Battery Energy Storage Systems for Primary Frequency Regulation Applied to a Thermal Generation Plant

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 SoC trajectory 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.

As the penetration of renewable energy sources (RESs) in power systems continues to increase, their volatility and unpredictability have exacerbated the burden of frequency regulation (FR) on conventional generator units (CGUs). Therefore, to reduce frequency deviations caused by comprehensive disturbances and improve system frequency stability, this paper proposes an integrated strategy for hybrid energy storage systems (HESSs) to participate in primary frequency regulation (PFR) of the regional power grid. Once the power grid frequency exceeds the deadband (DB) of the HESS, the high-frequency signs of the power grid frequency are managed by the battery energy storage system (BESS) through a division strategy, while the remaining parts are allocated to pumped hydroelectric energy storage (PHES). By incorporating positive and negative virtual inertia control and adaptive droop control, the BESS effectively maintains its state of charge (SOC), reduces the steady-state frequency deviation of the system, and provides rapid frequency support. When the system frequency lies within the DB of the HESS, an SOC self-recovery strategy restores the BESS SOC to an ideal range, further enhancing its long-term frequency regulation (FR) capability. Finally, a regional power grid FR model is established in the RT-1000 real-time simulation system. Simulation validation is conducted under three scenarios: step disturbances, short-term continuous disturbances, and long-term RES disturbances. The results show that the proposed integrated strategy for HESS participation in PFR not only significantly improves system frequency stability but also enhances the FR capability of the BESS.

Optimal configuration of battery energy storage system in primary frequency regulation

Primary frequency control with BESS considering adaptive SoC recovery

Comprehensive setting and optimization of Dead-Band for BESS participate in power grid primary frequency regulation

The increase of new energy penetration and load fluctuation level has brought new challenges to power system frequency regulation. The Battery Energy Storage System (BESS) has been proved to have broad application prospects in frequency control recent years. The use of BESS in primary frequency modulation can effectively improve the condition of frequency deviation. But how to control the BESS operating parameters to make power system more economical and stable is still a problem to be solved. A timer trigger parameter tuning method based on rolling optimization and genetic algorithm is proposed. The primary frequency regulation parameters of BESS are dynamically adjusted by proposed method periodically, which can guarantee both smaller frequency deviation and more economical operation of BESS. The result of case study based on MATLAB/SINMULINK demonstrates the effectiveness and advantage of the strategy compared with fixed parameter control method.

In view of the frequency fluctuation caused by the power dynamic imbalance between power system and load when a large number of new energy sources are connected to the grid, this paper proposes a balanced operation strategy that takes into account the demand of grid frequency regulation, the state of charge (SOC) of energy storage batteries and the participation of multiple battery energy storage systems (BESS) in frequency regulation. The primary frequency regulation adaptive control strategy. The strategy is based on the demand of grid frequency regulation, firstly, the frequency deviation is partitioned to determine the throughput flow of battery power, secondly, the adaptive regulation of frequency regulation is achieved based on sag control for single group of BESS in different SOC states, and at the same time, considering the uneven power output of multiple groups of BESS participating in frequency regulation, balanced control is introduced on the basis of single unit frequency regulation to achieve the liaison and cooperation of multiple units of frequency regulation. Finally, based on Matlab/Simulink platform, the simulation verifies the correctness and effectiveness of the mentioned adaptive control strategy.

In primary frequency regulation (PFR) using battery energy storage system (BESS), the droop configuration for BESS needs to be considered thoroughly. This paper modified the traditional droop configuration method by considering more BESS`s internal nonlinear constraints and then proposed a variable droop strategy for operation. By doing this, a modified BESS model for PFR was constructed. Finally, the validity of BESS droop configuration method in this paper is testified with a three-area equivalent model based on the data of actual grid. The results show that variable droop strategy is more suitable for PFR than fixed traditional one.

Battery energy storage systems (BESS) have gained research interests in assisting thermal units in primary frequency regulation (PFR) due to their extremely fast ramp rate. In most previous works regarding PFR control, BESS is designed to track frequency deviation to the best of its ability, namely strategies of full compensation. Although such strategies try hard to reduce penalty costs, they are not necessarily cost-effective since operation costs are ignored in strategy design. This drives to the idea of deriving an optimal target compensation degree by deciding a tradeoff between operation costs and penalty costs. Therefore, first, we establish an optimal BESS operation strategy assisting thermal units in PFR, featured with an optimized target compensation degree. Then, based on the operation strategy, we investigate the optimal size of BESS to minimize operating costs and penalty costs. Finally, numerical simulations are conducted on a commercially-operating 1000MW thermal unit in Shanghai City, where the penalty costs are calculated according to local PFR assessment rules. Simulation results based on practical data have shown that the proposed methodology offers a viable solution to maximize the economic benefits for thermal units equipped with BESS participating in PFR.

Traditionally, the dynamics of power systems have been governed by synchronous generators and their associated rotating masses. However, with the increasing penetration of renewable generation and power electronic interfaces, the inertia contributed by rotating machines has been gradually displaced. This makes it imperative to study alternative elements capable of mitigating the reduction in inertia in modern power systems. This article addresses the problem of optimal sizing and placement of Battery Energy Storage Systems to enhance frequency response in power grids through the application of optimization techniques such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Several inertia scenarios are analyzed, where the algorithms determine the optimal locations for Battery Energy Storage Systems units while minimizing the total installed Battery Energy Storage Systems capacity. As key contributions, this study models Battery Energy Storage Systems units, which emulate inertial responses based on the system’s Rate of Change of Frequency, and evaluates the impact of Battery Energy Storage Systems on frequency stability by analyzing parameters such as the frequency nadir, zenith, and steady-state frequency according to the installed Battery Energy Storage System’s size and location. A comparative analysis of the optimization scenarios shows that the Particle Swarm Optimization algorithm with 50% rotational inertia is the most efficient, requiring the lowest total installed power (277.11 MW). It is followed by the Particle Swarm Optimization algorithm with 100% rotational inertia (285.79 MW) and Genetic Algorithms with 50% rotational inertia (285.57 MW). In contrast, Genetic Algorithms with 25% rotational inertia demand the highest total installed Battery Energy Storage Systems power (307.44 MW), a result directly associated with a significant reduction in system inertia. Overall, an inverse relationship is observed between the available inertia level and the required Battery Energy Storage Systems capacity: the lower the inertia, the greater the power that the Battery Energy Storage Systems must supply to keep the system frequency within acceptable operational limits.

To improve the dynamic response and steady-state frequency quality of a wind–storage coordinated system during primary frequency regulation, and to address the secondary frequency dip caused by rotor kinetic energy recovery when a doubly fed induction generator (DFIG)-based wind turbine (DFIG-WT) participates in frequency support, this paper proposes a coordinated wind–storage primary frequency regulation strategy. This strategy synergistically controls the wind turbine’s rotor kinetic energy recovery and exploits the advantages of hybrid energy storage system (HESS). During the DFIG-WT control stage, an adaptive weighted model is developed for the inertial and droop power contributions of the DFIG-WT based on the available rotor kinetic energy, enabling a rational distribution of primary frequency regulation power. In the control segment of HESS, an adaptive complementary filtering frequency division strategy is proposed. This approach integrates an adaptive adjustment method based on state of charge (SOC) to control both the battery energy storage system (BESS) and supercapacitor (SC). Additionally, the BESS assists in completing the rotor kinetic energy recovery process. Through simulation experiments, the results demonstrate that under operating conditions of 9 m/s wind speed and a 30 MW step disturbance, the proposed adaptive weight integrated inertia control elevates the frequency nadir to 49.84 Hz and reduces the secondary frequency dip to 0.0035 Hz. Under the control strategy where wind and storage coordinated participate in frequency regulation and BESS assist in rotor kinetic energy recovery, secondary frequency dips were eliminated, with steady-state frequency rising to 49.941 Hz. The applicability of this strategy was further validated under higher wind speeds and larger disturbance conditions.

Battery Energy Storage Systems (BESSs) are a new asset for Primary Frequency Regulation (PFR), an ancillary service for improving the grid stability. The system operators determine the implementation and remuneration of PFR. However, assessing the revenue stream is not enough to define the business case, as also the components' lifetime has to be estimated. Previous studies of lifetime estimation for BESSs performing PFR considered only the electrochemical storage, disregarding the power electronics (PE). Nonetheless, researchers have shown the importance of estimating PE wear due to the operation when applied in renewable energy generation and microgrids. This paper presents a lifetime analysis of BESSs providing PFR considering IGBT modules, electrolytic capacitors and electrochemical storage degradation. The lifetime information is used to estimate BESS's Net-Present-Value (NPV), evaluating the benefits of deploying PE-based BESS in the European grid. A comparison between different countries, Germany, the Netherlands, and the U.K., is performed, considering the PFR implementation and remuneration differences. The analysis shows that the BESS management strategy can extend its lifetime and that the component that exhibits the shortest lifetime is the electrochemical storage. The PE components are subject to low wear due to the low power utilization and, therefore, small thermal swings while performing PFR. In conclusion, the provision of PFR by means of BESS has been found to be profitable in all three countries. However, in the Netherlands, the potential NPV has been estimated to be 47% and 76% higher than in Germany and the U.K., respectively.

The increasing exploitation of Renewable Energy Sources (RES) is progressively displacing large conventional power plants, thus reducing system operating reserves and stability margins. Therefore new resources for ancillary service provision are needed. Very fast and flexible response capabilities make Battery Energy Storage Systems (BESS) good candidates to this purpose. However, the related cycling operation may cause early performance degradation due to battery aging. Here, attention is focused on primary and secondary frequency regulation by a BESS, in a stand-alone configuration or supporting a RES-based plant. The BESS response to the measured frequency error and to the secondary control signal in mainland Italy is simulated, in terms of power and energy exchanges and State of Charge (SoC) dynamics. A simplified method is proposed to evaluate battery aging due to such operation: starting from typical characteristic curves Maximum number of cycles to end of life versus Depth of Discharge (DoD), a weighted average DoD, accounting for the actual SoC transient, is computed; the battery expected life is the ratio of the maximum number of cycles and the actual number of partial cycles done, both evaluated at the average DoD. This lifetime is finally compared to the BESS investment pay-back period.

With the increasing penetration of the renewables, power system is with the challenge of the frequency stability. Battery energy storage systems (BESS) are regarded as an effective way providing frequency regulation. At present, BESS mainly make profit by the energy arbitrage, and cannot get much by frequency regulation. Beside executive orders, economic stimulation is another more reasonable method to encourage BESS providing frequency regulation. Therefore, a pricing mechanism for BESS in frequency regulation (FR) considering the penetration level of the renewables is proposed in this paper. In detail, the proposed mechanism sets the minimum tracking accuracy of the BESS in frequency regulation according to the renewables penetration level, and decides the optimal regulation price of BESS which encourages BESS to achieve the setting tracking accuracy. The dynamic programming method is used to decide the way that BESS follow the frequency regulation signals. At last, the promising results shows the proposed pricing mechanism can stimulate BESS in frequency regulation, benefiting to the power system frequency stability.

Lithium-ion battery energy storage systems (BESSs) represent suitable alternatives to conventional generating units for providing primary frequency regulation on the Danish market. This paper presents aspects concerning the operation of the BESSs in the Danish energy market while providing upwards primary frequency regulation. Moreover, the paper presents the experience form field tests dedicated to the evaluation of the BESSs' performance degradation. For this purpose, capacity measurements, Hybrid Pulse Power Characterization (HPPC) measurements, and AC impedance measurements were performed on the BESS demonstrator located in Western Denmark and initial results are introduced and discussed. These measurements can be used to validate models for battery ageing during realistic operation or to develop the diagnostic tools for the BESS.