Great Britain Power System Research Articles

Enhanced load frequency control: incorporating locational information for temporal enhancement

With the increasing penetration of renewables in power systems, frequency regulation is proving to be a major challenge for system operators using slower conventional generation, and alternative means to provide faster regulation are being actively sought. The participation of demand side management in ancillary service provision is proven in some energy markets, yet its full potential to benefit frequency regulation, including the exploitation of fast power ramping capability of some devices, is still undergoing research. In this study, a novel approach to improve the speed of response of load frequency control, a secondary frequency control approach is proposed. The proposed control is enabled by an effective location identification technique, is highly resilient to anticipated system changes such as reduction of inertia, and enables fully decentralised power system architectures. The effectiveness of the approach is demonstrated and compared to that of present day regulation control, by means of real-time simulations incorporating appropriate time delays conducted on a five-area reduced model of the Great Britain power system. The applicability of the method is further proven under realistic communications delays and measurements experimentally using a controller and power hardware-in-the-loop setup, demonstrating its critical support for enabling the stable operation of future power systems.

Wide area inter‐area oscillation control system in a GB electric power system

A wide area control system (WACS) for the Great Britain (GB) power system is presented. This WACS is designed to enhance the GB system's small signal stability, i.e. improve the damping of the inter-area oscillatory mode between Scotland and England. This study mainly consists of two parts. In the first part, the conventional concept of high-voltage direct current (HVDC) and supplementary damping control modelling is presented. The model of HVDC and supplementary damping control are tested through the classic two-area model. In the second part, the operation of the proposed WACS is demonstrated using a full model of the GB power system. In addition to the demonstration of the major applications, some key factors that will influence the operation of the wide area inter-area oscillation damping control scheme will be tested and discussed. These factors include the time delay involved in wide area data transmission and the reactions between the additional HVDC damping controller and conventional power system stabilisers.

Structure Constrained Controller Design for Power Plants and EV Aggregator in Frequency Regulation Considering Time Delays

Frequency control is the major concern for the integration of renewable energy into power systems. Electric vehicles (EV) are suggested to mitigate the system frequency deviation due to its vehicle-to-grid (V2G) capability and quick response characteristic. In this paper, the EVs are modeled by an EV aggregator and responded to the measureable states, such as system frequency, outputs of power plants and EV aggregator. Thus, a structure constrained feedback controller for the power plants and the EV aggregator is designed. However, the time delays during the transmission of control signal and state variable are inevitable. To deal with the time delays in the input and state variables, the Pade approximation is applied to construct the state space equations for the time delays. An equivalent augmented system without time delay is derived, in which the linear quadratic regulator (LQR) method is applied to derive the structure constrained feedback controller. Effectiveness and correctness of the proposed method are validated by a simple Great Britain power system in 2020.

Controller to enable the enhanced frequency response services from a multi‐electrical energy storage system

The increased adoption of renewable energy generation is reducing the inertial response of the Great Britain (GB) power system, which translates into larger frequency variations in both transient and pseudo-steady-state operation. To help mitigate this, National Grid, the transmission system operator in GB, has designed a control scheme called enhanced frequency response (EFR) specifically aimed at energy storage systems (ESSs). This study proposes a control system that enables the provision of EFR services from a multi-electrical ESS and at the same time allows the management of the state of charge (SOC) of each ESS. The proposed control system uses a Fuzzy Logic Controller to maintain the SOC as near as possible to the desired SOC of each ESS while providing EFR. The performance of the proposed controller is validated in transient and steady-state domains. Simulation results highlight the benefits of managing the SOC of the energy storage assets with the proposed controller. These benefits include a reduced rate of change of frequency and frequency nadir following a loss of generation as well as an increase in the service performance measure which renders into increased economic benefits for the service provider.

A Hierarchical Governor/Turbine and Electric Vehicles Optimal Control Framework for Primary Frequency Support in Power Systems

This paper aims to develop a hierarchical framework for control of governor/turbine (G/T) and electric vehicles (EVs) as primary reserves to provide primary frequency support. The framework involves two decision layers. The top layer based on EV utilization cost dispatches the primary reserve references that balances load and generation following a generation drop. Subsequently, control commands of this layer transmit to G/T and the lower layer. The lower layer dispatches the aggregated EV power change that commanded from the top layer among large number of EVs. Therefore, in this layer, each individual EV will solve an optimal EV dispatch control in a decentralized manner while meeting its own constraints. To draw further insights into the performance of our proposed scheme, we investigate the impact of the proposed control framework on a simplified Great Britain power system model. The listed simulation results show that the proposed scheme restores the power system frequency within a short period of time upon a sudden supply demand imbalance along with minimizing the aggregated and individual EV utilization and G/T generation change for participating in primary frequency support.

Potential of a Population of Domestic Heat Pumps to Provide Balancing Service

This paper investigates the model of aggregated heat pumps as a source of the flexible load in Great Britain. A thermal model of a domestic heat pump was presented. A decentralised temperature control algorithm was proposed to control the building temperature, and heat pump’s ON and OFF cycles. Seven case studies were used to identify the suitable number of individual heat pump models that can be aggregated to accurately represent the projected number of heat pumps connected to the 2030 GB’s power system. The simulation results revealed that an aggregated model of 5,000 individual heat pumps was accurately representing the entire number of heat pumps in the Great Britain power system. Also, the power consumption of a group of heat pumps was examined in response to the grid frequency. Simulation results showed that the power consumption of aggregated heat pumps was successfully controlled in response to a frequency change. The controlled heat pumps reduced the dependency on the frequency service obtained by expensive peaking generators.

Potential of demand side response aggregation for the stabilization of the grids frequency

The role of ancillary services related to the frequency control have become increasingly important in the smart grids. Demand Side Response is a competitive resource that can be used to regulate the grid frequency. This paper describes the use of heat pumps and fridges to provide ancillary services of frequency response so that to continuously balance the supply with demand. The power consumption of domestic units is usually small and, therefore, the aggregation of large numbers of small units should be able to provide sufficient capacity for frequency response. In this research, dynamic frequency control was developed to evaluate the capacity that can be gathered from the aggregation of domestic heat pumps and fridges for frequency response. The potential of frequency response was estimated at a particular time during winter and summer days. We also investigated the relationship between both loads (domestic heat pumps and fridges) to provide Firm Frequency Response service. A case study on the simplified Great Britain power system model was developed. Based on this case study, three scenarios of load combination were simulated according to the availability of the load and considering cost savings. It was demonstrated that the aggregation of heat pumps and fridges offered large power capacity and, therefore, an instantaneous frequency response service was achievable. Finally, the economic benefit of using an aggregated load for Firm Frequency Response service was estimated.

Energy and reserve scheduling under ambiguity on renewable probability distribution

This paper presents a novel methodology to devise a least-cost energy and reserve scheduling under uncertainty in renewable energy sources (RES) and equipment outages. The uncertainty in renewable production is accounted for by exogenously simulated scenarios, as customary in stochastic programming, whereas outages of generators and/or transmission lines are addressed via adjustable robust optimization. The precise characterization of the RES output by means of a unique probability distribution is a challenging task. Hence, we provide a general formulation that allows the consideration of a set of “credible” probability distributions. In this manner, the system operator's ambiguity aversion to uncertainty in renewable production is accounted for. Our proposed methodology determines the least-cost energy and reserve scheduling through a three-level model. Structurally, the upper level defines a least-cost scheduling and, under uncertainty in renewable production, the middle level identifies the worst contingency for the given operating point. The lower level then utilizes the scheduling provided by the upper-level to determine the best redispatch. In order to control the system equilibrium, we adapt risk constraint techniques to handle the system imbalance uncertainty and ensure a reliable operating level. To solve the multi-level problem, we propose an algorithm that combines Benders decomposition and column-and-constraint generation techniques to approximate the risk measure while scheduling power and reserves. The effectiveness of the proposed model and the importance of considering ambiguity are demonstrated through a case study with real data from the Great Britain power system network.

Load Aggregation over a Time of Day to provide Frequency Response in the Great Britain Power System

In the traditional power system, most of the frequency response services are provided from expensive large synchronous generators. However, demand is an effective element to provide frequency response with less expenditure. This paper discusses the availability of domestic heat pumps and fridges load to provide frequency response service to the Great Britain power system. The data of the low and high-frequency response from heat pumps is supplied by Element Energy while Open Energi provides data of the availability of fridges over the time of day. The potential of frequency response from the aggregation of heat pumps and fridges without undermining the inherent function of the load was estimated at a time of day. The combination of both loads to provide Firm Frequency Response (FFR) service was also investigated. Frequency control was developed to alter the power consumption of the aggregated load in response to a frequency signal. Simulation results showed that the aggregation of the load is an effective way to provide a dynamic frequency response over a day.

Price-Based Schemes for Distributed Coordination of Flexible Demand in the Electricity Market

This paper proposes novel distributed control schemes for large-scale deployment of flexible demand. The problem of efficiently coordinating price-responsive appliances operating in the electricity market is tackled within a game-theoretical framework. Adopting the concept of Nash equilibrium and Lyapunov-based techniques, a new iterative control algorithm is designed in order to always converge to a satisfactory solution for the individual customers, which aim at minimizing their energy costs. From the system perspective, it is shown that global quantities such as total generation costs are reduced at each algorithm iteration. These results are achieved for any penetration level of flexible demand and for all types of interruptible electrical appliances. The proposed control scheme can be applied in practice through a one-shot implementation that, at the price of a negligible degradation of the equilibrium performance, ensures faster convergence to a stable solution. Simulation results are also presented, testing the novel schemes in realistic future scenarios of the Great Britain power system with high penetration of flexible demand.

Assessing the contribution of nightly rechargeable grid-scale storage to generation capacity adequacy

Abstract This paper is concerned with assessing the contribution of grid-scale storage to generation capacity adequacy. Results are obtained for a utility-scale exemplar involving the Great Britain power system. All stores are assumed, for the purpose of capacity adequacy assessment, to be centrally controlled by the system operator, with the objective of minimising the Expected Energy Not Served over the peak demand season. The investigation is limited to stores that are sufficiently small such that discharge on one day does not restrict their ability to support adequacy on subsequent days. We argue that for such stores, the central control assumption does not imply loss of generality for the results. Since it may be the case that stores must take power export decisions without the benefit of complete information about the state of the system, a methodology is presented for calculating bounds on the value of such information for supporting generation adequacy. A greedy strategy is proven to be optimal for the case where decisions can be made immediately after a generation shortfall event has occurred, regardless of the decision maker’s risk aversion. The adequacy contribution of multiple stores is examined, and algorithms for coordinating their responses are presented.

Rapid Frequency Response From Smart Loads in Great Britain Power System

Flexibility in certain types of loads could be exploited to provide fast and controllable power reserve if the supply voltage/frequency is controlled using existing power electronic interfaces (e.g., motor drives) or additional ones like recently proposed electric springs. Such a load together with its power electronic interface forms a so called smart load. Effectiveness of static smart loads for primary frequency response provision has been shown in the previous papers through case studies on a segment of the low voltage/medium voltage (LV/MV) distribution network. In this paper, collective contribution of both static and motor type smart loads to rapid frequency response provision is demonstrated through a case study on the Great Britain (GB) transmission system. The active power reserve available from such smart loads are quantified and aggregated at each node at the transmission level (275/400 kV). The study shows that the smart loads collectively offer a short-term power reserve which is comparable to the spinning reserve in the GB system, and thus can ensure acceptable frequency deviation and its rate of change following a large infeed loss.

System-Level Operational and Adequacy Impact Assessment of Photovoltaic and Distributed Energy Storage, with Consideration of Inertial Constraints, Dynamic Reserve and Interconnection Flexibility

The growing penetration of solar photovoltaic (PV) systems requires a fundamental understanding of its impact at a system-level. Furthermore, distributed energy storage (DES) technologies, such as batteries, are attracting great interest owing to their ability to provide support to systems with large-scale renewable generation, such as PV. In this light, the system-level impacts of PV and DES are assessed from both operational and adequacy perspectives. Different control strategies for DES are proposed, namely: (1) centralised, to support system operation in the presence of increasing requirements on system ramping and frequency control; and (2) decentralised, to maximise the harnessing of solar energy from individual households while storing electricity generated by PV panels to provide system capacity on request. The operational impacts are assessed by deploying a multi-service unit commitment model with consideration of inertial constraints, dynamic reserve allocation, and interconnection flexibility, while the impacts on adequacy of supply are analysed by assessing the capacity credit of PV and DES through different metrics. The models developed are then applied to different future scenarios for the Great Britain power system, whereby an electricity demand increase due to electrification is also considered. The numerical results highlight the importance of interconnectors to provide flexibility. On the other hand, provision of reserves, as opposed to energy arbitrage, from DES that are integrated into system operation is seen as the most effective contribution to improve system performance, which in turn also decreases the role of interconnectors. DES can also contribute to providing system capacity, but to an extent that is limited by their individual and aggregated energy availability under different control strategies.

Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation

State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. The power system of Great Britain (GB) is used as an example because independent verifying data is available from National Grid. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the “resolved” uncertainty associated with estimating the future large-scale atmospheric state is larger than the “unresolved” uncertainty associated with estimating the system-wide wind power response to a given large-scale state. The bounds of skilful forecast range are quantified for three leading global forecast systems. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time are found to be 6-8 days. The lower bound is found to be 1.4-2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5-5.5 days). The upper bound to useful forecast range can only be extended by improving the global forecast system (outside the control of most users) or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound to useful forecast range. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days).

Coordinated control for EV aggregators and power plants in frequency regulation considering time-varying delays

Nowadays, large scale intermittent renewable energy is being integrated to power systems as a solution for the low-carbon development worldwide. With the increasing penetration of renewable power generation, system frequency stability is becoming more and more serious. To increase the utilization of renewable energy, electric vehicles (EVs) are suggested to participate in load frequency control (LFC) through aggregators due to their vehicle-to-grid (V2G) capability and quick response characteristic, which is denoted as EV-LFC controller in this paper. In order to fully take the advantages of EVs in the LFC, this paper presents a coordinated control strategy between EV-LFC controller and traditional power plants based LFC (PP-LFC) controller for frequency regulation. In this strategy, the EV-LFC has a priority in response than the PP-LFC when the system deviation violates its acceptable range. However, the LFC integrating EVs is with inevitable time delays due to the data and control signal transmission. Meanwhile, the system inertia uncertainty caused by renewable energy in power system may also cause instability problem. For this reason, an improved robust stability criterion is proposed to estimate the asymptotically stable for LFC system considering the inertia uncertainty and time-varying delays simultaneously. Additionally, a PI controller for EV-LFC controller is used to enhance the system frequency stability. Finally, the effect of increasing EVs number on the frequency stability is investigated, which may guide system operator to utilize EVs to the LFC properly. Case studies are carried out based on a simplified Great Britain (GB) power system. Simulation results show that the proposed coordination strategy can not only provide effective frequency regulation, but also reduce the output of traditional power plants, in which the inertia uncertainty and time delays are properly considered.

Advanced Control of Thermostatic Loads for Rapid Frequency Response in Great Britain

In the Great Britain power system, reduced system inertia (particularly during low demand conditions) and larger possible infeed loss would make grid frequency regulation extremely challenging in future. Traditional primary frequency response could be insufficient to limit the frequency variation within acceptable range. This paper shows that thermostatically controlled loads (TCLs) (domestic refrigerators) can be controlled without real-time communication and in a nondisruptive way to collectively enhance the network frequency response. The aggregated power consumption of TCLs, distributed across the system, could be controlled as a ‘linear’ function of the locally measured frequency and its rate of change. Alternatively, their aggregated consumption could be made to follow a ‘pre-set’ power profile depending on the estimated infeed loss. A novel technique for accurate estimation of infeed loss and consequent postfault TCL power reduction is also proposed. The effectiveness of the two TCL control strategies is compared for primary and secondary frequency response through a case study on a 36 busbar reduced equivalent of the Great Britain power system. The effect of spatial variation of transient frequencies and the time delays in frequency measurement and filtering are considered to show how the TCLs can realistically provide rapid frequency response.

Dealing with multiple decades of hourly wind and PV time series in energy models: A comparison of methods to reduce time resolution and the planning implications of inter-annual variability

Using a high-resolution planning model of the Great Britain power system and 25years of simulated wind and PV generation data, this study compares different methods to reduce time resolution of energy models to increase their computational tractability: downsampling, clustering, and heuristics. By comparing model results in terms of costs and installed capacities across different methods, this study shows that the best method depends heavily on input data and the setup of model constraints. This implies that there is no one-size-fits-all approach to the problem of time step reduction, but heuristic approaches appear promising. In addition, the 25years of time series demonstrate considerable inter-year variability in wind and PV power output. This further complicates the problem of time detail in energy models as it suggests long time series are necessary. Model results with high shares of PV and wind generation using a single or few years of data are likely unreliable. Better modeling and planning methods are required to determine robust scenarios with high shares of variable renewables. The methods are implemented in the freely available open-source modeling framework Calliope.

Performance of industrial melting pots in the provision of dynamic frequency response in the Great Britain power system

As a result of the increasing integration of Renewable Energy Source (RES), maintenance of the balance between supply and demand in the power system is more challenging because of RES’s intermittency and uncontrollability. The smart control of demand is able to contribute to the balance by providing the grid frequency response. This paper uses the industrial Melting Pot (MP) loads as an example. A thermodynamic model depicting the physical characteristics of MPs was firstly developed based on field measurements carried out by Open Energi. A distributed control was applied to each MP which dynamically changes the aggregated power consumption of MPs in proportion to changes in grid frequency while maintaining the primary heating function of each MP. An aggregation of individual MP models equipped with the control was integrated with the Great Britain (GB) power system models. Case studies verified that the aggregated MPs are able to provide frequency response to the power system. The response from MPs is similar but faster than the conventional generators and therefore contributes to the reduction of carbon emissions by replacing the spinning reserve capacity of fossil-fuel generators. Through the reviews of the present balancing services in the GB power system, with the proposed frequency control strategy, the Firm Frequency Response service is most beneficial at present for demand aggregators to tender for. All studies have been conducted in partnership between Cardiff University, Open Energi London – Demand Aggregator, and National Grid – System Operator in GB to ensure the quality and compliance of results.

Real-Time Detection of Power System Disturbances Based on $k$ -Nearest Neighbor Analysis

Efficient disturbance detection is important for power system security and stability. In this paper, a new detection method is proposed based on a time series analysis technique known as ${k}$ -nearest neighbor ( ${k}$ NN) analysis. Advantages of this method are that it can deal with the electrical measurements with oscillatory trends and can be implemented in real time. The method consists of two stages, which are the off-line modeling and the on-line detection. The off-line stage calculates a sequence of anomaly index values using ${k}$ NN on the historical ambient data and then determines the detection threshold. Afterward, the on-line stage calculates the anomaly index value of presently measured data by readopting ${k}$ NN and compares it with the established threshold for detecting disturbances. To meet the real-time requirement, strategies for recursively calculating the distance metrics of ${k}$ NN and for rapidly picking out the ${k}$ th smallest metric are built. Case studies conducted on simulation data from the reduced equivalent model of the Great Britain power system and measurements from an actual power system in Europe demonstrate the effectiveness of the proposed method.

Quantifying the increasing sensitivity of power systems to climate variability

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.