Primary Control Reserve Research Articles

Demonstration of participation in the German balancing power market using a large‐capacity hybrid battery storage system

AbstractAs one of NEDO's international demonstration projects, a large‐capacity hybrid battery storage system which consists of two types of battery cells with different charge‐discharge characteristics was constructed in the state of Lower Saxony in the Federal Republic of Germany. By using the hybrid battery system has a lithium‐ion which has an advantage in short time and high rate, and a sodium‐sulfur battery (NAS) which has an advantage in long time and low rate, the tender participation in the balancing power market in Germany had been executed. The hybrid battery storage system could successfully drive and provided services for primary and secondary control reserves, elimination of power imbalance, and reactive power injection, as well as a combination of these services.

Overcurrent Limitation in Hydrogen Storage Power Plants (HSPP)

The importance of electrical energy storage (EES) systems has been increasingly recognized for enabling the large-scale integration of intermittent renewable energy sources (RES) into the power grid. Among these systems, the Hydrogen Storage Power Plant (HSPP) stands out as a solution capable of independently managing the supply and storage of electrical energy based on network requirements. Previous investigations have shown that the HSPP operating in grid forming mode (GFM) can provide the required ancillary services in the form of instantaneous, primary and secondary control reserves similar to conventional fossil-fired power plants. However, unlike these traditional synchronous generators, the HSPP consists of power semiconductor devices, resulting in much lower overcurrent tolerance. This paper addresses this challenge by proposing a simple yet robust control technique that regulates the maximum current across the HSPP grid interfacing inverter functioning in GFM. The results demonstrate that the controller can maintain the maximum current magnitude below a threshold of 1.2 pu while ensuring the required reactive current contribution during a three-phase fault.

Analysis of Onshore Synthetic Inertia and Primary Control Reserve Contributions of Alternating Current-Side Meshed Offshore Grids with Voltage-Source Converter and Diode Rectifier Unit High-Voltage Direct Current Connections

The increasing use of renewable energy sources in place of conventional generation units is leading to a reduction in onshore inertia and to the development of offshore wind park grids connected by multiple high-voltage direct current (HVDC) connections to the onshore alternating current (AC) grid. For AC-side meshed offshore grids with voltage-source converter (VSC) and diode rectifier unit (DRU) HVDC connections towards onshore grids, this study focuses on the energetic feasibility of synthetic inertia (SI) and primary control reserve (PCR) contributions triggered locally at the onshore converters of both connection types. To this end, the obstacles preventing contributions for VSC HVDC connections and the mechanisms allowing contributions for DRU HVDC connections are identified first. Based on these findings, the article proposes an enhancement of the offshore HVDC converter controls that is continuously active and allows locally triggered onshore contributions at all onshore HVDC converters of both connection types without using communication and requiring only minimal system knowledge. Additional simulations confirm that, although the enhancement is continuously active, the operational performance of the offshore HVDC converter controls for normal offshore grid operation and its robustness against offshore AC-side faults are not affected.

Preventive DC-side decoupling: a control and operation concept to limit the impact of DC faults in offshore multi-terminal HVDC systems

For the integration of large amounts of offshore wind power, the interconnection of HVDC links towards multi-terminal networks is highly desired. However, its technical realisation remains a major challenge - especially in a multi-vendor environment. In addition to the challenges on the DC-side, it is crucial to guarantee that DC faults do not lead to an intolerable loss of power infeed to the connected AC grid(s). To restrict this power loss, a control and operation concept is presented in this paper which utilises state-of-the-art control and switchgear only: When the total wind power infeed exceeds the primary control reserve of the adjacent AC grid, the DC-side interconnection can be preventively decoupled via DC-side load commutation switches. At all other times, the multi-terminal network is operated in a coupled manner. Using (VDC/P)-droop controls and a DC grid controller, a decoupling sequence is implemented and validated via EMT simulations. The resulting DC fault behaviour is discussed along with technical requirements and limitations. The proposed concept could not only save costs, but also de-risk and accelerate the development of first offshore multi-terminal HVDC networks considering missing DC grid codes and a lack of coherent functional requirements for HVDC protection.

Determining the Required Frequency Control Reserve and Capacity and Location of Synchronous and Virtual Inertial Resources

Replacing conventional generating units with inverter-based generation has lowered the natural inertia of power grids and the primary frequency control reserve provided by synchronous generators. Some of the most important consequences include large frequency deviations and large rates of change of frequency (RoCoF) during sudden load and generation loss. Increasing the inertia of the grid through virtual inertia and synchronous machines, and fast primary frequency response are possible solutions for these problems. This paper proposes an optimization problem to determine the capacity of ultracapacitors and synchronous condensers installed at each bus for inertial response and also the optimal amount of fast primary frequency response while considering technical and economic metrics. A combinational model is proposed to calculate the values of these technical metrics, which results in acceptable accuracy and computational cost. Finally, a modified low-inertia version of the IEEE 39-bus test system is used to verify the effectiveness of the proposed method. The results show that the method is successful in keeping the RoCoF and frequency deviations within acceptable limits while reaching a compromise between technical and economic aspects.

BESS Primary Frequency Control Strategies for the West Africa Power Pool

In recent years, power systems have been moving from conventional power plants toward the integration of renewable energy sources (RES). This trend is taking shape in many developing economies, including in the West Africa Power Pool (WAPP). The integration of RES, however, stresses grid security and stability due to the variability and intermittency of the underlying renewable sources. Battery Energy Storage Systems (BESS) have been identified as a possible solution to address the frequency control challenges in the WAPP Interconnected Transmission System (WAPPITS) in order to help to accommodate high levels of RES. This paper analyzes the application and effectiveness of BESS in providing primary frequency control reserves in the WAPPITS. The analyses are based on numerical simulations that were performed using an open-loop model based on historic frequency measurements from the WAPPITS. The simplified model provided a first-order analysis of the frequency control and state of charge (SOC) restoration logic for BESS installations. This study indicates that a droop-based control strategy that is able to react only to the symmetrical and fast frequency oscillations in the network could be appropriate for regulating BESS in the system. Moreover, it demonstrates that the deployment of BESS alone does not solve frequency control problems and a deep revision of the frequency control service is required, mainly involving traditional power plants.

Convolutional Neural Network for High-Resolution Cloud Motion Prediction from Hemispheric Sky Images

A novel high-resolution method for forecasting cloud motion from all-sky images using deep learning is presented. A convolutional neural network (CNN) was created and trained with more than two years of all-sky images, recorded by a hemispheric sky imager (HSI) at the Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Hannover, Germany. Using the haze indexpostprocessing algorithm, cloud characteristics were found, and the deformation vector of each cloud was performed and used as ground truth. The CNN training process was built to predict cloud motion up to 10 min ahead, in a sequence of HSI images, tracking clouds frame by frame. The first two simulated minutes show a strong similarity between simulated and measured cloud motion, which allows photovoltaic (PV) companies to make accurate horizon time predictions and better marketing decisions for primary and secondary control reserves. This cloud motion algorithm principally targets global irradiance predictions as an application for electrical engineering and in PV output predictions. Comparisons between the results of the predicted region of interest of a cloud by the proposed method and real cloud position show a mean Sørensen–Dice similarity coefficient (SD) of 94 ± 2.6% (mean ± standard deviation) for the first minute, outperforming the persistence model (89 ± 3.8%). As the forecast time window increased the index decreased to 44.4 ± 12.3% for the CNN and 37.8 ± 16.4% for the persistence model for 10 min ahead forecast. In addition, up to 10 min global horizontal irradiance was also derived using a feed-forward artificial neural network technique for each CNN forecasted image. Therefore, the new algorithm presented here increases the SD approximately 15% compared to the reference persistence model.

Techno-Economic Assessment of Flexibility Options Versus Grid Expansion in Distribution Grids

In this paper five different flexibility options are analysed from a techno-economic perspective as alternatives to traditional grid expansion for a specific distribution grid in Germany. The options are: two reactive power control strategies with photovoltaic inverters (as a function of the power feed-in, or of the voltage at the connection point), one residential and two large scale battery storage applications (primary control reserve with autonomous reactive power control or self consumption maximisation strategy with autonomous reactive power control). For the pilot grid located in Southern Germany a photovoltaic expansion pathway is determined. The main goal of this work is to quantify the grid expansion actions that can be avoided by applying these five flexibility options for the assumed expansion pathway, focusing on large scale battery storages. It is shown that the five flexibility options increase the hosting capacity for PV systems, compared to a scenario without, by up to 45%. Furthermore, the results of the economic assessment indicate that the analysed flexibility options might be a viable alternative to traditional grid expansion as all of them show a cost reduction potential for the pilot region. These results could encourage DSOs to consider the integration of additional PV and battery storage systems not as a problem which triggers grid expansion, but as part of the solution reducing future grid expansion costs.

Optimal PV and Battery Investment of Market-Participating Industry Facilities

Introducing flexible consumers to electricity markets is beneficial to the power system and offers them potential economic savings. Industrial consumers are pioneer candidates due to their high energy demand and interest in reducing energy costs. This paper addresses the battery storage and photovoltaics investment problem, which includes five revenue streams for industrial consumers, such as participation in the day-ahead and intraday energy markets as well as the primary control reserve market peak shaving and optimized self-consumption. The uncertainty is considered using correlated scenarios of the local load, primary reserve market and day-ahead market prices, as well as generation from photovoltaics. The uncertainty of the pay-as-bid intraday market with continuous trading is modeled using robust optimization. Credibility and applicability of the model is achieved by using market settings and prices from three European countries (Germany, Denmark and Croatia) and comparing their suitability for encompassing the end-user flexibility. Results shed light on national energy-political and climatic differences, highlighting opportunities for active market participation through individual or aggregated industrial plants.

Reversible Capacity Losses in LiFePO4 / Graphite Cells

This investigation focuses on significant capacity losses that have been found to occur in commercial lithium-iron phosphate (LFP) / graphite cells after repeated shallow cycling around medium states of charge (SOCs). Many combinations of cycle depth, medium SOC and temperature are examined over up to 10,000 full cycle equivalents. Up to 1000 full cycle equivalents, the capacity loss rate is four times higher when the cells are cycled between 40% and 60% state of charge than it is with full cycles. It is shown that these extraordinary losses occur in three different lithium-iron phosphate / graphite cell models, two 26650-type and one 18650-type, but do not occur in a nickel-manganese-oxide / graphite 18650-type cell. Most of the apparently lost capacity is shown to be recoverable by holding the cells at either 0 % or 100 % state of charge over a period of several days. Differential voltage analysis and visual post-mortem inspection as well as coin cell experiments with harvested electrode material suggest that these capacity losses are caused by strongly non-uniform lithium distributions in the electrodes. Hypothetical mechanisms are presented and discussed that could lead to such non-uniform distributions of lithium forming preferentially in lithium-iron phosphate based cells. The findings presented in this study are believed to be particularly relevant for grid applications like primary control reserve or in other scenarios where the battery mainly serves as a peak power buffer, e. g. in hybrid drivetrains.The graph shows the capacity evolution of LFP / graphite cells cycled with full cycles and with 20 % cycle depth around three different medium SOCs. Capacity loss is largest when cycling between 40 % and 60 % SOC. The photographs show post-mortem views of the graphite anodes of three different LFP / graphite cell models that were cycled using this procedure until reaching ca. 80 % remaining capacity. Gold colored stripes at the top and the bottom of the electrodes indicate a non-uniform distribution of intercalated lithium. Figure 1

Techno-Economic evaluation of single and multi-purpose grid-scale battery systems

As the technological evolution continuously flourishes, battery cell prices plunge and political debates about sustainable innovation heat up, the economic attractiveness of battery energy storage systems gets stimulated. The recent development in the German political sphere is driving the transformation in energy generation from traditional to sustainable energy supply. Whereas most research analyzes the potential of single-purpose battery energy storage systems, few studies prove the techno-economic benefits of this technology and its ability to serve multiple purposes. This study evaluates the economic implications of such batteries with a simulation model designed to optimize the return of investment and net present value for a project scope of 20 years while serving as frequency containment operators. The model simulates one year with real data of the Continental European grid frequency, the EPEX electricity market, and load and generation profile of a northern German distribution grid and scales the results with respect to the battery's degradation. Enhanced frequency response and primary control reserve are compared on their technical and economic feasibility as well as their combination with peak shaving applications. The results of the simulations indicate that the enhanced frequency response has the highest profitability and performance for battery energy storage systems. Adding the peak shaving application can improve the profitability and de-stress the grid. In any case, larger battery dimensions regarding capacity and power are linked to higher investment costs and thereby reduce the overall return on investment.

Power Smoothing of a Variable-speed Wind Turbine Generator

This paper presents a power-smoothing scheme of a variable-speed wind turbine generator (VSWTG) that employs separate control gains for the over-frequency section (OFS) and under-frequency section (UFS). In the proposed scheme, an additional proportional control loop based on the system frequency deviation operating in conjunction with maximum power point tracking operation is used. In the OFS, to improve the energy-storing capability, the scheme suggests the gain of the frequency deviation control loop, which is set to be monotonously decreasing with the rotor speed while being significantly larger than that in the UFS. In the UFS, to improve the energy-releasing capability while preventing over-deceleration, the gain of the frequency deviation control loop is set to be a linear function of the rotor speed. The simulation results under continuously varying wind speeds with different wind patterns and wind speeds clearly demonstrate that the proposed scheme significantly mitigates the output power fluctuations of a VSWTG. The proposed scheme keeps the frequency within a narrow range, thereby reducing the required primary frequency control reserve for regulating the frequency under normal operations.

Alkaline Water Electrolysis: Efficient Bridge to CO2‐Emission‐Free Economy

AbstractWater electrolysis is a key technology to realize sector coupling and renewables integration. To establish CO2‐free or ‐reduced value chains as well as carbon capture and utilization, “green hydrogen” is the essential element, serving as fuel, energy carrier, and feedstock for “green chemicals”. As a well‐developed technology, alkaline water electrolysis (AWE) enables industrial scale hydrogen production in high purity. The electrolyzers are highly dynamic in operation and can also serve as primary control reserve, thus further stabilizing the power grid.

Assessment of Primary Control Reserve Requirement from Generator Considering a Battery Energy Storage System

In Korean power system, 376 MW of battery energy storage system (BESS) functions as primary control reserve. The current total requirement of primary control reserve is 750 MW, which is procured by 376 MW of BESS and 374 MW of conventional generators. The BESS installed in the Korean power system can supply its energy for 10 min after loss of generators. If all the energy of the BESS is supplied during the system frequency restoration, this can cause a shortage in primary control reserve. Therefore, a new approach for reserve procurement is required to cope with the shortage in primary control reserve in case the second contingency might happen. Pumped storage hydro generators are good candidates for the additional reserve sources. In this paper, we propose a methodology for procuring additional primary control reserve considering their availability varying in real time and droop characteristics. In the case study, the effect of the proposed methodology is verified through a dynamic simulation.

Day-Ahead and Intra-Day Planning of Integrated BESS-PV Systems Providing Frequency Regulation

The paper proposes an optimal management strategy for a system composed by a battery and a photovoltaic power plant. This integrated system is called to deliver the photovoltaic power and to simultaneously provide droop-based primary frequency regulation to the main grid. The battery state-of-energy is controlled by power offset signals, which are determined using photovoltaic energy generation forecasts and predictions of the energy required to operate frequency regulation. A two level control architecture is developed. A day-ahead planning algorithm schedules the energy profile which is traded at the day-ahead market and defines the primary control reserve that the integrated system is able to provide in the considered day. During the day operations, a second level algorithm corrects the dispatched plan using updated information, in order to guarantee a continuous and reliable service. Both control algorithms take into account the uncertainties of the photovoltaic generation and of the frequency dynamics using stochastic optimization.

SoC management strategies in Battery Energy Storage System providing Primary Control Reserve

Abstract Nowadays, the deployment of grid-tied Lithium-ion Battery Energy Storage Systems (BESSs) is a promising technical solution to guarantee the security and reliability of the electric power system characterized by an increasing share of renewable sources. This paper studies BESS for Primary Control Reserve (PCR) provision by developing an approach to properly simulate BESS behaviour. The proposed approach consists of a controller that elaborates the input signals (frequency fluctuations and battery State of Charge) and returns a power setpoint for the battery, a simplified inverter model and the battery model which is the core part of the approach. Finally, economic analyses are detailed to evaluate the investment on a defined period. The case study is developed in Matlab™ Simulink™ and applied on the Italian regulation framework. Two different battery models are compared: empirical and electrical. Their different nature (e.g. model characteristics and complexity) brings to different results on the PCR service provision. The economic analyses highlight that the optimal design of the BESS is strongly influenced by the penalty costs connected to battery unavailability. In order to guarantee the service continuity SoC mitigation strategies are proposed and simulated; however, it is demonstrated that such strategies might cause a heavier battery utilization impacting on the BESS lifetime expectations and decreasing the investment profitability.

Autoregressive Neural Network for Cloud Concentration Forecast from Hemispheric Sky Images

We present here a new method to predict cloud concentration five minutes in advance from all-sky images using the Artificial Neural Networks (ANN). An autoregressive neural network with backpropagation (Ar-BP) was created and trained with four years of all-sky images as inputs. The pictures were taken with a hemispheric sky imager fixed on the roof at the Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Hannover, Germany. Firstly, a statistical method is presented to obtain key information of the pictures. Secondly, a new image-processing algorithm is suggested to optimize the cloud detection process starting with the Haze Index. Finally, the cloud concentration five minutes in advance at the IMUK is forecasted using machine learning methods. A persistence model forecast to provide a reference for comparison was generated. The results are quantified in terms of the root mean square error (RMSE) and the mean absolute error (MAE). The new algorithm reduced both the RMSE and the MAE of the prediction by approximately 30% compared to the reference persistence model under diverse cloud conditions. The new algorithm could be used as a tool for the stable maintenance of the network for the transmission system operators, i.e., the primary control reserve (within 30 seconds) and the secondary control reserve (within 5 minutes).

Heuristic solution of a joint electric control reserve and wholesale market model

A mixed integer linear programming (MILP) approach for the joint simulation of electric control reserve and electricity wholesale markets is presented. This generation dispatch model extends an existing integrated grid and electricity market (IGEM) model covering the Continental European electric power system. By explicitly incorporating the markets for primary and secondary control reserves (PCR and SCR), the model can reproduce the decisions of generating unit operators on which markets get involved. Besides, the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up. Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year, temporal and geographical interdependencies are used to solve it heuristically. The heuristic therefore splits the model into various sub-problems so that on the one hand, the number of variables, especially of integer variables, per sub-problem is reduced significantly and on the other hand, the relevant interdependencies remain considered. The heuristic is evaluated in terms of accuracy and computation time by means of two case studies. Both case studies show satisfactory accuracy and significant advantages in computation time.

Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry

This paper evaluates the economic potential of energy flexibility in 50 different German small and medium sized enterprises (SMEs) through the installation of a battery storage system (BSS). The central innovation lies in the possibility of pursuing multiple revenue streams simultaneously: peak shaving, provision of primary control reserve (PCR) and energy-arbitrage-trading through intraday and day-ahead markets. The energy system of an industrial manufacturing plant is modelled as a linear program (LP) with a 15-min resolution. The model offers the option to invest in BSSs with different capacities, with the objective of minimizing the overall cost and identifying the optimal size of the BSS. The results show that none of these three revenue streams individually is economically attractive, but when combined, all three together can achieve profitability for some companies, whereby the majority of the cash flow comes from peak shaving and PCR. With a fixed BSS capacity of 500 kWh, the Net Present Value (NPV) varies from a minimum of −350,000 € for just arbitrage up to about 200,000 € for all three use cases in parallel. In the case of a variable BSS capacity, the capacity varies up to 1200 kWh and the Profitability Index (the ratio of investment to NPV) varies from 0.06 to 0.31. Under current German market conditions, arbitrage trading contributes only marginally to the profitability, as the price spreads are too small to justify stronger battery degradation. The paper also identifies various load indicators from the analysis of the demand profile that support the evaluation of a BSS in industry. A stepwise linear regression reveals a moderate dependency of the BSS profitability on two newly developed load indicators. Future work should focus on a more detailed depiction of the battery’s technical behaviour and increasing the sample size to improve the statistical significance of the results.

A Hardware-in-the-Loop Test on the Multi-Objective Ancillary Service by In-Vehicle Batteries: Primary Frequency Control and Distribution Voltage Support

The motivation of our research is to pursue a possibility of utilizing electric vehicles for the future operation of power transmission and distribution grids. In this paper, we report a Power-Hardware-In-the-Loop (Power-HIL) testing on the provision of Ancillary Service (AS) by in-vehicle batteries. The AS of our interest is multi-objective in the sense that it simultaneously provides both primary frequency control reserve for a transmission grid and voltage support for a high-voltage distribution grid. The Power-HIL testing is crucial to validating the Multi-Objective AS because the dynamics of the grids and of power conditioning systems emerge in a common time scale, latter of which involves modeling difficulties and thus needs their inclusion as real physical devices, that is, Power-HIL. We show that the Multi-Objective AS is simulated consistently in a Power-HIL testbed and works effectively in a dynamic situation of transmission and distribution grids.