The use of wind power has grown strongly in recent years and is expected to continue to increase in the coming decades. Solar power is also expected to increase significantly. In a power system, a continuous balance is maintained between total production and demand. This balancing is currently mainly managed with conventional power plants, but with larger amounts of wind and solar power, other sources will also be needed. Interesting possibilities include continuous control of wind and solar power, battery storage, electric vehicles, hydrogen production, and other demand resources with flexibility potential. The aim of this article is to describe and compare the different challenges and future possibilities in six systems concerning how to keep a continuous balance in the future with significantly larger amounts of variable renewable power production. A realistic understanding of how these systems plan to handle continuous balancing is central to effectively develop a carbon-dioxide-free electricity system of the future. The systems included in the overview are the Nordic synchronous area, the island of Ireland, the Iberian Peninsula, Texas (ERCOT), the central European system, and Great Britain.

To be able to efficiently maintain a continuous balance between supply and demand in power systems with high shares of variable renewable energy (VRE) sources, a variety of studies related to the topic are needed. A fundamental input parameter for such studies is an assessment of the power system's physical needs for balancing power, in form of power imbalances. This article presents a new model for simulating physical power imbalances with a 1-minute time resolution based on multi-area economic dispatch simulations. Compared to existing models with the same purpose, the new model includes the combination of simulating power imbalances with 1-minute time resolution, simulating forecast uncertainty, simulating the continuous behaviour of all power system components and simulating the transmission for netting of power imbalances between balancing areas. By applying the model to a case study of the Nordic synchronous power system in year 2045, the impact of including these features in the model is highlighted. Case study results also show that the size and pattern of power imbalances much depends on the characteristics of a balancing area, in terms of electricity demand, available generation technologies and interconnections to other balancing areas.

This article investigates the potential benefits of dynamic Frequency Restoration Reserve (FRR) allocation and dimensioning in a multi-area context, focusing on the Nordic Load-Frequency Control block. Emphasis is placed on how the available information impacts the FRR dimensioning. To assess the potential benefits, a model for multi-area FRR dimensioning is proposed, applicable to both static and dynamic dimensioning approaches. The proposed FRR dimensioning model includes a new application of a methodology to simulate imbalance scenarios and sequentially dimensions FRR capacity for reference incidents and normal imbalances. The main benefit of dynamic FRR dimensioning is that the need for FRR capacity is continuously updated according to the expected short-term operating conditions, such that the daily reliability level is always close to the desired reliability level. Case study results show that dynamic FRR dimensioning can lead to a reduction in total reserve needs compared to a static approach. This reduction is significantly larger if FRR is dimensioned after the clearing of the day-ahead market.

This paper presents a novel market clearing mechanism for manual Frequency Restoration Reserve (mFRR) capacity markets, focusing on the Nordic market setup. The proposed market clearing mechanism accounts for both expected energy activation costs and mFRR capacity costs. The market clearing problem is formulated as a two-stage stochastic Mixed Integer Linear Program (MILP). To efficiently solve the resulting optimization problem, we introduce a nested decomposition algorithm that combines the Benders Decomposition (BD) and Surrogate Absolute Value Lagrangian Relaxation(SAVLR) methods. For practical implementation, input data scenarios aregenerated using day-ahead (DA) price data modeled by a Bayesian Neural Network (BNN). A real-world case study in Sweden demonstrates that theproposed mechanism can reduce daily mFRR costs by 600-14,500 €. Simulation results further show that the nested decomposition algorithm converges to a near-optimal solution more quickly than standard BD.

To ensure that battery energy storage systems (BESSs) are used to facilitate the operation of power systems with high shares of variable renewable energy (VRE) sources, new policies for BESSs are currently being designed. This paper presents a new model for the system cost-minimizing scheduling of BESSs providing energy and balancing services, which can be used as a policy-evaluation tool and as a benchmark for evaluating current market performance. The model is based on a stochastic optimization problem, which we suggest solving using an algorithm combining Benders Decomposition (BD) and Stochastic Dual Dynamic Programming (SDDP). In this paper, we apply the model to study how the system cost-minimal scheduling of BESSs in Sweden is impacted by new requirements for Limited Energy Reservoir (LER) resources providing Frequency Containment Reserves (FCR). Case study results show that new requirements related to guaranteeing a minimum full activation time significantly impact the operation of BESSs, reducing the provision of upregulating FCR capacity for disturbances (FCR-D up) by over 60 %. Also, the case study results show that the consideration of BESSs’ degradation costs reduces the provision of energy as well as balancing services from BESSs. The daily discharged energy from BESSs is more than 85 % lower if the degradation costs are considered, compared to if they are not considered.

With increasing penetration of variable renewable energy sources (vRES) and a higher rate of electrification in the society, there will be future challenges in maintaining a continuous balance between electricity supply and demand. To investigate the possibility of different technologies to provide balancing services, to dimension future balancing services and design technical requirements for future balancing services, the future need of balancing power must first be known. Future power systems are often analysed by performing simulations capturing the energy produced, consumed or transmitted for different power system components with resolution of one trading period (TP), here called TP energy simulations. However, these simulations do not fully capture the continuous intra-TP power balance that must be kept at every time instance. In this paper, we propose a model to perform high-resolution intra-TP simulations to estimate the need of balancing power based on TP energy simulations. The model is applied to the Swedish system operator (SO) Svenska kraftnät's TP energy simulations of a scenario with high vRES penetration and a highly electrified society in year 2045. The results show that a considerable need of balancing power will occur frequently, where faster ramping of components tend to increase the need of balancing power while assuming that the transmission reliability margin (TRM) is used to net imbalances clearly decreases the need of balancing power.

Increasing penetration of wind power poses challenges to power system balancing due to the uncertainty and variability of wind power generation. In wind integration studies, it is hence important to consider the need of balancing power caused by wind power. In this paper, we propose a new model to simulate minute resolution wind power time series in multi-area power systems, that allows for estimation of the additional need of reserves caused by wind power in future scenarios. The model is based on first simulating forecast uncertainty using a multidimensional autoregressive moving average model, and then simulating the variability by adding an autoregressive time series to a cubic spline interpolation. The model is found to generate scenarios of minute resolution wind power generation that are sufficiently realistic for long-term scenario studies. The model output can be used for analysing future reserve requirements or for scenario generation for stochastic optimisation of future power systems.

This paper presents a sequential dimensioning methodology for frequency restoration reserves in a multi-area power system based on chance-constrained optimization. In the first stage, the reserves to handle the reference incident in each area are dimensioned. Then, the transmission network usage for providing these reserves is calculated and the remaining transfer capacity is used in the next stage where the reserves to handle normal imbalances are dimensioned. The optimization problem in each stage seeks to allocate reserves such that the total volumes of reserves and the line flows are co-optimized. Reserves are dimensioned for four seasons instead of the current static approach with yearly dimensioning. By adjusting the reserve requirements based on the system’s needs, the total reserves are reduced. Also, the results demonstrate high potential in sharing reserves among bidding zones in the Nordic synchronous area.