Operation related maintenance and reinvestment costs for hydropower scheduling

This paper addresses the questions: How to calculate the cost of a start/stop cycle? How to calculate the cost of running one hour outside normal operating range, e.g., on part load? The paper presents a model for calculation of start/stop cost for individual hydropower units comprising both direct costs incurring at each start/stop cycle, and indirect cost because of reduced rehabilitation intervals for the main components. The fundamental assumption is that frequent start-ups lead to increased stress, degradation and wear reducing residual service life equivalent to a certain number of normal operating hours, thus accelerating the need for rehabilitation. The proposed model is used for calculation of both average cost and marginal cost for one start/stop cycle. When calculating the marginal cost, the technical condition of the turbine and generator as well as the length of the stand-still period can be considered. Applying a similar approach, the model is extended to calculate the cost of ramping, part load and overload operation, i.e., costs incurring when using the unit outside the normal operating range. This extension for operation related costs is important to include when deciding hydropower scheduling in systems with large shares of variable generation from wind and solar. Such operation related costs are very important to consider when calculating of the optimal operating strategy for the hydropower units in power systems where hydropower delivers flexibility in terms of load following and different types of reserves. © 2023, The Author(s).Operation related maintenance and reinvestment costs for hydropower schedulingpublishedVersio

Stochastic operation of energy constrained microgrids considering battery degradation

Power systems with high penetration of variable renewable generation are vulnerable to periods with low generation. An alternative to retain high dispatchable generation capacity is electric energy storage that enables utilization of surplus power, where the electric energy storage contributes to the security of supply. Such systems can be considered as energy-constrained, and the operation of the electric energy storage must balance the minimization of the current operating costs against the risk of not being able to meet the future demand. Safe and efficient operation requires stochastic methods with sufficient foresight. Operation dependent storage degradation is a complicating factor. This paper proposes a linear approximation of battery state-of-charge degradation and implements it in a stochastic dual dynamic programming based energy-management model in combination with cycling degradation. The long-term implications of degradation modeling in the daily operation are studied for a small Norwegian microgrid with variable renewable power generation and limited dispatchable generation capacity as well as battery and hydrogen storage to balance supply and demand. Our results show that the proposed strategy can prolong the expected battery lifetime by more than four years compared to the naive stochastic strategy but may cause increased degradation for other system resources. © 2022 The AuthorsStochastic operation of energy constrained microgrids considering battery degradationpublishedVersio

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero‑carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.publishedVersio

Possibilities and challenges for balancing from hydropower

publishedVersio

Balancing future variable wind and solar power production in Central West Europe with Norwegian hydropower Energy

acceptedVersio

Modelling Minimum Pressure Height in Short-term Hydropower Production Planning

-When planning the production for certain hydropower plants, minimum pressure is one of the major critical points. Violation of the minimum pressure causes the power plant to automatically shut down, hence violating the obligations of the plant. Automatic pressure switches and pressure constraints are difficult to model in particular when embedded in a complex water way. This problem is expected to increase when retrofitting hydro installations with new parallel units and increased exploitation of inflow resources. From a scheduling point of view, however, such switches become hard to integrate in an optimal operation plan as the constraint depends on the system state. This paper introduces a novelty in short-term production planning, namely a solution for modelling minimum pressure height in regulated watercourses when optimizing the energy production of hydropower plants. This solution is integrated in the short-term hydropower scheduling tool SHOP. The tool finds an optimal strategy to run a power station with such minimum pressure restrictions and the state dependent topological couplings within the water system. We apply the model on a complex topology, the Sira-Kvina water system, where Norway's largest hydropower station Tonstad Kraftstajon is operationally subject to this rigorous pressure constraint. First, in order to illustrate the concepts of the model, we apply the model on a simplified water course including one reservoir. Next, the outcome and tests are demonstrated on the final model of two reservoirs whose respective outflows are joining together above the pressure gauge, as found in the Sira-Kvina water system

Applying successive linear programming for stochastic short-term hydropower optimization

We present a model for operational stochastic short-term hydropower scheduling, taking into account the uncertainty in future prices and inflow, and illustrate how the benefits of using a stochastic rather than a deterministic model can be quantified. The solution method is based on stochastic successive linear programming. The proposed method is tested against the solution of the true non-linear problem in a principal setting. We demonstrate that the applied methodology is a first-order approximation to a formal correct head-of-water optimization and achieve good results in tests. How the concept of stochastic successive linear programming has been implemented in a prototype software for operational short-term hydropower scheduling is also presented, and the model's ability is demonstrated through case studies from Norwegian power industry. From these studies, improvements occurred in terms of the objective function value and decreased risk of spill from reservoirs.acceptedVersio

Balancing needs and measures in the future West Central European power system with large shares of wind and solar resources

The future European power system will include large shares of variable wind and solar resources. This paper analyses the variability for the eHighway 2050 scenarios (from the EU 7th Framework project) by modelling wind and solar resources from the COSMO-EU model. It quantifies the variability for the countries in West Central Europe, separate for each country, and integrated assuming there is no transmission limitations. The analysis results show that integration of systems by grids will have a smoothing effect on the variability. However, main challenges with periodically very low output will remain. The paper quantifies need for balancing taking present and future load profiles into consideration. The paper shows that many aggregated small-scale batteries only will have a limited effect on the need for balancing beyond a few hours. Finally, the paper discusses how the large reservoirs in the Norwegian hydropower system may serve to the balancing needs

Balancing needs and measures in the future West Central European power system with large shares of wind and solar resources

The future European power system will include large shares of variable wind and solar resources. This paper analyses the variability for the eHighway 2050 scenarios (from the EU 7th Framework project) by modelling wind and solar resources from the COSMO-EU model. It quantifies the variability for the countries in West Central Europe, separate for each country, and integrated assuming there is no transmission limitations. The analysis results show that integration of systems by grids will have a smoothing effect on the variability. However, main challenges with periodically very low output will remain. The paper quantifies need for balancing taking present and future load profiles into consideration. The paper shows that many aggregated small-scale batteries only will have a limited effect on the need for balancing beyond a few hours. Finally, the paper discusses how the large reservoirs in the Norwegian hydropower system may serve to the balancing needs

Non-linear charge-based battery storage optimization model with bi-variate cubic spline constraints

Variable renewable generation demands increasing amount of flexible resources to balance the electric power system, and batteries stand out as a promising alternative. Battery models for optimization typically represent the battery with power and energy variables, while the voltage, current, charge variable space is used for simulation models. This paper proposes a non-linear battery storage optimization model in the voltage, current, charge variable space. The battery voltage is conceived as an empirical function of both state-of-charge and charge current and represented through bi-variate cubic splines. The voltage source converter losses are also approximated with a cubic spline function. Compared to energy-based storage models, the results show that this approach enables safe operation closer to the battery voltage and current limits. Furthermore, it prefers operating around high state-of-charge due to the higher efficiency in that region. © 2020 The AuthorspublishedVersio