Photovoltaic Penetration Research Articles

Impact of High PV Penetration on Transient Stability — a Case Study on the U.S. ERCOT System

This study was performed to assess the impact of high photovoltaic (PV) penetration on transient stability using a series of hypothetical models of the ERCOT system. This was done by calculating the critical clearing time (CCT) when faulting various busses. Varying levels of PV penetration were used to study the system transient stability. For each case 15% wind penetration was also included. It was found that under the PV volt/Var control with plant-level GE SolarControl settings, PV penetration at lower level can slightly improve the transient stability in the ERCOT system model. However, at approximately 54% penetration of renewables (39% PV and 15% wind), transient stability starts to show declining trend. This value has slight variance depending on PV distribution.

Voltage assessment of distribution network with large penetration of PVs by probabilistic approach

In this paper, the voltage profile in the Japanese distribution system with large penetration of photovoltaics (PVs) is estimated probabilistically by Monte-Carlo simulation. PV outputs and load demands are given as probability distributions with certain correlation factors.

A Comparative Study of Optimal PV Allocation in a Distribution Network Using Evolutionary Algorithms

The growing distributed energy resource (DER) penetration into distribution networks, such as through residential and commercial photovoltaics (PV), has emerged through a transition from passive to active networks, which takes the complexity of planning and operations to the next level. Optimal PV allocation (sizing and location) is challenging because it involves mixed-integer non-linear programming with three-phase non-linear unbalanced power flow equations. Meta-heuristic algorithms have proven their effectiveness in many complex engineering problems. Thus, in this study, we propose to achieve optimal PV allocation by using several basic evolutionary algorithms (EAs), particle swarm optimization (PSO), artificial bee colony (ABC), differential evolution (DE), and their variants, all of which are applied for a study of their performance levels. Two modified unbalanced IEEE test feeders (13 and 37 bus) are developed to evaluate these performance levels, with two objectives: one is to maximize PV penetration, and the other is to minimize the voltage deviation from 1.0 p.u. To handle the computational burden of the sequential power flow and unbalanced network, we adopt an efficient iterative load flow algorithm instead of the commonly used and yet highly simplified forward–backward sweep method. A comparative study of these basic EAs shows their general success in finding a near-optimal solution, except in the case of the DE, which is known for solving continuous optimization problems efficiently. From experiments run 30 times, it is observed that PSO-related algorithms are more efficient and robust in the maximum PV penetration case, while ABC-related algorithms are more efficient and robust in the minimum voltage deviation case.

Towards carbon neutrality: A multi-objective optimization model for photovoltaics systems installation planning

Increasing photovoltaic (PV) installed capacity is considered a primary way to achieve carbon neutrality targets. However, the rapid development has led to the PV market saturation in some areas, and solar curtailment has even occurred due to the oversupply. With more demand for PV installation in the future, the question of where to efficiently deploy PV systems to both meet the increasing PV electricity demand and alleviate the mismatch between PV supply and local demand becomes relevant. To explore these issues, this paper proposes an integrated framework for planning the PV installed capacity allocation. The framework can be decomposed into two stages: at the optimization stage, a multi-objective optimization (MOO) model is proposed, integrating the minimization of mismatch between PV supply and local demand as an additional objective along with the traditional economic and environmental profits maximization objective; and at the evaluation stage, an entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is employed to make the decision of the PV allocation scheme. By applying this integrated model to the Chinese PV deployment, the results reveal that the consideration of the match between PV supply and local demand has a direct influence on the PV installation layout. More than 50% of the PV systems are expected to be in areas with higher demand and higher profits, rather than the areas with high solar irradiance but lower demand. Distributed PV installations are expected to account for 60% of the total installed capacity. The implementation of this PV installation planning is estimated to result in a reduction of 1036 Mt CO2 emission, a 14.2% PV penetration rate, and 566 billion CNY total profits, making it an attractive and feasible instrument for countries striving towards carbon neutrality goals.

Methodology for the formulation of medium voltage representative networks in three DSO areas

In the 2020s, in line with international trends, a rapidly increasing photovoltaic penetration is expected in Hungary. These decentralized electricity sources are typically connected to the low and medium voltage distribution network, affecting their operation. The spread of different output power connection demands the development of the network infrastructure. The development directions and opportunities can be examined with software simulation, so the formulation of reference networks is required. In order to get valid reference networks, clustering of real feeders can be a solution. When the clusters and the values of the variables that describe the clusters are defined, the networks can be implemented in simulation software. In this paper, the clustering process of Hungarian distribution networks, the determination of the optimal cluster number, and the reference networks are all presented, on which the effects of the growing photovoltaic penetration in the Hungarian medium voltage distribution network system can be simulated

Impact of OLTC equipped transformer operation on PV installation in urban distribution network

Presented paper addresses the problem of proper large-scale integration of photovoltaic (PV) systems in urban area distribution network (DN). A methodology for minimization of annual energy losses in DN by optimal placement of PV systems, which simultaneously considers rooftop PV potential and time dependent network operation, is presented. Optimal reactive power generation of PV systems and optimal setting of on-load tap changer (OLTC) equipped transformer in secondary substation are determined as well. Furthermore, proposed methodology enables evaluation of the impact of OLTC equipped transformer on the share of PV installation that urban DN can accommodate. Proposed methodology is based on the optimization tool called differential evolution, with the objective function set to minimize network’s annual energy losses, while preventing the voltage violations and thermal overloading of lines. Results of the case study performed on a real urban low voltage distribution network, with consideration of different scenarios of OLTC operation are presented. The results indicate that simultaneous consideration of chosen variables yields greater benefits to DN operation in terms of reduction of annual energy losses and greater PV penetration.

Integration method of large-scale photovoltaic system in distribution network based on improved multi-objective TLBO algorithm

The increasing integration of distributed generations brings great challenges to the power grid. In this paper, a distributed photovoltaic (PV) integration methodology in distribution network is established for large-scale PV penetration. Firstly, a PV integration model was formulated with the aim of maximizing PV integration capacity and enhancing the voltage profile. Specially, the PV large-scale integration model for county-wide promotion is proposed by considering various typical integration scenarios. Additionally, a novel improved multi-objective Teaching-Learning based optimization (TLBO) algorithm, namely, IM-TLBO, was proposed to seek an optimal Pareto front of the PV integration model. The IM-TLBO algorithm innovatively incorporates the elite reverse learning search strategy to enhance exploration in the solution space. Moreover, the differentiated teaching guided by optimal individual and central location is employed to improve the efficiency of the “teaching” process. Meanwhile, a cyclic crowded sort deletion based on crowding distance is developed to enhance the diversity of elite individuals and the distribution characteristics of the Pareto Frontier. Finally, the performance of IM-TLBO is tested in benchmark functions. Also, a simulation case in IEEE 33 bus system is performed to verify the proposed PV integration method. It is observed that the proposed method in this paper can not only realize the overall optimal integration of roof distributed PV, but also improve voltage profile. The results of IM-TLBO are compared to other classical algorithms, and it is shown that IM-TLBO outperformed them in terms of convergence, distribution and diversity.

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Given the increasing interests in carbon neutrality due to climate change, photovoltaic (PV)‐based microgrid has become an important research topic worldwide. Typically, high PV penetration without proper control schemes causes power quality issues such as voltage or frequency violation, resulting in the limited PV hosting capacity. Reactive and active power support from the PV is effective to solve the issues, however, it is a critical challenge to efficiently contribute to the stabilizing controls under the inverter capacity constraint. Recent studies have applied smart inverters, equipped with fixed active and reactive power control reserves, for dynamic voltage and frequency support. In this paper, we proposed a control strategy in which the control reserves for voltage and frequency support are flexibly adjusted using virtual power factor (VPF) to improve the power quality with reducing active power curtailment. The effectiveness of the proposed Q‐V/P‐f control is verified through numerical simulations using a microgrid model developed in MATLAB/Simulink platform. It was observed through the simulation that the proposed method contributed to mitigating voltage and frequency fluctuation with satisfying the inverter capacity constraint. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Multi-objective day-ahead scheduling of cascade hydropower-photovoltaic complementary system with pumping installation

Cascade hydropower (CHP) is a promising resource to compensate for the randomness and variability of photovoltaic (PV) power generation. However, the flexibility of CHP might become insufficient due to increasing PV penetration. By constructing pump units to transform into mixed pumped-storage plants, the regulating flexibility can be further improved. Nevertheless, since the pump is usually installed between two adjacent reservoirs, the hydraulic coupling between CHP and pumps is strengthened, and it challenges the coordinated power dispatch of the CHP-PV complementary system with pumping installation. In this paper, a day-ahead dispatch strategy for the complementary system is established based on multi-objective stochastic optimization, which aims to reduce the variance of residual load, output deviation of complementary system and PV curtailment caused by PV uncertainties simultaneously. The normalized normal constraint method is employed to generate evenly distributed points on the Pareto frontier, which can present a fair tradeoff among multi-objectives. Hence, subjectivity arising from weight assignment can be eliminated and comprehensive decision support can be provided for the dispatch of the complementary system. Simulation studies are conducted on a real system in southwest China and the effectiveness of the proposed approach is validated. Compared to the case without pumping installation, the capability to compensate for PV fluctuations and the peak-shaving performance can be improved.

Cost accounting and economic competitiveness evaluation of photovoltaic power generation in China —— based on the system levelized cost of electricity

Accelerating the penetration of photovoltaics (PV) oriented renewables is a vital mainstay in climate mitigation. Along with continuous growth of PV generation in the power system, PV costs have been rapidly declining. Levelized cost of electricity (LCOE) is commonly applied to cost accounting of energy, while neglecting the specific cost compositions of PV leads to an overly optimistic scenario. By integrating grid costs and balancing costs into conventional LCOE framework, a System LCOE (S-LCOE) model was constructed to evaluate the economic feasibility of PV generation, more accurately. The results revealed that all provincial S-LCOE of China's PV is currently higher than local desulfurized coal electricity price (DCEP). Based on the comparative analysis of provincial S-LCOE and DCEP, four regions with diverse economic competitiveness were identified. PV projects in Region I and Region II are considered to be potentially competitive comparing to thermal generation, in terms of environmental benefits and S-LCOE, especially in Guangdong, Jilin, and Hainan. Furthermore, by simulating the descent trajectory of S-LCOE, we estimate that China will achieve S-LCOE equal to DCEP in Region I as early as 2023, while it will be postponed to 2042 in Region Ⅳ at the latest, depending on different S-LCOE descent rates.

Robust microgrids for distribution systems with high solar photovoltaic penetration

Robust microgrids for distribution systems with high solar photovoltaic penetration

Analysis of Financial Penalties for Low Power Factor in Distribution Systems with High Penetration of Photovoltaics

Analysis of Financial Penalties for Low Power Factor in Distribution Systems with High Penetration of Photovoltaics

Utilisation of electric vehicles and battery energy storage systems for the enhancement of PV hosting capacity in a distribution network

To foster decarbonisation of the transportation sector, there is a growing widespread global adoption of electric vehicles (EVs) as a clean, environmentally friendly alternative to fossil-fuel-dependent internal combustion engine vehicles (ICEV). This has required the electrical power system to distribute power to EV charging stations. In addition, battery energy storage systems (BESSs) have also been deployed to improve network resilience. Both EVs and BESSs on distribution networks (DNs) may be charged using photovoltaic (PV) resources. Subsequently, huge numbers of PV plants have been installed globally over the past decade. With excessive PV penetration into the distribution network (DN), the consequences are risks of operational constraint violations such as over-voltages, feeder line congestion, protection maloperation and high harmonics. This requires limiting the amount of installed PV to alleviate these risks. The maximum amount of PV which can be integrated into the DN without violating these network operational limits is the PV hosting capacity (PVHC). This paper proposes models for quantifying the impacts of EVs and BESSs on the PV hosting capacity of DNs using the stochastic particle swarm and gradient descent algorithm (PSO-GD). The simulation results of case studies have shown that the proposed method is accurate, fast, and efficient.

Mitigation of High Photovoltaic Penetration Effects in Electrical Grid Systems Using a Hybrid Particle Swarm and Grey Wolf Optimization Approach

The rising integration of photovoltaic (PV) systems into electrical grids has introduced significant challenges allied with voltage stability, power quality, and grid reliability, particularly beneath high PV penetration scenarios. This work presents a hybrid optimization approach combining particle swarm optimization (PSO) and grey wolf optimization (GWO) to mitigate these challenges effectively. The hybrid PSO–GWO method is not only applied to optimize the position and sizing of PV systems, but also the configuration of grid‐supportive devices like static synchronous compensators (STATCOMs), in Institute of Electrical and Electronics Institute (IEEE) 14‐test bus system. The proposed hybrid system led to a 42.2% power loss reduction, from 18.5 to 10.7 MW effectively enhancing efficiency of the grid, improves voltage profiles, all bus voltages maintained with in the acceptable range of 0.95–1.05 p.u. The study also identified optimal locations for PV units, with placements at bus 3, 6, and 9, where PV sizes were adjusted to 10, 12, and 8 MW, respectively. Additionally, the optimal placement of STATCOMs at bus 4, 7, and 10 provided reactive power support of up to 9 MVAR, further enhancing system stability. The findings suggest that the hybrid PSO–GWO optimization technique is a promising tool for managing the complexities of high PV penetration in modern electrical grids, ensuring proficient and reliable grid operation.

Analysis of fast frequency control using battery energy storage systems in mitigating impact of photovoltaic penetration in Ethiopia–Kenya HVDC link

The high penetration of photovoltaic (PV) in power grids typically leads to the displacement of traditional synchronous generators (SGs). However, with a high penetration of PV, fewer SGs are running, and the sharing of responsibility to control the system frequency is reduced and easily exacerbates the problem of reduced inertia response in the power system. This can increase frequency deviation when there is a load-generation imbalance or unexpected disturbances. The limited amount of inertial response from the PV generation means that it cannot provide the same frequency support as SGs. Therefore, this paper suggests a fast frequency control (FFC) technique for the battery energy storage system (BESS) to reduce the instantaneous frequency deviation (IFD) in the Ethiopian grid. The authors specifically provide knowledge of the modeling of droop-type controlled BESS, which can provide additional damping, enhance the inertial ability of the system, and reduce IFD. The simulation results indicate the effectiveness of BESS in mitigating the adverse inertial impact of PV and meeting the necessary grid requirement. The proposed method was tested on the Ethiopian power system model through simulations by using DIgSILENT simulation software. To validate the model, transient frequency simulation studies are performed for various fault conditions, and comparisons are made with and without BESS for different levels of PV penetration.

Pilot Protection of a Distribution Network with Distributed Generators Based on 5G and Dynamic Time Warping Considering Cosine Transform

The application of 5G-based communication for pilot protection in a distribution network with distributed generators is becoming increasingly widespread, but the existence of a 5G communication transmission data delay adversely affects the rapidity and reliability of the pilot protection based on the principle of the traditional dynamic time warping distance (DTW) algorithm. Therefore, to address this problem, and according to the difference in fault currents between distributed generators and synchronous machines, a new scheme of pilot protection based on the principle of an improved DTW is proposed. The scheme firstly performs cosine transform on the fault current sequence, and then it normalizes the DTW value. Finally, the proposed scheme is verified via simulation. The simulation results show that, compared with the traditional DTW, the proposed algorithm has better anti-delay characteristics and a stronger anti-interference ability, and the scheme can quickly and reliably identify in-zone and out-of-area faults with strong noise resistance. Further, the action times for a single-phase ground fault, two-phase ground fault, two-phase-to-phase fault, and three-phase short-circuit fault were reduced by 2.9 ms, 4.54 ms, 5.81 ms, and 5.89 ms, respectively. In addition, it is also sui for a distribution network with a high wind and photovoltaic penetration rate.

Optimal sizing and techno-economic analysis of the hybrid PV-battery-cooling storage system for commercial buildings in China

Energy systems for flexibility in buildings are hybrid, primarily including rooftop photovoltaics (PV), cooling storage, and battery. Considering their techno-economic patterns, this research establishes an optimization model to determine the optimal technology portfolio and financial advantages of PV-battery-cooling storage systems for commercial buildings in China. The analysis of all cases indicates that cooling storage outperforms batteries in economic benefits, suggesting the prioritization of cooling storage installation. Once the optimal cooling storage rate is exceeded, it is advisable to proceed with batteries. Meanwhile, PV integration significantly enhances the system efficiency and promotes battery utilization. For example, a 40% PV penetration combined with a 0.006 $/(a·kWhe) energy storage investment results in an impressive 27.3% cost reduction in a Beijing mall, while the optimal cooling storage rate decreases from 55% to 40%. Furthermore, the study emphasizes the impact of tariff patterns and electricity demand on the economic feasibility of hybrid energy systems. The museum's substantial annual cooling requirements and nighttime loads make cooling storage favorable, with PV less suitable than the mall and office. Notably, cities like Beijing, Shanghai, Chongqing, and Guangzhou exhibit considerable peak-to-valley tariff differences, yielding higher economic benefits ranging from 23% to 27%. Finally, as battery costs decline and electricity price becomes more volatile, the battery would gradually replace cooling storage, especially when battery cost drops from 150 $/kWh to 70 $/kWh.

RELAY COORDINATION PLANNING FOR HIGH PHOTOVOLTAIC PENETRATION USING PRESET-TIME METHOD

In light of the advancement and technological development, electricity has become the main component of all areas of life. Photovoltaic (PV) systems are widely used within distribution networks. Despite all the advantages that PV possesses, it has some effects on the protection system. One of the most essential effects caused by PV is an increase in the relay operating time (ROT) of the backup protection relay during faults. Many studies have focused on improving the coordination of protection relays at high PV penetration, either by using current limiters or modifying the characteristics of the protection curves. However, they require a high cost and advanced relay. Therefore, the Preset-Time method is introduced in this study to shorten the ROT of the backup protection relay within the radial distribution networks which contributes to accelerating the removal of faults. The proposed method is tested on the Iraqi distribution network and is simulated using ETAP 19 software. The performance of the Preset-Time method is evaluated during the change in penetration levels. To validate the preset time method, its results are compared to the conventional method and the Max PSM method. From the results obtained by the Preset-Time method, the highest percentage of reduction in ROT was 33.20% and 29.23% compared to the conventional and the Max PSM methods, respectively.

Power stability control of wind-PV-battery AC microgrid based on two-parameters fuzzy VSG

Virtual synchronous generator (VSG) control addresses the issue of decreasing microgrid standby inertia caused by the rise in wind turbines and photovoltaic (PV) penetration. However, various types of perturbations occur frequently making the traditional constant parameter VSG control unable to meet the system performance requirements, and thus a two-parameters fuzzy VSG control is proposed to ensure that microgrid inertia and damping. Firstly, the device-level control of each generation unit in the microgrid is designed based on the wind-PV-battery alternating current (AC) microgrid architecture. Secondly, fuzzy VSG control uses fuzzy rules written in plain language to represent the relationship between the main VSG factors and the power and frequency. Then, the influence of virtual inertia and damping coefficient on the dynamic performance of the system is analyzed through the theory of small-signal model, and a reasonable variation range of VSG parameters are given. Finally, the simulation model of wind-PV-battery AC microgrid is built in MATLAB/Simulink, and compared with other improved VSG control strategies, the fuzzy VSG control proposed in this paper has better dynamic performance and safety stability. This research emphasizes the practicality and importance of utilizing fuzzy control to adjust VSG techniques for developing microgrid configurations incorporating more renewable energy sources to guarantee the reliability and efficiency of microgrid.

Evaluation of Photovoltaic Penetration on System Grid with Minimum Loading Approach

The Indonesian government has also set a target to increase the contribution of renewable energy in the national energy mix to 23% by 2025 and 31% by 2050. In this paper, an analysis of Maximum PV Capacity was used on the transmission network with a minimum loading approach using the Power Factory15.1 simulation. From the simulation that has been done, it can be seen that the placement of two PV location points gets better results than the placement of one PV location point. This can be seen that the feeder load for PV location point of 74.3%, while for two PV location points of 35.8% which value is still within safe limits, but for two PV location points get better results. PV trip state frequency values obtained for single location point and two PV location points get a result of 2% of 50 Hz which is still within safe limits.