Primary Frequency Reserve Research Articles

Stochastic Risk-driven Bidding of a Solar and Storage Aggregator in Primary Frequency and Energy Markets: A Performance-based Capacity Allocation Approach

The ever-increasing impact of deploying renewable energy resources reducing power system inertia, requires distributed energy resource (DER) aggregators to secure high-performance, fast-responding primary frequency reserve (PFR) in ancillary service markets. However, enabling immediate and local regulation of the operating point upon detecting frequency deviations imposes the necessity of allocating specific headroom for DERs. The individual headroom susceptibility to uncertainty and response speed of a certain DER not only compromises aggregated headroom performance in the PFR market but also leads to incurring unnecessary opportunity costs in the energy market and inadequate frequency control in the power system. To address this challenge, this paper introduces an integrated probabilistic performance index for DERs that considers their individual interactive heterogeneous response speed and uncertainty. Using this index, aggregators overseeing photovoltaic and smart buildings equipped with energy storage can evaluate, allocate, and remunerate optimal headroom capacity for individual DERs based on their performance. This approach ensures maximum aggregated profits and minimum opportunity costs in the PFR and energy markets while improving the performance of the provided PFR capacity, respectively. These tasks are aimed by a novel optimal capacity allocation strategy for an aggregator in both markets. This strategy employs a mixed-integer linear programming model to find the optimal solution and the conditional value-at-risk measure to tackle the uncertainties faced with the problem. The efficiency of the proposed model is assessed within a system reflecting the ERCOT market structure, demonstrating improved aggregated headroom performance, reduced energy opportunity costs, diminished risk of capacity shortage, and improved load frequency control (LFC) from the power system perspective.

Modeling the Coupling of Rotor Speed, primary Frequency Reserve and Virtual Inertia of Wind Turbines in Frequency Constrained Look-Ahead Dispatch

Modeling the Coupling of Rotor Speed, primary Frequency Reserve and Virtual Inertia of Wind Turbines in Frequency Constrained Look-Ahead Dispatch

Optimal Primary Frequency Reserve Provision by an Aggregator Considering Nonlinear Unit Dynamics

Optimal Primary Frequency Reserve Provision by an Aggregator Considering Nonlinear Unit Dynamics

Chance-Constrained Primary Frequency Reserve Optimization Considering Stochastic Disturbances and Contingencies

Chance-Constrained Primary Frequency Reserve Optimization Considering Stochastic Disturbances and Contingencies

Primary Frequency Reserve Providing Strategy of Doubly-Fed Induction Generator Wind Generation Using Rotor Inertia Characteristics

Primary Frequency Reserve Providing Strategy of Doubly-Fed Induction Generator Wind Generation Using Rotor Inertia Characteristics

Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach

Battery storage is emerging as a key component of intelligent green electricitiy systems. The battery is monetized through market participation, which usually involves bidding. Bidding is a multi-objective optimization problem, involving targets such as maximizing market compensation and minimizing penalties for failing to provide the service and costs for battery aging. In this article, battery participation is investigated on primary frequency reserve markets. Reinforcement learning is applied for the optimization. In previous research, only simplified formulations of battery aging have been used in the reinforcement learning formulation, so it is unclear how the optimizer would perform with a real battery. In this article, a physics-based battery aging model is used to assess the aging. The contribution of this article is a methodology involving a realistic battery simulation to assess the performance of the trained RL agent with respect to battery aging in order to inform the selection of the weighting of the aging term in the RL reward formula. The RL agent performs day-ahead bidding on the Finnish Frequency Containment Reserves for Normal Operation market, with the objective of maximizing market compensation, minimizing market penalties and minimizing aging costs.

A Study on Frequency Stability and Primary Frequency Response of the Korean Electric Power System Considering the High Penetration of Wind Power

The high penetration of wind power decreases the system inertia and primary frequency reserve while replacing the conventional synchronous generators (SGs). Therefore, if the system operator does not take appropriate action on the remaining generation units (GUs) operation, high penetration of wind power will aggravate the frequency stability. To solve this problem, wind power plants (WPPs) may provide the inertial response and primary frequency response (PFR) to support the frequency stability. However, due to the variability of renewable energy, WPPs may not provide adequate frequency response whenever it is required. This paper proposes an algorithm to determine the operation of GUs to provide appropriate PFR for a power system with high penetration of wind power. Through the proposed algorithm, it calculates the required PFR to restore the decreased frequency stability caused by the high penetration of wind power. Then, while considering the available PFR from WPPs, it redetermines the droop coefficient of SGs governor to provide the sufficient PFR to recover the frequency stability. Finally, the effectiveness of the proposed algorithm is verified on the practical Korean electric power system.

Configuration of an Energy Storage System Considering the Frequency Response and the Dynamic Frequency Dispersion

The high proportion of renewable energy sources (RESs) in the system reduces the frequency support capacity and aggravates the generation of unbalanced power, while the dynamic frequency dispersion makes it difficult for a centralized energy storage system (ESS) to take into account the frequency requirements of different regions. In this context, the research takes the region with high penetration of RESs and frequent power fluctuations as the grid node of the ESS. By configuring the parameters of the ESS under the control strategy of virtual synchronous generators, the inertia and the primary frequency reserve of the system are supplemented, and the regulation characteristics of the ESS are depicted. Taking the steady-state recovery time and the amplitude coefficient as the evaluation indexes, the effects of the virtual inertia constant, the virtual damping coefficient, and the virtual frequency regulation coefficient on the behavior of the ESS are deeply analyzed. Finally, the quantitative configuration of the ESS is realized by considering the frequency response and the dynamic frequency dispersion.

Frequency Stability Enhancement of Low-Inertia Large-Scale Power System Based on Grey Wolf Optimization

The high penetration of converter-based distributed generations (DGs) to power system can give rise to the lack of rotational inertia while replacing the conventional synchronous generators (SGs), which provide the primary frequency reserve (PFR) in power systems. As the result, the decrease in PFR aggravates the frequency stability. To overcome this problem, the droop coefficients of governors in the remaining conventional SGs must be re-determined newly and properly. This paper proposes a new solution based on the grey wolf optimization (GWO) method to optimally select the droop coefficients of SG governors in the low-inertia large-scale power system due to the high penetration of renewables. The proposed solution is very effective for reducing the computational effort significantly, and it is able to recover not only the steady-state but also the transient frequency stability. To verify the effectiveness of proposed optimization solution based on the GWO method, several case studies are carried out on the practical Korea electric power system with the penetration of wind power plants of 4 GW.

The potential for balancing the Swedish power grid with residential home batteries

This paper presents the potential for prosumer batteries coupled to PV units to cover the national frequency balancing needs in Sweden. PV coupled residential batteries are found to be profitable with today's prices, if granted access to balancing markets. Simulations are based on national targets for solar PV production in 2040 (5-10 TWh, 5-10% of electric consumption) and current residential PV share of total installed PV capacity. In the study battery attachment rate was 50% and 15% of single family houses were equipped with 10 kW PV installation with a battery capacity of 6 kW / 7.68 kWh. In total, the battery PV systems constituted 25% of total installed capacity of PV in 2040. The results showed that 20% of the aggregated batteries capacity is sufficient to provide around 70-100% of each of the frequency reserves individually. The highest savings are gained for the households when both the primary frequency reserves, FCR-N and FCR-D, are provided by the aggregated batteries together with increasing the PV self-consumption, peak shaving and energy arbitrage. When providing frequency support the PV system payback time was reduced from 14 to 11 years when equipped with battery, compared to only installing PV.

A Market Clearing Mechanism Considering Primary Frequency Response Rate

Prior-art market mechanism designs in the literature do not well distinguish the primary frequency reserve resources with different response rates. This letter proposes a performance ratio that quantifies the relative effectiveness of generators and flexible demand resources in frequency regulation considering their response rates. The performance ratio is incorporated into a real-time market clearing model to optimize both upward and downward primary frequency reserve resources. The proposed method is validated based on the IEEE 118 bus system.

Validating the Real-Time Performance of Distributed Energy Resources Participating on Primary Frequency Reserves

A significant body of research has emerged for adapting diverse intelligent distributed energy resources to provide primary frequency reserves (PFR). However, such works are usually vague about the technical specifications for PFR. Industrial practitioners designing systems for PFR markets must pre-qualify their PFR resources against the specifications of the market operator, which is usually a transmission system operator (TSO) or independent system operator (ISO). TSO and ISO requirements for PFR have been underspecified with respect to real-time performance, but as fossil-fuel based PFR is being replaced by various distributed energy resources, these requirements are being tightened. The TSOs of Denmark, Finland, Norway, and Sweden have recently released a joint pilot phase specification with novel requirements on the dynamic performance of PFR resources. This paper presents an automated procedure for performing the pre-qualification procedure against this specification. The procedure is generic and has been demonstrated with a testbed of light emitting diode (LED) lights. The implications of low bandwidth Internet of Things communications, as well as the need to avoid abrupt control actions that irritate human users, have been investigated in the automated procedure.

A Simulation Environment for Training a Reinforcement Learning Agent Trading a Battery Storage

Battery storages are an essential element of the emerging smart grid. Compared to other distributed intelligent energy resources, batteries have the advantage of being able to rapidly react to events such as renewable generation fluctuations or grid disturbances. There is a lack of research on ways to profitably exploit this ability. Any solution needs to consider rapid electrical phenomena as well as the much slower dynamics of relevant electricity markets. Reinforcement learning is a branch of artificial intelligence that has shown promise in optimizing complex problems involving uncertainty. This article applies reinforcement learning to the problem of trading batteries. The problem involves two timescales, both of which are important for profitability. Firstly, trading the battery capacity must occur on the timescale of the chosen electricity markets. Secondly, the real-time operation of the battery must ensure that no financial penalties are incurred from failing to meet the technical specification. The trading-related decisions must be done under uncertainties, such as unknown future market prices and unpredictable power grid disturbances. In this article, a simulation model of a battery system is proposed as the environment to train a reinforcement learning agent to make such decisions. The system is demonstrated with an application of the battery to Finnish primary frequency reserve markets.

A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves

Primary frequency reserves in Northern Europe have traditionally been provided with hydro plants and fossil fuel-burning spinning reserves. Recently, smart distributed energy resources have been equipped with functionality needed to participate on frequency reserves. Key categories of such resources include photovoltaic systems, batteries, and smart loads. Most of these resources are small and cannot provide the minimum controllable power required to participate on frequency reserves. Thus, virtual power plants have been used to aggregate the resources and trade them on the frequency reserves markets. The information technology aspects of virtual power plants are proprietary and many of the details have not been made public. The first contribution of this article is to propose a generic data model and application programming interface for a virtual power plant with the above-mentioned capabilities. The second contribution is to use the application programming interface to cope with the unpredictability of the frequency reserve capacity that the photovoltaic systems and other distributed energy resources are able to provide to the frequency reserves markets in the upcoming bidding period. The contributions are demonstrated with an operational virtual power plant installation at a Northern European shopping center, aggregating photovoltaic Primary Frequency Reserves resources.

Sizing HESS as inertial and primary frequency reserve in low inertia power system

Sizing HESS as inertial and primary frequency reserve in low inertia power system

Configuration of an Energy Storage System for Primary Frequency Reserve and Inertia Response of the Power Grid

The replacement of traditional fossil fuels by renewable energy sources (RESs) leads to the loss of power grid's frequency support capability while reducing the greenhouse effect. To improve the primary frequency reserve (PFR) and the inertia response (IR) of the grid, a configuration method for an energy storage system (ESS) is proposed. The relationship between the maximum power fluctuation that the system can withstand and the proportion of RESs is deduced in this paper considering the frequency requirements. The capacity and the control parameters of the ESS under the third-order virtual synchronous generator (VSG) control strategy are configured to improve the system's ability to promote energy consumption. Taking the unit power regulation and the inertia constant as references, the contribution of the ESS under different power fluctuations and different control parameters is analyzed. Finally, the simulation results show that the ESS with the proposed methodology has eminent control characteristics and flexible power flow, which can effectively improve the grid's operating environment.

Primary Frequency Support Through North American Continental HVDC Interconnections With VSC-MTDC Systems

This paper proposes a frequency control strategy for voltage source converter based multi-terminal HVDC systems (VSC-MTDC) to facilitate the exchange of primary frequency reserves among asynchronous AC systems, thus providing frequency support from each AC system to the others. The proposed frequency control utilizes a reference signal calculated from global measurements which reflects the overall frequency dynamics of all connected asynchronous AC systems. The proposed control outperforms the traditional frequency droop scheme by reducing impact on the DC voltage profile and improving frequency nadir. The performance of the designed frequency control with different DC voltage droop controls is evaluated. The adaptation of the proposed frequency control for converter outages is analyzed. The robustness of the proposed control to communication latency and the sensitivity of frequency support to power limits are also investigated. The VSC-MTDC model and the proposed control are implemented in the commercial grade software PSS/E and thus is suitable to study large-scale realistic systems and can be incorporated into the power system planning process at utilities and ISOs. The effectiveness of the proposed control is illustrated on a developed AC-MTDC test system and also on a large-scale realistic model combining the North American Western Interconnection (WI) and Eastern Interconnection (EI) with continental HVDC interconnections.

Primary Frequency Response Improvement in Interconnected Power Systems Using Electric Vehicle Virtual Power Plants

The smart grid concept enables demand-side management, including electric vehicles (EVs). Thus way, some ancillary services can be provided in order to improve the power system stability, reliability, and security. The high penetration level of renewable energy resources causes some problems to independent system operators, such as lack of primary reserve and active power balance problems. Nowadays, many countries are encouraging the use of EVs which provide a good chance to utilize them as a virtual power plant (VPP) in order to contribute to frequency event. This paper proposes a new control method to use EV as VPP for providing primary reserve in smart grids. The primary frequency reserve helps the power system operator to intercept the frequency decline and to improve the frequency response of the whole system. The proposed method calculates the electric vehicles’ primary reserve based on EVs’ information, such as the state of charge (SOC), the arriving time and the vehicle’s departure time. The effectiveness of the proposed scheme is verified by several simulation scenarios on a real-world modern power system with different generating units, such as conventional power plants, renewable energy resources, and electric vehicles.

Technical valuation of generating units for participating in primary frequency control

Technical specifications of the generating units affect their primary frequency reserve activation amounts (capacity) and quality (speed and maintaining), which have significant effects on power system security and reliability. This paper discusses the technical value of generating units, participating in primary frequency control, based on all their influential parameters. Initially, the formulation of the active power calculation of the generating units, in response to frequency variations, is developed. The concept of Weighted Average of Frequency Active Power Change (WAFAPC) is introduced, and its continuous and discrete formulation with different types of weighting function are proposed afterwards. Also, a novel general frequency profile is formulated for the incidents. Then the procedure for the technical valuation index calculation is presented while discussing its theoretical convergence issue and stopping criterion. The calculated index has the quantity with the same dimension and unit of electrical power which leads to a quantitative and meaningful comparison of the generating units with possible applications in many areas, such as remuneration, rescheduling, market designing, and technical-economic investigation. Numerical results, based on a real large-scale power grid validated data are presented. These include active power formulation validation, normal condition and incidents frequency variations statistical data, convergence demonstration, time-frame selection, and index calculation for various generating units types. The results demonstrate the accuracy and sufficiency of the proposed concepts and formulations.

A New Control Scheme for Fast Frequency Support From HVDC Connected Offshore Wind Farm in Low-Inertia System

Large-scale renewable energy integration and consequent displacement of synchronous machines result in low system inertia. Low system inertia leads to high rate of change of frequency, higher frequency nadir, and potentially require higher primary frequency reserve to stabilise system frequency following a sudden generation shortfall. To address such frequency stability issue in wind energy integrated system, this paper has proposed a new and realistic control strategy for inertial and primary frequency support from HVDC connected Offshore Wind Farms (OWF). The proposed control strategy, which is based on offshore AC voltage control is not only addressing limitations of high rate of frequency change in the offshore grid, but also does not result in any frequency deviation in the offshore grid while providing frequency support to the main grid. The proposed control strategy is robust for any frequency deviation in the main grid, which utilises HVDC converters to map onshore frequency variation in to voltage variation in the offshore grid, thus enabling adequate inertial and primary frequency support from the OWF. The proposed control strategy has been tested on two test systems and the results are compared with conventional method to demonstrate the robustness, effectiveness and reliability of the proposed frequency support strategy.