Photovoltaic Penetration Research Articles

Studies on effective solar photovoltaic integration in distribution network with a blend of Monte Carlo simulation and artificial hummingbird algorithm

AbstractIn this paper, the two level stochastic optimisation approach has been suggested. In the lower level, the probability distribution functions (pdfs) for bus voltages and branch currents have been determined using the Monte Carlo simulation (MCS) to be employed in chance‐constrained probabilistic optimisation by taking into account solar radiation and power consumption uncertainties in the distribution networks (DNs). In the upper level, artificial hummingbird algorithm (AHA) handles the expected power loss minimisation subjected to chance constraints, which are related to bus voltages and branch currents, by optimising photovoltaic (PV) system capacities. This research examines the effect of uncertainties in PV system performing under diverse solar radiation and varying PV penetration level scenarios on expected power losses with stochastic DN limits. The stochastic optimisation approach has been compared with the deterministic method for observing the efficiency with optimal power usage. This research improves the knowledge base for optimal PV installation in DN by combining AHA with MCS and emphasising chance‐constrained methods. To indicate the efficacy of proposed strategy, the optimisation outcomes are tested utilising MCS under various uncertainty circumstances and DN parameters are assessed in terms of probabilities of exceeding limitations. The results are compared with the application of firefly algorithm (FA) using stochastic assessment and simulations. The simulation results show that the AHA technique outperforms the FA method in terms of effectively minimising power losses with less simulation time.

Grand challenges of wind energy science – meeting the needs and services of the power system

Abstract. The share of wind power in power systems is increasing dramatically, and this is happening in parallel with increased penetration of solar photovoltaics, storage, other inverter-based technologies, and electrification of other sectors. Recognising the fundamental objective of power systems, maintaining supply–demand balance reliably at the lowest cost, and integrating all these technologies are significant research challenges that are driving radical changes to planning and operations of power systems globally. In this changing environment, wind power can maximise its long-term value to the power system by balancing the needs it imposes on the power system with its contribution to addressing these needs with services. A needs and services paradigm is adopted here to highlight these research challenges, which should also be guided by a balanced approach, concentrating on its advantages over competitors. The research challenges within the wind technology itself are many and varied, with control and coordination internally being a focal point in parallel with a strong recommendation for a holistic approach targeted at where wind has an advantage over its competitors and in coordination with research into other technologies such as storage, power electronics, and power systems.

Stochastic optimal harmonic suppression with permissible photovoltaic penetration level for grid-linked systems using Monte Carlo-based hybrid NSGA2-MOPSO

Stochastic optimal harmonic suppression with permissible photovoltaic penetration level for grid-linked systems using Monte Carlo-based hybrid NSGA2-MOPSO

Integrating renewable energy communities and Italian UVAM project through renewable hydrogen chain

Renewable energy communities (RECs) in Italy could play an important role in increasing the stock of electric renewable generation in the coming years. Their impact on the electric grid could be non-negligible. At the same time with increased electric generation from renewables, a greater need for electric national grid balancing is expected, preferably based on zero-emission energy storage. Based on currently existing entities in Italian regulation framework (i.e. REC and UVAM project), the present work proposes an original business model to create a storage of dispatchable renewable hydrogen to be used for balancing National electric grid. Hydrogen production is from excess of renewables in RECs constituted in the same area. UVAM project allows to access the ancillary services market with the minimum capacity of 1 MW that appears appropriate to the proposed scenario. Based on current technical-economic constraints of the technologies involved (electrolysis and both fuel cell and internal combustion engine fed by hydrogen), proposed business model is not day-present economic feasible: the return on investment is never positive. The cost forecasts available for 2035 indicate that the business model will be likely sustainable, with a net present value becoming positive for configurations with more than 3000 people involved in the RECs, with a photovoltaic penetration condition of 1.8 kWp/capita. This research work suggests an original business model for managers of RECs with an excess of renewables generation.

Optimal EV Charging and PV Siting in Prosumers towards Loss Reduction and Voltage Profile Improvement in Distribution Networks

In this paper, the problem of simultaneous charging of Electrical Vehicles (EVs) in distribution networks (DNs) is examined in order to depict congestion issues, increased power losses, and voltage constraint violations. To this end, this paper proposes an optimal EV charging schedule in order to allocate the charging of EVs in non-overlapping time slots, aiming to avoid overloading conditions that could stress the DN operation. The problem is structured as a linear optimization problem in GAMS, and the linear Distflow is utilized for the power flow analysis required. The proposed approach is compared to the one where EV charging is not optimally scheduled and each EV is expected to start charging upon its arrival at the residential charging spot. Moreover, the analysis is extended to examine the optimal siting of small-sized residential Photovoltaic (PV) systems in order to provide further relief to the DN. A mixed-integer quadratic optimization model was formed to integrate the PV siting into the optimization problem as an additional optimization variable and is compared to a heuristic-based approach for determining the sites for PV installation. The proposed methodology has been applied in a typical low-voltage (LV) DN as a case study, including real power demand data for the residences and technical characteristics for the EVs. The results indicate that both the DN power losses and the voltage profile are further improved in regard to the heuristic-based approach, and the simultaneously scheduled penetration of EVs and PVs could yield up to a 66.3% power loss reduction.

Real-Time Power Regulation of Flexible User-Side Resources in Distribution Networks via Dual Ascent Method

Flexible user-side resources are of great potential in providing power regulation so as to effectively address the challenges of reverse power flow and overvoltage issues in distribution networks characterized by high photovoltaic (PV) penetration. However, existing distributed algorithms typically implement control signals after the convergence of the algorithms, making it difficult to track frequent and rapid fluctuations in PV power outputs in real time. Given this background, an online-distributed control algorithm for the real-time power regulation of flexible user-side resources is proposed in this paper. The objective of the established control model is to minimize network losses by dynamically adjusting active power outputs of flexible user-side resources and reactive power outputs of PV inverters while respecting branch power flow and voltage magnitude constraints. Furthermore, by deconstructing the centralized problem into a primal–dual one, a distributed control strategy based on the dual ascent method is implemented. With the proposed method, agents can achieve global optimality by exchanging limited information with their neighbors. The simulation results verify the good balance between economic efficiency and voltage control performance of the proposed method.

Adaptive reactive power control for voltage rise mitigation on distribution network with high photovoltaic penetration

This research addresses the challenge of voltage rise on low voltage distribution networks with high photovoltaic penetration. The proliferation of distributed generators, particularly small-scale PV systems, has raised concerns about voltage stability and power quality in these networks. Existing reactive power control techniques, such as fixed power factor and voltage-based methods (Q(V)), have limitations in effectively mitigating voltage rise while considering load variations and network sensitivity. To overcome these limitations, an adaptive reactive power control technique is proposed in this research. The technique combines both PV active power injection and network voltage considerations in real-time to dynamically adjust reactive power output. Unlike traditional methods, which directly link reactive power reference to PV active power or voltage, the adaptive technique calculates the change in reactive power reference (ΔQ) based on both factors. This dynamic approach enables more responsive and accurate voltage regulation. The effectiveness of the adaptive technique is demonstrated through MATLAB simulations on a representative low voltage distribution network. The results show that the adaptive technique outperforms existing methods, providing better voltage regulation and reduced losses. The technique's adaptability to different scenarios and variations is also highlighted. However, it is noted that the adaptive technique may have a slightly slower response time compared to existing methods due to its dynamic nature.

GA and PSO Techniques Based Optimal Tuning of Power System Stabilizers in a PV Integrated Power Network

This paper involves the employment of Genetic Algorithm (GA) and Particle Swam Optimization (PSO) methods for the optimal tuning of gain and time constant parameters of power system stabilizers in a power network with integrated Photovoltaic (PV) energy conversion systems. To examine the critical modes of the PV integrated system and the impact of the PV integration on various modes of oscillations, eigenvalue analysis is carried out under various PV penetration levels. The investigations indicate that the rotor angle oscillations following a disturbance have less damping as the PV penetration level increases. To enhance the small signal stability, the excitation systems are provided with the signal from power system stabilizers (PSS). The gain and time constant parameters of the PSS are tuned utilizing the GA and PSO methods and compared with the conventional proportional-integral (PI) PSS. The preliminary investigations on the PV integrated standard IEEE power system reveal that the PSO and GA-based PSS are significantly better than the PI-PSS, and further, PSO-PSS is marginally more effective than the GA-PSS in damping the rotor angle oscillations.

Multi-objective parameter design and economic analysis of VSG-controlled hybrid energy systems in islanded grids

Photovoltaic (PV) systems offer cost-effective power solutions for outlying islands but often compromise system stability due to reduced inertia. This study introduces a Virtual Synchronous Generator (VSG) control strategy, integrated with Energy Storage Systems (ESS) and PV, to enhance system inertia. By optimizing coordination between these energy sources, the proposed method mitigates oscillations and improves grid stability. However, PV-VSG systems are generally not favored by energy providers due to the requirement for pre-curtailment of power output. To address this, the paper proposes a parameter design method for VSG control of ESS and PV, utilizing multi-objective genetic algorithm (MOGA) optimization to simultaneously increase the frequency nadir and minimize the settling time after disturbances. Additionally, an adaptive curtailment decision and parameter design method based on artificial neural networks is introduced to enhance the feasibility of PV-VSG systems by reducing PV pre-curtailment and prioritizing PV power release and ESS charging during frequency oscillations. Real data from the Penghu Archipelago in Taiwan are used to build a dynamic model in DIgSILENT, enabling interaction with MOGA. The Value at Risk (VaR) method with dual stochastic variables is employed to assess the allowable PV installed capacity. The results show that when VaR is set at 1%, the proposed PV-VSG method can increase PV penetration by 57.5% compared to scenarios without VSG. Furthermore, compared to traditional PV-VSG methods, the proposed approach achieves a 16.8% increase in PV penetration and reduces annual PV curtailment by 25 MWh. This study also evaluates the economic impact of planners choosing different risk levels, offering valuable insights for grid development in remote or island regions.

An Active Distribution Network Voltage Optimization Method Based on Source-Network-Load-Storage Coordination and Interaction

In response to global energy, environment, and climate concerns, distributed photovoltaic (PV) power generation has seen rapid growth. However, the intermittent and uncertain nature of PVs can cause voltage fluctuations in distribution systems, threatening their stability. To address this challenge, this paper proposes an active distribution network voltage optimization method, of which the main contribution is the development of a comprehensive voltage optimization strategy that integrates day-ahead prediction and real-time adjustment, significantly enhancing the stability and efficiency of distribution networks with high PV penetration. In the day-ahead prediction stage, the forecast scenarios of load and PV output guide network reconfiguration for improved voltage distribution. In the real-time operation stage, flexible regulation of PV and energy storage systems is used to adjust power outputs, further optimizing voltage quality. Simulations on the IEEE 33-bus system show that the method effectively improves voltage distribution, enhances renewable energy consumption, and ensures the safe, economic operation of the distribution system.

Voltage regulation and energy loss minimization for distribution networks with high photovoltaic penetration and EV charging stations using dual-stage model predictive control

The widespread integration of photovoltaic (PV) units and controllable loads like electric vehicles (EVs) might cause uncertain voltage fluctuations quite frequently. The reactive power from distributed generation (DG) units and EV charging stations (EVCSs) can effectively be used along with conventional devices like on-load tap changer (OLTC) to successfully control network voltages in real-time, with multi-time scale coordination. However, the control of a large number of available resources, with reliable communication among them becomes a complex task. Moreover, the substantial real-time data set amassed through the deployment of measurement devices across the network increases both cost and computational intricacies. This paper presents a novel approach, employing a time decomposition-based dual-stage model predictive control (MPC) with a reduced model control framework for voltage control and energy loss minimization in active distribution networks (ADNs), by significantly reducing the number of measuring devices. A minimum global set of available control resources is identified for real-time control, aiming to mitigate control complexity and minimize the demand for heavy communication. The proposed control strategy is validated on the 33-bus distribution network and modified IEEE 123-bus distributed network, under high PV penetration and EV charging stations. It is seen that the proposed reduced model framework with very limited measuring devices and control equipment can effectively regulate the voltages with a standard deviation of 0.0059 p.u. and 0.0035 p.u. as compared to the full order system model, for 33-bus network and IEEE 123-bus network, respectively. Furthermore, there is a net 23.24% reduction in energy losses when power loss minimization is considered along with the minimization of voltage deviations in the 33-bus network.

Optimal Sizing and Siting of Fresh and Second-Life Battery Energy Storage Systems Based on Linearized Optimal Power Flow for High Photovoltaic Penetration: A Comparative Study

Optimal Sizing and Siting of Fresh and Second-Life Battery Energy Storage Systems Based on Linearized Optimal Power Flow for High Photovoltaic Penetration: A Comparative Study

Low‐frequency oscillations in MMC‐MVDC systems with high PV penetration: Modelling, mechanism, and assessment

AbstractThis study investigates the low‐frequency oscillations (LFOs) in MMC‐MVDC systems with high photovoltaic (PV) penetration, considering the whole operating conditions of the grid‐connected MMC, including both the inverter and rectifier modes. First, the multi‐port impedance models of converters and networks are developed, upon which a stability criterion is defined. The mechanism of LFOs is then identified using bus participation analysis and parameter sensitivity analysis. In addition, the stable zones of the dominant parameters are identified, taking into account the whole operating conditions of the grid‐connected MMC. Interestingly, a phase‐locked loop may induce LFOs in two low‐frequency ranges. Finally, the experimental results confirm the correctness of the theoretical analysis.

Photovoltaic penetration potential in the Greek island of Ikaria

The operation of Distribution Networks (DNs) has been affected by the ongoing energy transition, gradually incorporating more Distributed Energy Resources (DERs), mainly Renewable Energy Sources (RES), as well as Energy Storage Systems (ESS) sustainably enhancing DN’s flexibility. In the case of the non-interconnected island of Ikaria, Greece, with high solar and wind potential, the DN includes conventional generators, Photovoltaic systems (PVs), wind farms and a hydro-pumped ESS. Scope of this study is to assess the possible impact of the PVs expansion considering either: i) fixed, ii) single-axis or iii) dual-axis tracking panels. For this purpose, CERTH’s in-house INTEMA.grid platform is used. Tracking mechanism’s effectiveness is studied considering that the expansion doubles or triples the rated power of the existing, fixed 0.4 MW PVs, following the directions of the Distribution System Operator (DSO). Additionally, a monthly analysis is presented, because Ikaria is an island with extremely higher load during summer months due to tourism. According to the results, if the current PV capacity is doubled or tripled, a dual-axis expansion yields 16.0% or 21.3% yearly production increase compared to fixed panels, respectively, with the single-axis effect though being much higher (14% or 18.7%, respectively) than the incremental effect of the second axis (further comparative 1.8% or 2.3%, respectively). The effectiveness of tracking mechanisms is highlighted during summer months and particularly early in the morning or late in the afternoon. Finally, environmental and economic indicators for the proposed installations are assessed.

Mitigation of Photovoltaics Penetration Impact upon Networks Using Lithium-Ion Batteries

The paper conducts a comprehensive analysis of the impact of very large-scale photovoltaic generation systems on various aspects of power systems, including voltage profile, frequency, active power, and reactive power. It specifically investigates IEEE 9-bus, 39-bus, and 118-bus test systems, emphasizing the influence of different levels of photovoltaic penetration. Additionally, it explores the effectiveness of battery energy storage systems in enhancing system stability and transient response. The transition to PV generation alters system stability characteristics, impacting frequency response and requiring careful management of PV plant locations and interactions with synchronous generators to maintain system reliability. This study highlights how high penetration of photovoltaic systems can improve steady-state voltage levels but may lead to greater voltage dips in contingency scenarios. It also explores how battery energy storage system integration supports system stability, showing that a balance between battery energy storage system capacity and synchronous generation is essential to avoid instability. In scenarios integrating photovoltaic systems into the grid, voltage levels remained stable at 1 per unit and frequency was tightly controlled between 49.985 Hz and 50.015 Hz. The inclusion of battery energy storage systems further enhanced stability, with 25% and 50% battery energy storage system levels maintaining strong voltage and frequency due to robust grid support and sufficient synchronous generation. At 75% battery energy storage system, minor instabilities arose as asynchronous generation increased, while 100% battery energy storage system led to significant instability and oscillations due to minimal synchronous generation. These findings underline the importance of synchronous generation for grid reliability as battery energy storage system integration increases.

Analyzing the consequences of power factor degradation in grid-connected solar photovoltaic systems

This study examines the impact of integrating solar photovoltaic (PV) systems on power factor (PF) within low-voltage radial distribution networks, using empirical data from the Energy Self-Sufficiency for Health Facilities in Ghana (EnerSHelF) project sites in Ghana. The research included simulations focusing on optimal PV integration, with and without PF considerations, and the strategic placement of PV and shunt capacitors (SC). Three scenarios evaluated PV injection at high-load demand nodes, achieving penetration levels of 85.00 percent, 82.88 percent with high voltage drop, and 100.00 percent with high loss nodes. Additionally, three scenarios assessed SC allocation methods: proportional to the node's reactive power demand (Scenario I), even distribution (Scenario II), and proportional to installed PV capacity at PV nodes (Scenario III).The analysis used a twin-objective index (TOI), combining voltage deviations and power factor degradation. Results showed significant PV curtailment was necessary to achieve standard PF. Optimal penetration levels, considering TOI, reduced PV penetration from 85.00 percent to 63.75 percent, 82.88 percent to 57.38 percent, and 100.00 percent to 72.50 percent for high load, high voltage drops, and high loss nodes, respectively. Notably, all scenarios showed a concerning PF of 0.00 at dead-end nodes (P20, P21, P22).Scenario I achieved PF ranges of -0.26 to 1.00 with PV at high load, -0.69 to 1.00 with PV at high voltage drop, and 0.95 to 1.00 with PV at high loss nodes. Scenario II produced similar ranges, -0.48 to 1.00, -1.00 to 0.99, and 0.30 to 0.96, with PV placement at high load, voltage drops, and loss nodes, respectively. Scenario III yielded ranges of -0.19 to 0.97 (high load), -0.23 to 1.00 (high voltage drop), and 0.86 to 0.96 (high losses).The study concluded that the most effective strategy involves installing PVs at high-loss nodes and distributing SCs proportionally to the node's reactive power demand (Scenario I). This approach achieved a more uniform PF pattern throughout the network, highlighting the practical implications of strategic PV placement and targeted reactive power compensation for maintaining a healthy and efficient distribution system with solar PV integration.

Multi-Timescale Voltage Regulation for Distribution Network with High Photovoltaic Penetration via Coordinated Control of Multiple Devices

The high penetration of distributed photovoltaics (PV) in distribution networks (DNs) results in voltage violations, imbalances, and flickers, leading to significant disruptions in DN stability. To address this issue, this paper proposes a multi-timescale voltage regulation approach that involves the coordinated control of a step voltage regulator (SVR), switched capacitor (SC), battery energy storage system (BESS), and electric vehicle (EV) across different timescales. During the day-ahead stage, the proposed method utilizes artificial hummingbird algorithm optimization-based least squares support vector machine (AHA-LSSVM) forecasting to predict the PV output, enabling the formulation of a day-ahead schedule for SVR and SC adjustments to maintain the voltage and voltage unbalance factor (VUF) within the limits. In the intra-day stage, a novel floating voltage threshold band (FVTB) control strategy is introduced to refine the day-ahead schedule, enhancing the voltage quality while reducing the erratic operation of SVR and SC under dead band control. For real-time operation, the African vulture optimization algorithm (AVOA) is employed to optimize the BESS output for precise voltage regulation. Additionally, a novel smoothing fluctuation threshold band (SFTB) control strategy and an initiate charging and discharging strategy (ICD) for the BESS are proposed to effectively smooth voltage fluctuations and expand the BESS capacity. To enhance user-side participation and optimize the BESS capacity curtailment, some BESSs are replaced by EVs for voltage regulation. Finally, a simulation conducted on a modified IEEE 33 system validates the efficacy of the proposed voltage regulation strategy.

Optimal dispatching of distributed photovoltaic system based on operating costs

Abstract This article investigates the method of distributed photovoltaic optimal dispatching method. The goal is to minimize the operating costs of the distribution network system by coordinating electric heating and distributed energy storage when adjusting the demand-side resources of the distribution network. The analysis is conducted on the operating costs of the distribution network system under different penetration rates of photovoltaics to further promote the accommodation capacity of distributed photovoltaics. The research results show that when the penetration rate of photovoltaics is less than or equal to 90%, only electric heating needs to participate in the accommodation capacity of distributed photovoltaics; when the photovoltaic penetration rate exceeds or equals 100%, both distributed energy storage and electric heating need to participate in the accommodation capacity of distributed photovoltaics. As the penetration rate of photovoltaics gradually increases, the total operating costs and purchased electricity costs show a downward trend. When the penetration rate of photovoltaics increases from 70% to 100%, the network loss costs decrease first, but when the penetration rate reaches 110%, photovoltaics cannot be completely integrated, leading to an increase in network loss costs and dispatching costs. This method fully utilizes the flexible adjusting capabilities of electric heating loads and distributed energy storage, promotes the accommodation capacity of distributed photovoltaics, and improves the economic efficiency of distribution network operation.

Transient response of a megawatt-scale solar photovoltaic in an electric distribution utility

There is an increasing trend among customers of an electrical distribution utility to adopt grid-tied solar photovoltaic systems. This shift offers multiple benefits to consumers, including lower monthly electricity bills and a contribution to the development of green energy. For the electrical distribution utility, various impacts may arise due to varying levels of solar energy penetration. This study investigates the effects of integrating varying levels of solar photovoltaic penetration into the commercial consumer network of Cagayan de Oro Electric Power and Light Company (CEPALCO) in the Philippines. Utilizing PowerWorld simulator, the research evaluates 11 different scenarios with solar penetration levels adjusted according to the percentage of load demand. Key findings include alterations in solar megavolt ampere of reactive power output, bus voltage levels, transformer power loading, and transmission line ampacity, with frequency levels remaining stable across scenarios. The optimal solar penetration level was identified at 70%, balancing the benefits of solar energy integration with the need to maintain grid stability and operational limits. This optimal level ensures the effective utilization of renewable energy sources without compromising the performance of CEPALCO’s electrical infrastructure. The research concludes with recommendations for maintaining grid stability and operational limits at the optimal solar penetration limits.

Study of rooftop PV hosting capacity in 20 kV systems in facing distributed generation penetration

---With the increasing request for integrating rooftop photovoltaic (PV) systems into the distribution grid, it is crucial to prevent the potential negative impacts of high PV penetration. Considering the uncertainty and variability characteristics of high rooftop PV penetration, a stochastic approach for determining PV hosting capacity (HC)—the maximum capacity of a PV system to receive electricity from the power distribution network before the network reaches an operating limit violation—is necessary. Therefore, this study proposes calculating PV hosting capacity using the Monte Carlo simulation. Unlike previous works, this paper uses real feeders as case studies, representing both urban and rural areas. The feeder representing an urban area with many industrial and business customers has a higher hosting capacity, 31 % of full load, compared to the feeder representing rural areas, which has 18 % of full load. By using actual feeders that represent urban and rural areas, more representative results for specific problems can be achieved without assuming urban and rural feeders have the same specific problems.