategic buses. This concept is modeled and demonstrated in this work. Furthermore, the high levels of PV generation can interfere with the overcurrent protection schemes prevalent in distribution networks. An analytical approach is proposed in this work to estimate the distribution feeder PV accommodation limits with respect to overcurrent protection issues as the impact criteria, without needing to simulate numerous PV screening scenarios to assess the impactElectrical and Computer Engineerin

Digital Twins and Artificial Intelligence for Applications in Electric Power Distribution Systems

As modern electric power distribution systems (MEPDS) continue to grow in complexity, largely due to the ever-increasing penetration of Distributed Energy Resources (DERs), particularly solar photovoltaics (PVs) at the distribution level, there is a need to facilitate advanced operational and management tasks in the system driven by this complexity, especially in systems with high renewable penetration dependent on complex weather phenomena. Digital twins (DTs), or virtual replicas of the system and its assets, enhanced with AI paradigms can add enormous value to tasks performed by regulators, distribution system operators and energy market analysts, thereby providing cognition to the system. DTs of MEPDS assets and the system can be utilized for real-time and faster-than-real-time operational and management task support, planning studies, scenario analysis, data analytics and other distribution system studies. This study leverages DT and AI to enhance DER integration in an MEPDS as well as operational and management (O&M) tasks and distribution system studies based on a system with high PV penetration. DTs have been used to both estimate and predict the behavior of an existing 1 MW plant in Clemson University by developing asset digital twins of the physical system. Solar irradiance, temperature and wind-speed variations in the area have been modeled using physical weather stations located in and around the Clemson region to develop ten virtual weather stations. Finally, DTs of the system along with virtual and physical weather stations are used to both estimate and predict, in short time intervals, the real-time behavior of potential PV plant installations over the region. Ten virtual PV plants and three hybrid PV plants are studied, for enhanced cognition in the system. These physical, hybrid and virtual PV sources enable situational awareness and situational intelligence of real-time PV production in a distribution system

Distribution System Modeling for Assessing Impact of Smart Inverter Capabilities

Photovoltaic (PV) generation is increasingly common throughout power distribution systems. The real power injections and cloud-induced power output fluctuations of this variable resource can cause adverse impacts to the system. These adverse impacts limit PV capacity additions and introduce the need for more advanced distribution system models and mitigation efforts. The IEEE P1547a standard for interconnecting distributed generation has been amended to allow inverter-based generation to actively participate in voltage regulation. However, there is currently no method of choosing the appropriate reactive power response for the PV inverters to prevent voltage issues and benefit distribution system performance. The performance of these smart inverter settings vary based on the objective and system conditions such as load level and solar conditions. This difficulty in choosing a single “out of the box” setting presents the need for more adaptive control functionalities. This thesis assesses the impact of different smart inverter settings on the performance of a distribution feeder in the United States. The use of simulation software to identify relationships between the chosen objective, appropriate settings, and feeder conditions help determine an approach to choosing settings that realize the potential benefits. Due to the limitations of existing reactive power control functions, a new smart inverter capability is proposed that adjusts to changing feeder conditions and offers improved performance