Primary Frequency Regulation Service Research Articles

A Novel Allocation Strategy Based on the Model Predictive Control of Primary Frequency Regulation Power for Multiple Distributed Energy Storage Aggregators

As the amount of distributed energy storage (DES) in a power system continues to increase, it will not be long before there are multiple DES aggregators participating in frequency regulation, and the realization of their coordinated control is a critical topic of current research. This study focused on the primary frequency regulation (PFR) power allocation strategy among multiple DES aggregators participating in PFR. This study first calculated the PFR demand according to a system frequency response model of the power system with DESs. Next, a PFR power allocation model of DES aggregators was developed based on model predictive control. The objective of this model was to minimize the overall frequency regulation cost while satisfying all of the constraints of DESs. Finally, the distributed interior point method was used to solve the model rapidly. The correctness and effectiveness of the proposed model and algorithm were verified on two unified transmission and distribution systems with DES aggregators used to supply the PFR service. The results revealed that the proposed model could effectively allocate PFR power to the various types of energy storage, with the additional benefits of slowing down the shift in the state of charge for energy storage units and ensuring the continuity of energy storage participation in frequency regulation.

Adaptive Frequency Control Strategy for PMSG-Based Wind Power Plant Considering Releasable Reserve Power

Wind power plants (WPPs) are required to provide primary frequency regulation services when a high proportion of wind power is connected to the grid. The reserve power of wind turbine generators (WTGs), including rotor kinetic energy and deloading power, is determined by its current rotor speed and active power, thus, different frequency regulation levels of WTGs will be formed because of the variable wind speed and the wake effect in a WPP. This article proposes an adaptive frequency control strategy considering releasable reserve power that can enhance the frequency regulation capacity in the permanent magnet synchronous generator (PMSG)-based WPP. The inertial control gains of frequency controller for PMSGs are adjusted adaptively, resting with the releasable kinetic energy, which is a function of current rotor speed. Moreover, primary frequency control gains are adjusted adaptively, resting with the releasable deloading power, which is a function of the current active power, thus, a PMSG operating at a higher rotor speed and active power can release more rotor kinetic energy and deloading power to provide greater frequency regulation capability. The proposed adaptive frequency control strategy is tested using a PSCAD/EMTDC simulator. The simulation analysis indicates that the reserve power of PMSGs in WPP can be utilized effectively while ensuring their stable operation. Meanwhile, the frequency regulation capability would be further enhanced.

Techno Economy Comparison of Conventional Generating Unit and Lithium Battery Energy Storage as a Primary Frequency Regulation of Variable Renewable Energy Penetrated Grid System, Case Study: Southern Sulawesi of Indonesia

Integrating higher shares energy mix of variable renewable energy (VRE) technologies, such as wind and solar PV, in the energy transition process presents many challenges in its operation. One of the required services needed in this activity is the Primary Frequency Regulation (PFR). Many studies have studied various ways to provide PFR services, such as using the Conventional Generating Unit (CGU) and Lithium Battery Energy Storage (LiBESS). This paper presents several battery sizing methods used for comparison between the Levelized Cost of Electricity (LCOE) of a CGU and the Levelized Cost of Storage (LCOS) of a LiBESS, which used as PFR of a VRE penetrated grid system in a case study: the grid of southern Sulawesi, Indonesia. The results show that the LCOE of LiBESS is still below the LCOE of the CGU, but for projections in 2030, the LCOS LiBESS shows a competitive number compared to the LCOE of CGU.

Bi-level non-convex joint optimization model of energy storage in energy and primary frequency regulation markets

Large-scale energy storage as a new type of flexible market player can arbitrage in the energy market and provide primary frequency regulation (PFR) service to make profits. The operation of the battery energy storage system and the market clearing process interact with each other. Therefore, this paper proposes a bi-level optimization joint model of energy storage in energy and primary frequency regulation markets, where the upper-level maximizes the storage profit considering the battery degradation and the lower level simulates the joint market clearing process. Different from the existing research, dynamic frequency nonlinear constraints and the non-convex constraints of binary decision variables are considered in the lower level problem. The reformulation–linearization technique (RLT) is used to transform them into linear constraints. The relaxation and primary-dual reformulation of the original, and penalization of the associated duality gap are used to transform the non-convex model into a single-level mixed integer linear programming problem (MILP) which can be solved directly. The results reflect the influence of energy storage on system frequency and market clearing price. The interactive decision-making relationship between energy storage operation and clearing price is balanced.

Investigation on the ageing mechanism for a lithium-ion cell under accelerated tests: The case of primary frequency regulation service

Lithium-ion batteries are increasingly used for the power network stabilization since renewable energy sources are massively exploited. Since the operating load profile has a strong impact on the degradation of lithium-ion cells, dedicated experimental tests can provide important information in this regard. Herein, a commercial high power 18,650-type LiCoO2-LiNiCoMnO2/Graphite cell was aged according to a standardized endurance test from IEC 61,427–2), which profile is formulated to simulate the primary frequency regulation service. In addition, accelerated ageing was obtained by increasing the ambient temperature to 45 °C. Then, a deep investigation was performed to assess the main degradation phenomena induced by the operating profile. For this purpose, incremental capacity (IC) and differential voltage (DV) analysis as well as electrochemical impedance spectroscopy (EIS) were performed at different state of health (SoH) of the cell. Moreover, in order to estimate the effects induced by the frequency regulation profile in comparison to the degradation phenomena caused by a typical full charge/discharge profile, an identical cell was also aged under this condition. Experimental evidences indicate that the operation under primary frequency regulation is less detrimental for the cell by capacity loss point of view, while larger internal impedance increase was observed in comparison to the typical full charge/discharge profile. Finally, a thermal acceleration coefficient was extrapolated to describe the cell capacity loss at room temperature under frequency regulation profile.

Performance analysis of frequency regulation services provided by aggregates of domestic thermostatically controlled loads

This paper proposes a control method for allowing aggregates of thermostatically controlled loads to provide synthetic inertia and primary frequency regulation services to the grid. The proposed control framework is fully distributed and basically consists in the modification of the thermostat logic as a function of the grid frequency. Three strategies are considered: in the first one, the load aggregate provides synthetic inertia by varying its active power demand proportionally to the frequency rate of change; in the second one, the load aggregate provides primary frequency regulation by varying its power demand proportionally to frequency; in the third one, the two services are combined. The performances of the proposed control solutions are analyzed in the forecasted scenario of the electric power system of Sardinia in 2030, characterized by a huge installation of wind and photovoltaic generation and no coil and combustible oil power plants. The considered load aggregate is composed by domestic refrigerators and water heaters. Results prove the effectiveness of the proposed approach and show that, in the particular case of refrigerators and water heaters, the contribution to the frequency regulation is more significant in the case of positive frequency variations. Finally, the correlation between the regulation performances and the level of penetration of the load aggregate with respect to the system total load is evaluated.

An Automatic Weak Learner Formulation for Lithium-Ion Battery State of Health Estimation

Current pulses are convenient to be actively implemented by a battery management system. However, the short-term features (STF) from current pulses originate from various sensors with uneven qualities, which hinder one powerful and strong learner with STF for the battery state of health (SOH) estimation. This article, thus, proposes an optimized weak learner formulation procedure for lithium-ion battery SOH estimation, which further enables the automatic initialization and integration of the weak learners with STF into an efficient SOH estimation framework. A Pareto front-based selection strategy is designed to select the representative solutions from the nondominated solutions fed by a knee point driven evolutionary algorithm, which guarantees both the diversity and accuracy of the weak learners. Afterward, the weak learners, whose coefficients are obtained by self-adaptive differential evolution, are integrated by a weight-based structure. The proposed method utilizes the weak learners with STF to boost the overall performance of the SOH estimation. The validation of the proposed method is proved by LiFePO <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${_4}$</tex-math></inline-formula> /C batteries under accelerated cycling ageing test including one mission profile providing primary frequency regulation service to the grid and one constant current profile.

Optimal provision of concurrent primary frequency and local voltage control from a BESS considering variable capability curves: Modelling and experimental assessment

This paper proposes a control method for battery energy storage systems (BESSs) to provide concurrent primary frequency and local voltage regulation services. The actual variable active and reactive power capability of the converter, along with the state-of-charge of the BESS, are jointly considered by the optimal operating point calculation process within the real-time operation. The controller optimizes the provision of grid services, considering the measured grid and battery statuses and predicting the battery DC voltage as a function of the current trajectory using a three-time-constant model (TTC). A computationally-efficient algorithm is proposed to solve the formulated optimal control problem. Experimental tests validate the proposed concepts and show the effectiveness of the employed control framework on a commercial utility-scale 720 kVA/560 kWh BESS.

Profitability of Frequency Regulation by Electric Vehicles in Denmark and Japan Considering Battery Degradation Costs

This paper determines the profitability of the primary frequency regulation (FR) service considering the wear of the electric vehicle (EV) battery as a cost. To evaluate the profitability of the FR service, the cost of degradation from FR provision is separated from the degradation caused by driving usage. During FR, the power response is proportional to the frequency deviation with full activation power of 9.2 kW, when deviations are larger than 100 mHz. The degradation due to FR is found to be an additional 1–2% to the 7–12% capacity reduction of a 40 kWh Lithium-ion NMC battery pack over 5 years. The overall economic framework is applied in Denmark, both DK1 and DK2, and Japan, by considering historical frequencies. The DK2 FR market framework is taken as reference also for the Japanese and the DK1 cases. Electricity prices and charger efficiency are the two main parameters that affect the profitability of the service. Indeed, with domestic prices there is no profitability, whereas with industrial prices, despite differences between the frequencies, the service is similarly profitable with approx. 3500€ for a five-year period.

An optimized ensemble learning framework for lithium-ion Battery State of Health estimation in energy storage system

Abstract Battery State of Health (SOH) is critical for the reliable operation of the grid-connected battery energy storage systems. During the long-term Lithium-ion (Li-ion) battery degradation, large amounts of data can be recorded. Unfortunately, massive raw data are naturally with different qualities, which makes it difficult to guarantee the superior performance of one unified and powerful data driven estimator. Thus, this paper proposes a novel ensemble learning framework to estimate the battery SOH, which can boost the performance of the data driven SOH estimation through a well-designed integration of the weak learners. Moreover, the short-term current pulses, which are convenient to be obtained from real applications, act as the deterioration feature for SOH estimation. To establish the weak learners with good diversity and accuracy, support vector regression is chosen to utilize the measurement from a specific condition. A Self-adaptive Differential Evolution (SaDE) algorithm is used to effectively integrate the weak learners, which can avoid the trial and error procedure on choosing the trial vector generation strategy and the related parameters in the traditional differential evolution. For the validation of the proposed method, two LiFePO4/C batteries are cycling under a mission profile providing the primary frequency regulation service to the grid.

A risk-constrained decision support tool for EV aggregators participating in energy and frequency regulation markets

The growing trend of electric vehicles (EVs) in recent years has led to the emergence of EV aggregators in electricity markets. Generally, the main goal of an EV aggregator is to buy electricity from the wholesale market in a cost-effective manner while satisfying the charging requirements of EV owners. Accordingly, this paper presents a decision support tool for EV aggregators which enables them to determine the optimal bidding strategy to effectively participate in the day-ahead and real-time energy, and frequency regulation markets. Indeed, the aggregator mainly obtains profit by selling energy during the high-price hours (via vehicle-to-grid (V2G) capability) and providing primary frequency regulation service to the system operator. The proposed approach is based on a two-stage stochastic programming method, where risk aversion is modeled through the conditional value-at-risk (CVaR). The underlying uncertainties including the real-time energy prices, real-time regulation service deployments, and the uncertainties associated with the EV owners (i.e., arrival time, departure time, and initial battery state-of-charge (SOC)) are modeled as stochastic processes that are represented by different sets of scenarios. The cardinality of the combined scenario set is reduced using backward probability distance algorithm to make the resulting mixed-integer linear programming (MILP) problem tractable in large-scale and real-world cases. Extensive numerical analysis with one thousand EVs and real-world market data are conducted to validate the efficiency of the proposed approach in terms of solution optimality, robustness, and computation efficiency.

Multiobjective Optimization of Data-Driven Model for Lithium-Ion Battery SOH Estimation With Short-Term Feature

As a favorable energy storage component, lithium-ion (Li-ion) battery has been widely used in the battery energy storage systems (BESS) and electric vehicles (EV). Data driven methods estimate the battery state-of-health (SOH) with the features extracted from the measurement. However, excessive features may reduce the estimation accuracy and also increases the human labor in the lab. By proposing an optimization process with nondominated sorting genetic algorithm II (NSGA-II), this article is able to establish a more efficient SOH estimator with support vector regression (SVR) and the short-term features from the current pulse test. NSGA-II optimizes the entire process of establishing a SOH estimator considering both the measurement cost of the feature and the estimation accuracy. A series of nondominated solutions are obtained by solving the multiobjective optimization problem, which also provides more flexibility to establish the SOH estimator at various conditions. The degradation features in this article are the knee points at the transfer instants of the voltage in the short-term current pulse test, which is fairly convenient and easy to be obtained in real applications. The proposed method is validated on the measurement from two LiFePO4/C batteries aged with the mission profile providing the primary frequency regulation (PFR) service to the grid.

Modeling Vehicles to Grid as a Source of Distributed Frequency Regulation in Isolated Grids with Significant RES Penetration

The rapid development of technology used in electric vehicles, and in particular their penetration in electricity networks, is a major challenge for the area of electric power systems. The utilization of battery capacity of the interconnected vehicles can bring significant benefits to the network via the Vehicle to Grid (V2G) operation. The V2G operation is a process that can provide primary frequency regulation services in the electric network by exploiting the total capacity of a fleet of electric vehicles. In this paper, the impact of the plug-in hybrid electric vehicles (PHEVs) in the primary frequency regulation is studied and the effects PHEVs cause in non-interconnected isolated power systems with significant renewable energy sources (RES) penetration. Also it is taken into consideration the requirements of users for charging their vehicles. The V2G operation can be performed either with fluctuations in charging power of vehicles, or by charging or discharging the battery. So an electric vehicle user can participate in V2G operation either during the loading of the vehicle to the charging station, or by connecting the vehicle in the charging station without any further demands to charge its battery. In this paper, the response of PHEVs with respect to the frequency fluctuations of the network is modeled and simulated. Additionally, by using the PowerWorld Simulator software, simulations of the isolated power system of Cyprus Island, including the current RES penetration are performed in order to demonstrate the effectiveness of V2G operation in its primary frequency regulation.

A BESS Sizing Strategy for Primary Frequency Regulation Support of Solar Photovoltaic Plants

This paper proposes a strategy for sizing a battery energy storage system (BESS) that supports primary frequency regulation (PFR) service of solar photo-voltaic plants. The strategy is composed of an optimization model and a performance assessment algorithm. The optimization model includes not only investment costs, but also a novel penalty function depending on the state of charge (SoC). This function avoids the existence of a potential inappropriate SoCtrajectory during BESS operation that could impede the supply of PFR service. The performance assessment algorithm, fed by the optimization model sizing results, allows the emulation of BESS operation and determines either the success or failure of a particular BESS design. The quality of a BESS design is measured through number of days in which BESS failed to satisfactorily provide PFR and its associated penalization cost. Battery lifetime, battery replacements, and SoC are also key performance indexes that finally permit making better decisions in the election of the best BESS size. The inclusion of multiple BESS operational restrictions under PFR is another important advantage of this strategy since it adds a realistic characterization of BESS to the analysis. The optimization model was coded using GAMS/CPLEX, and the performance assessment algorithm was implemented in MATLAB. Results were obtained using actual frequency data obtained from the Colombian power system; and the resulting BESS sizes show that the number of BESS penalties, caused by failure to provide PFR service, can be reduced to zero at minimum investment cost.

Aggregation Frequency Response Modeling for Wind Power Plants With Primary Frequency Regulation Service

High-penetration wind power access to grid requires wind turbine generator (WTG) to provide frequency regulation service. Consequently, the frequency dynamics of wind power plants (WPPs) integrated system are changing; thus, it is necessary to investigate the dynamic frequency response of WPPs. In this paper, an analytical approach for an aggregated frequency response model for WPPs with primary frequency regulation service is presented and validated. First, different operation region of WTGs is fully taken into account, and a low-order wind power frequency response (WPFR) model with combined frequency control is deduced based on small signal analysis theory, which has been given in the form of symbolic transfer function. Afterwards, a system identification (SI) analytical method is proposed to aggregate a multi-machine WPFR model with heterogeneous parameters into a single equivalent model, which is called an aggregated WPFR (AWPFR) model, and this aggregation method is validated by the mathematical proof. Finally, the accuracy and effectiveness of the AWPFR model is verified through comparisons of simulation results obtained from the multi-machine WPFR model, detailed wind power plant (WPP) model and individual WPFR models, and the impact of the WTG parameters on the system frequency characteristics is analyzed and discussed. Such an aggregation model can provide a convenient way to describe the dynamic frequency response of WPPs by avoiding the need for modeling complex transient processes while maintaining a satisfactory level of accuracy.

An evolutionary framework for lithium-ion battery state of health estimation

Battery energy storage system expands the flexibility of the electricity grid, which facilitates the extensive usage of renewable energies in industrial applications. In order to ensure the techno-economical reliability of the battery energy storage system, managing the lifespan of each battery is critical. In this paper, a novel evolutionary framework is proposed to estimate the Lithium-ion battery state of health, which uniformly optimizes the two key processes of establishing a data driven estimator. The features in the degradation process of a battery are conveniently measured by a group of current pulses, which last only few seconds. The proposed evolutionary framework selects the most efficient combination of the short-term features from the current pulse test, and guarantees an optimal training process simultaneously. A hybrid encoding technology is applied to mix the feature extraction and the parameters of support vector regression in one chromosome. With the benefit of the proposed evolutionary framework, the battery state of health is estimated by using support vector regression and genetic algorithm in a more efficient way. A mission profile corresponding to batteries providing the primary frequency regulation service to the power system is used to cycle two Lithium-ion batteries for the validation of the proposed method.

Dual-level consensus-based frequency regulation using vehicle-to-grid service

To coordinate plug-in electric vehicles (PEVs) to support the primary frequency control, this paper presents a dual-level consensus-based frequency control method. The upper-level control aims to minimize the frequency deviation of multi-area power system, and the lower-level control aims to minimize the frequency regulation cost and battery degradation cost for individual PEVs. The incremental cost functions are formulated based on the objectives of the dual control levels, in this case, no objective function needs to be solved, and instead, the optimal results can be achieved by reaching a consensus incremental cost among neighboring individuals. The graph theory is applied to build the communication network among neighboring control areas in upper-level control, and among neighboring PEVs in lower-level control. The consensus algorithm is applied to specify the information updating and exchange among neighboring individuals. In addition, the dynamic models of multi-area power system and PEVs are developed for controller implementation and investigation. The simulation with different case studies are conducted to validate the performance of the proposed dual-level frequency control. The simulation results show that, with limited communication, the connected PEVs can be efficiently coordinated via dual-level controller to provide primary frequency regulation service, and meanwhile meet the battery charging/discharging constraints.

Italian Experience on Electrical Storage Ageing for Primary Frequency Regulation

The paper describes the results of different types of ageing tests performed by Terna (the Italian Transmission System Operator) applied to several electrochemical technologies, namely lithium-based and sodium-nickel chloride-based technologies. In particular, the tested lithium-based technologies exploit a graphite-based anode and the following cathode electrochemistries: lithium iron phosphate, lithium nickel cobalt aluminium, lithium nickel cobalt manganese, and lithium titanate. These tests have been performed in the storage labs located in Sardinia (Codrongianos) and Sicily (Ciminna). The aim of the storage labs is intended to give the electrical grid ancillary services, for example, primary frequency regulation, secondary frequency regulation, voltage regulation, synthetic rotational inertia provision, and many more. For the primary frequency regulation service, the ageing of the batteries is difficult to foresee as the ageing tests are not standardized. The authors proposed some novel cycle types, which showed that, in several cases, the frequency regulation cycle ages the batteries much more than the standard cycle. The standard cycle definition has been adopted in the paper to identify a battery cycle test that was carried out to uniformly compare and rank the different technologies. Moreover, sodium-nickel chloride batteries are unaffected by the types of cycle and have a negligible ageing. In addition, lithium manganese oxide and lithium titanate batteries show very good behaviour with a slight degradation of the dischargeable energy, irrespectively of the type of cycle. Inversely, lithium nickel cobalt aluminium technology shows a considerable ageing and a strong dependence on the cycle types. Even if the theoretical explanations of such aging behaviours need time to be understood and expounded, the authors are convinced that the scientific community should become aware of these experimental results.

Data centers as a source of dynamic flexibility in smart girds

Data centers have a significant potential to become a major source of flexibility in smart girds. They consume currently roughly 3% of all the electricity produced globally and are expected to only increase their consumption as the world becomes more connected and digitalized.As data centers are required to operate without any interruptions, they use power protection systems and energy storages. This paper investigates the technical and economic feasibility of dual-purposing these power protection systems, the uninterruptible power supplies, and their batteries in data centers to perform primary frequency regulation services. While the topic of data centers and demand response has been extensively covered in the current scientific literature, the focus has been on the demand response enabled by server workload shifting or hardware-enabled peak shaving. Based on an extensive literature review, there is a knowledge gap in the literature concerning primary frequency regulation and dynamic response enabled by modern power electronics systems in data centers. In this paper, this knowledge gap is bridged by suggesting a novel approach of taking advantage of the bidirectional operations capabilities of the uninterruptible power supply systems, thereby enabling them to provide dynamic power response from their battery systems.The feasibility of this approach is examined with the proposed method, which includes (1) an analysis of the required energy for primary regulation and the availability of this energy in a typical data center, (2) a simulation of activation events and their impact on the service life of the battery systems, (3) reaction speed and reliability considerations of the operations, and (4) an economic feasibility and balancing market analysis.The results show that as primary frequency regulation is an energy nonintensive service and data center battery systems are by design oversized for redundancy reasons, typical data centers have more than ample amounts of energy to participate in the primary regulation without jeopardizing their own processes. The results also show that by maintaining reasonable levels of usage, the battery systems can be operated within their specifications, and the demand response operations will not cause premature aging of the battery systems. The reaction speed of the power electronics is found to be very high and easily meet the current market requirements.While the achievable revenue from the primary regulation service is small compared for example with the electricity costs of the data centers, it is still significant as there is little to no impact on the daily business of the data centers.

Coordinated Control Method for DFIG-Based Wind Farm to Provide Primary Frequency Regulation Service

With the rapid growth of wind power penetration, system operators are required to enforce grid codes that implement frequency regulation of wind farms. This paper presents a distributed cooperation framework for a doubly fed induction generator based wind farm to participate in primary frequency regulation, including imitated inertia and droop characteristics similar to conventional plants. Compared with centralized schemes, the control efficiency is significantly improved. To realize fast distributed coordination and optimal power distribution among wind turbines (WTs), a distributed Newton method is developed, which only requires WTs to exchange limited information with their neighbors over a sparse communication network, and has a super-linear convergence rate. By introducing an index of state of energy, this method can adequately exploit the kinetic energy of all WTs without loss of security. The simulation results indicate that the method exhibits satisfying dynamic performance and reliability, and the system frequency can be stabilized faster when the wind farm controlled by the proposed method participates in frequency control.