Photovoltaic Power Curtailment Research Articles

Techno-economic analysis of green hydrogen production using a 100 MW photovoltaic power generation system for five cities in North and Northwest China

In recent years, photovoltaic power generation technology has developed rapidly, but due to its impact on the stability and security of the power grid, some areas in North and Northwest China have a certain degree of photovoltaic power curtailment phenomenon. Hydrogen is considered a good medium for energy storage, and the photovoltaic power generation system based on hydrogen energy storage has been the focus of research. Therefore, this work established simulation models of a photovoltaic power generation with a rated capacity of 100 MW coupling with hydrogen production system using MATLAB software and performs real-time simulation. Techno-economic performance of the integration system in five cities of Hami, Ordos, Datong, Yinchuan, and Yulin was analyzed. The results show that the coupling system can generate 158484–175675 MWh of electricity annually, which can drive the electrolyzer to produce 2524–2761 tonnes of hydrogen. The energy efficiency of the overall system and levelized cost of hydrogen are 9.03–9.31 % and 25.95/22.54–28.38/24.97 CNY/kg. The total CO2 emissions reduction and carbon credits earned by the established system over a lifetime of 20 years can reach 1.81–2.00 million tonnes and 92.19–102.19 million CNY. This paper will provide economic and energy efficiency reference for studying the coupling of green hydrogen production systems with the coal chemical industry in the above regions.

A Mixed-integer Linear Programming Model for Defining Customer Export Limit in PV-rich Low-voltage Distribution Networks

A photovoltaic (PV)-rich low-voltage (LV) distribution network poses a limit on the export power of PVs due to the voltage magnitude constraints. By defining a customer export limit, switching off the PV inverters can be avoided, and thus reducing power curtailment. Based on this, this paper proposes a mixed-integer nonlinear programming (MINLP) model to define such optimal customer export. The MINLP model aims to minimize the total PV power curtailment while considering the technical operation of the distribution network. First, a nonlinear mathematical formulation is presented. Then, a new set of linearizations approximating the Euclidean norm is introduced to turn the MINLP model into an MILP formulation that can be solved with reasonable computational effort. An extension to consider multiple stochastic scenarios is also presented. The proposed model has been tested in a real LV distribution network using smart meter measurements and irradiance profiles from a case study in the Netherlands. To assess the quality of the solution provided by the proposed MILP model, Monte Carlo simulations are executed in OpenDSS, while an error assessment between the original MINLP and the approximated MILP model has been conducted.

Very Short-Term Forecast: Different Classification Methods of the Whole Sky Camera Images for Sudden PV Power Variations Detection

Solar radiation is by nature intermittent and influenced by many factors such as latitude, season and atmospheric conditions. As a consequence, the growing penetration of Photovoltaic (PV) systems into the electricity network implies significant problems of stability, reliability and scheduling of power grid operation. Concerning the very short-term PV power production, the power fluctuations are primarily related to the interaction between solar irradiance and cloud cover. In small-scale systems such as microgrids, the adoption of a forecasting tool is a brilliant solution to minimize PV power curtailment and limit the installed energy storage capacity. In the present work, two different nowcasting methods are applied to classify the solar attenuation due to clouds presence on five different forecast horizons, from 1 to 5 min: a Pattern Recognition Neural Network and a Random Forest model. The proposed methods are tested and compared on a real case study: available data consists of historical irradiance measurements and infrared sky images collected in a real PV facility, the SolarTechLAB in Politecnico di Milano. The classification output is a range of values corresponding to the future value assumed by the Clear Sky Index (CSI), an indicator allowing to account for irradiance variations only related to clouds passage, neglecting diurnal and seasonal influences. The developed models present similar performance in all the considered time horizons, reliably detecting the CSI drops caused by incoming overcast and partially cloudy sky conditions.

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

AbstractThis study introduces a quadratic programming‐based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non‐linear models and surpassing the limitations of local solutions derived from meta‐heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy‐boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival‐and‐desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware‐in‐the‐Loop setup.

Demand-side Management Based on Model Predictive Control in Distribution Network for Smoothing Distributed Photovoltaic Power Fluctuations

With the rapid increase of distributed photovoltaic (PV) power integrating into the distribution network (DN), the critical issues such as PV power curtailment and low equipment utilization rate have been caused by PV power fluctuations. DN has less controllable equipment to manage the PV power fluctuation. To smooth the power fluctuations and further improve the utilization of PV, the regulation ability from the demand-side needs to be excavated. This study presents a continuous control method of the feeder load power in a DN based on the voltage regulation to respond to the rapid fluctuation of the PV power output. PV power fluctuations will be directly reflected in the point of common coupling (PCC), and the power fluctuation rate of PCCs is an important standard of PV curtailment. Thus, a demand-side management strategy based on model predictive control (MPC) to mitigate the PCC power fluctuation is proposed. In pre-scheduling, the intraday optimization model is established to solve the reference power of PCC. In real-time control, the pre-scheduling results and MPC are used for the rolling optimization to control the feeder load demand. Finally, the data from the field measurements in Guangzhou, China are used to verify the effectiveness of the proposed strategy in smoothing fluctuations of the distributed PV power.

Techno-economic analysis of a hybrid energy system for CCHP and hydrogen production based on solar energy

A typical problem in Northeast China is that a large amount of surplus electricity has arisen owing to the serious photovoltaic power curtailment phenomenon. To effectively utilize the excess photovoltaic power, a hybrid energy system is proposed that uses surplus electricity to produce hydrogen in this paper. It combines solar energy, hydrogen production system, and Combined Cooling Heating and Power (CCHP) system to realize cooling, heating, power, and hydrogen generation. The system supplies energy for three public buildings in Dalian City, Liaoning Province, China, and the system configuration with the lowest unit energy cost (0.0615$/kWh) was obtained via optimization. Two comparison strategies were used to evaluate the hybrid energy system in terms of unit energy cost, annual total cost, fossil energy consumption, and carbon dioxide emissions. Subsequently, the annual total energy supply, typical daily loads, and cost of the optimized system were analyzed. In conclusion, the system is feasible for small area public buildings, and provides a solution to solve the phenomenon of photovoltaic power curtailment.

Optimal dispatch of heterogeneous energy complementary system under energy indifference bidding

Owing to the influence of uncontrollable factors (e.g., climate), wind and photovoltaic (PV) energy are highly fluctuating and undispatchable, thereby hindering their integration to the grid. To address this issue, complementary systems using hydropower as a regulating energy are gradually emerging. With the development of wind and PV power industries and the electricity spot market, wind and PV power subsidies are being reduced, and the bidding subjects are diverse. It is likely that wind, PV, and hydropower will participate in the market with the same quality and price. Wind–photovoltaic–hydropower complementary systems (WPHCSs) normally aim at minimum wind and PV power curtailment, which do not consider hydropower production aspects. This study considers the effect of complementary operation on hydropower in the context of energy indifference bidding in the future electricity spot market, establishes a comprehensive benefit index system to optimize WPHCS, and proposes a particle swarm optimization algorithm that introduces the dominant solution with an adjustable parameter to solve the maximizing comprehensive benefits of a complementary system model. Control experiments with different loads, storage capacities, inflows, and models were conducted to verify the superiority of the proposed model and to summarize the optimal operation rule of the complementary system. The results show that turbine efficiency is the main factor affecting the results, and the total benefit of the system could be improved by up to 69% comparing with the priority consumption of wind and the PV power model. This paper describes the WPHCS benefits more comprehensively, and the results can be used to improve the benefits of complementary systems.

Comparison of Active and Reactive Power Oscillation Damping With PV Plants

This article proposes a flexible control scheme (FCS) of a photovoltaic (PV) power plant to support the voltage stability and provide fast recovery after the grid faults in a power system with high penetration renewable energy sources (RES). To achieve these goals, the proposed FCS includes two control loops: a reactive current (I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</sub> ) injection loop and a frequency-damping control (FDC) loop. The I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</sub> injection loop injects I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</sub> in proportion to the terminal voltage of the PV during a fault. After the fault clearance, the FDC loop provides active and/or reactive power modulation to stabilize system frequency; then, the FDC loop puts the system recovery forward by damping out the remaining synchronous machines' frequency oscillations. The FDC loop comprises active power damping function without PV power curtailment and reactive power damping function. We verified the proposed FDC's performance in a two-area system for various penetration levels of inverter-based resources using a PSCAD simulator. We investigated the control schemes' effectiveness by comparing the efficiency and the response in mitigating the post-fault oscillations and restoring the voltage regulation.

Voltage regulation methods for active distribution networks considering the reactive power optimization of substations

Due to the increasing penetration of photovoltaic (PV) power systems in active distribution networks (ADNs), PV power fluctuations may result in significant voltage variations of ADNs. Therefore, this paper proposes a voltage regulation method for ADNs to minimize the operational losses while keeping the nodal voltages within the limit with the reduced PV power curtailment and the reduced switching numbers of on-load tap changers (OLTCs) and capacitor banks (CBs). Meanwhile, the proposed voltage regulation method also aims to minimize the reactive power flowing through OLTCs, and to minimize the switching numbers of substation CBs. In this study, the centralized voltage regulation is performed based on the worst voltage variation scenarios of ADNs, where a multi-objective mixed integer nonlinear programming (MINP) model with time-varying decision variables is established. The MINP model is solved using the non-dominated sorting genetic algorithm II (NSGA-II), and a practical decision-making algorithm is developed to select the best solution from the Pareto optimal set. Moreover, the decentralized voltage regulation aims at mitigating real-time nodal voltage variations via adjusting the real-time active and reactive power of each PV plant. Several simulations and comparisons are carried out on a modified IEEE 33-node system to verify the effectiveness of the proposed methods, and to compare with some previous voltage regulation methods. Simulation results show that the proposed voltage regulation methods can not only effectively control voltage variations of ADNs but also improve the economics of ADNs, substations, and PV plants.

Multiobjective Photovoltaic Sizing With Diverse Inverter Control Schemes in Distribution Systems Hosting EVs

Worldwide, photovoltaic (PV) and electric vehicles (EVs) have intensively been integrated into distribution systems. As a result, different operational issues can be observed due to PV generation variability and EV stochastic characteristics. In this article, an optimal sizing approach of multiple PVs in the existence of EVs is proposed. The proposed approach minimizes both the total voltage deviations and overall energy losses, prevents active PV power curtailment, and considers numerous constraints of PV, EV, and the distribution system. The features of the proposed approach are the considerations of PV, EV, and load uncertainties via incorporating their probabilistic models. Besides, it models arrival/parting times of EVs, the required state of charge (SOC) of EV batteries based on initial SOCs and remaining parking periods, and controlled/uncontrolled charging. Furthermore, diverse control schemes of the interfacing PV inverter are formulated in the proposed optimization model. To effectively solve this comprehensive model with conflicting subfunctions and variables, a two-level multiobjective evolutionary algorithm based on decomposition with fuzzy sets is developed. The upper optimization level accurately optimizes the sizes of multiple PVs, while the lower one optimizes charging/discharging of EV batteries, PV inverter oversize, and PV reactive power. The results prove the effectiveness of the proposed approach.

Steady-State Voltage Regulation With Reduced Photovoltaic Power Curtailment

The curtailment of photovoltaic (PV) power injection is one of the ways to mitigate the overvoltage issue in residential distribution networks with high levels of PVs. The reactive power compensation (RPC) of PV inverter, when applied in conjunction with the active power curtailment (APC) of battery energy storage system (BESS), is more effective in improving the voltage profile. Hence, a coordinated power compensation algorithm (PCA) is proposed in this article to regulate the voltage and reduce the power curtailment while serving requisite load demand. Both RPC and APC are integrated to improve the voltage regulation margin in a low-voltage distribution network. Using bus voltage sensitivities, the integrated RPC and APC are performed on the most sensitive PV inverter and BESS for voltage regulation. The proposed PCA has a large capability in voltage regulation as it performs RPC before APC, reducing the amount of total PV power curtailment. Simulation studies are conducted on distribution feeders to demonstrate the effectiveness of the proposed approach.

A Photovoltaic Power Curtailment Method for Operation on Both Sides of the Power-Voltage Curve

Massive integration of non-dispatchable energy into electric power systems is a challenging task. Electric power systems are becoming increasingly vulnerable in terms of frequency stability, as renewable energy displaces conventional synchronous generation from the energy mix. For this reason, grid codes are starting to demand different ancillary services from renewable generators, such as frequency control. In contrast to wind generators, which can deliver to the grid part of the kinetic energy stored in their rotating mass, photovoltaic generators must provide this service using batteries or power curtailment methods. The latter approach is preferable regarding the initial investment and its implementation cost, and several methods have been presented in the literature for this purpose. However, there is no consensus in which is the most appropriate side for operating the photovoltaic system in the curtailed mode. As both possible options have advantages and drawbacks, this paper proposes a novel photovoltaic power curtailment strategy that allows operation on both sides of the power-voltage curve depending on the needs. Moreover, in order to estimate the output characteristic of the photovoltaic system, a real-time nonlinear least squares curve fitting is applied. The proposed methodology has been tested in a simulation environment and the results show that this strategy achieves the requested active power reserves, regardless of the operation side.

What is the future policy for photovoltaic power applications in China? Lessons from the past

Over the past decades, a series of policies and regulations have been formulated to encourage photovoltaic (PV) development in China. The phenomena of “subsidy deception” and “PV power curtailment and brownout” indicate the policies have encountered problems in implementation. A large gap between subsidies and renewable funds has compelled the Chinese government to gradually withdraw subsidy policy. As such, investors are focusing on assessing China's future policies for PV application. To determine the reasons for the implementation problems and to seek solutions, this study summarized existing PV power application policies and established a two-dimensional framework to analyze these policies, using a content analysis. We found the government relies too much on the state's macroeconomic control, and does not fully play the role of “invisible hand” in PV power applications. Supply-type and environment-type policies are widely used, making up almost 80% of the total. To fully enable the market's role, it is necessary to reinforce demand-type policies and improve green certification transactions. These are forms of incentive policies instead of subsidies.

Weather index insurance for wind energy

As China vigorously promotes the development of new energy, photovoltaic power curtailment and wind power curtailment have been effectively resolved. At the same time, the yield from new energy power generation is becoming an important factor that affects the scale of investment in new energy. This paper focuses on the weather risks faced by wind power producers. By studying current research on weather index insurance in China and abroad, the functions and design methods for weather index insurance have been clarified. In addition, the feasibility of wind-power generation index insurance is discussed. The calculation methods for wind power generation index and the weather index insurance pricing methods for wind power enterprises are proposed. A weather index insurance model for wind power generation was established. The rationality and feasibility of the weather index insurance model proposed in this paper were verified using data from an existing power plant. The simulation results show that wind power enterprises can effectively avoid economic losses caused by weather risks through weather index insurance.

Control Strategy of a Hybrid Energy Storage System to Smooth Photovoltaic Power Fluctuations Considering Photovoltaic Output Power Curtailment

The power fluctuations of grid-connected photovoltaic (PV) systems have negative impacts on the power quality and stability of the utility grid. In this study, the combinations of a battery/supercapacitor hybrid energy storage system (HESS) and the PV power curtailment are used to smooth PV power fluctuations. A PV power curtailment algorithm is developed to limit PV power when power fluctuation exceeds the power capacity of the HESS. A multi-objective optimization model is established to dispatch the HESS power, considering energy losses and the state of charge (SOC) of the supercapacitor. To prevent the SOCs of the HESS from approaching their lower limits, a SOC correction strategy is proposed to correct the SOCs of the HESS. Moreover, this paper also investigates the performances (such as the smoothing effects, losses and lifetime of energy storage, and system net profits) of two different smoothing strategies, including the method of using the HESS and the proposed strategy. Finally, numerous simulations are carried out based on data obtained from a 750 kWp PV plant. Simulation results indicate that the proposed method is more economical and can effectively smooth power fluctuations compared with the method of using the HESS.

Research on new energy development comprehensive assessment model and application in China

In order to achieve the target of that non-fossil energy accounted for 15% in 2020 and 20% in 2030, new energy has developed rapidly in recent years in our country. However, the rapid development of new energy has brought many problems, such as the wind power curtailment, photovoltaic power curtailment, the unbalanced development in different regions and the imperfect policy. Therefore, it is necessary to make a comprehensive evaluation of the development of new energy, as the basis for the policy formulation and planning of new energy. In this paper, according to the characteristics of the new energy development in China, a comprehensive assessment model of new energy development is constructed, a set of assessment index system is proposed, which of the quantitative and qualitative combination, including energy production, energy consumption and policy mechanism from, and combining the Analytic Hierarchy Process(AHP) method to determine the weight coefficient. Finally, new energy development in Jiangsu province is taken as an example, the comprehensive evaluation of new energy development situation in 2018 is given.

A New Approach to Improve PV Power Injection in LV Electrical Systems Using DVR

With increasing photovoltaic (PV) penetration in low-voltage (LV) distribution networks, voltage violation during the peak PV generation period is one of the main power quality concerns. To minimize the PV power curtailment caused by voltage violations, this paper proposes a new approach utilizing one dynamic voltage restorer (DVR) at the secondary of an existing urban distribution transformer as a continuous voltage compensator with an accompanying control algorithm. The voltage compensation algorithm controls the DVR in real-time to prevent over-voltage and under-voltage at all network nodes, thereby maximizing PV injection and preventing equipment damage. The controller uses the equivalent line impedance of network to estimate the average voltage of load points without the need for any communication links for measuring load voltages. In this approach, the fixed tap changer of the distribution transformer is also optimally adjusted to minimize the DVR rating using a proposed offline optimization method. Simulation results on IEEE LV test feeder prove the ability of the DVR in maintaining all network node voltages within the allowable range in peak demand and peak PV generation periods with the benefit of injecting only a small amount of active and reactive power to the system, in contrast to alternative algorithms.

Autonomous Inverter Voltage Regulation in a Low Voltage Distribution Network

Inverter voltage control techniques, including Volt-Watt and Volt-VAR, have been developed to support higher penetration integration of photovoltaic (PV) generation. These techniques typically focus on voltage regulation as measured at the point of common coupling (PCC). Implementing voltage control with distributed inverters within a low voltage network is challenging due to voltage rise between the PCC and the electrical connection point (ECP). This paper proposes a voltage correction and control method for distributed PV microinverters in a low voltage network by utilizing readily available data measurements, i.e., voltage and power at the ECP of inverters. It is shown that this method could reduce unnecessary PV microinverter tripping and power curtailment while supporting voltage control schemes at the PCC. Test results are provided from simulation-only scenarios and a power-hardware-in-the-loop test platform.

Fully Distributed Quasi-Newton Multi-Area Dynamic Economic Dispatch Method for Active Distribution Networks

Distributed generators are integrated into microgrids or geographically distributed subsystems in active distribution networks and may belong to various entities. Centralized solutions cannot meet future requirements such as high resilience and privacy protection. Therefore, fully distributed economic dispatch (ED) methods are needed and most existing algorithms exhibit linear or sublinear convergence. This paper introduces an efficient fully distributed dynamic ED solution for minimizing photovoltaic power curtailment, based on a parallel primal-dual interior-point algorithm with a quasi-Newton technique. In this method, each area optimizes its own problem with limited information exchanged with its neighbors, and no central coordinator is needed. Based on a peer-to-peer communication paradigm, this method can achieve a global optimum while the privacy of each area is obliquely protected. Numerical tests demonstrated that the algorithm outperforms gradient-based methods such as ADMM and maintains stability under a partial communication failure.

Dynamic Power Management and Control of a PV PEM Fuel-Cell-Based Standalone ac/dc Microgrid Using Hybrid Energy Storage

In this paper, a dynamic power management scheme (PMS) is proposed for a standalone hybrid ac/dc microgrid, which constitutes a photovoltaic (PV)-based renewable energy source, a proton exchange membrane fuel cell (FC) as a secondary power source, and a battery and a supercapacitor as hybrid energy storage. The power management algorithm accounts for seamless operation of the microgrid under various modes and state-of-charge limit conditions of hybrid energy storage when all the sources, storages, and loads are connected directly at the dc link. The PMS generates current references for dc converter current controllers of the FC, the battery, and the supercapacitor. The average and fluctuating power components are separated using a moving average filter. The dc-link voltage regulation under dynamic changes in load and source power variation is proposed. Also, PV power curtailment through control is formulated. The proposed power management is modified and extended to multiple PV generation systems and batteries, with all the sources and storages geographically distributed and operating under multitime-scale adaptive-droop-based control with supervisory control for mode transition. The proposed PMS is validated using simulation results. Also, field programmable gate array/Labview-based laboratory-scale experimental results are presented to validate the PMS under various critical conditions.