Search

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., QC 20240325

For inclusion in large-scale power system models, various aggregations and simplifications in the modeling of relevant actors are needed. This paper focuses on reduced models of hydropower, so called area Equivalent models. They use a simplified topology but are not a direct aggregation of the real hydropower system. Instead, the area Equivalent is constructed to mimic the simulated power production of a more detailed hydropower reference model. Here, this goal is fulfilled by formulating a bilevel problem minimizing the difference in simulated power production between the area Equivalent and its reference. Solving this can be computationally heavy. Thus, for a fast solution of this bilevel problem, a single-level reduction is done, which is then solved using two methods. The first method includes McCormick envelopes to form a linear single-level problem. Second is a modified Benders with a relaxed sub-problem to handle the non-convex single-level. These are then also compared to Particle Swarm Optimization. Moreover, six new upper-level objective functions are investigated for a case study of hydropower in northern Sweden. The method using McCormick envelopes is fast (2–5 min), but the area Equivalent shows lower average performance. The modified Benders finds a solution in 5–31 min with good performance., QC 20240503

Volatilitet i elkostnader har alltid funnits och kommer alltid att finnas eftersom ett rationellt elsystembestår av en kombination av olika kraftverk. Vid hög tillgång på produktion och låg efterfrågan blirmarginalkostnaden låg, och på motsvarande sätt blir marginalkostnaden signifikant högre vid högefterfrågan och låg tillgång på kraftverk med låga driftkostnader. Den liberala elmarknaden som finns i hela Europa innebär att elpriset sätts efter dennaproduktionskostnad. Detta ger ett volatilt elpris, vilket ger incitament till flexibilitet samt ger ocksåsignaler till marknaden att investera i det som ger störst nytta för elsystemet. De kunder somefterfrågar ett stabilt elpris kan ha kontrakt med någon aktör som tar pris-risken. Detta kommer attske till en kostnad, då ingen aktör erbjuder denna tjänst gratis, men många kunder är beredda att tadenna kostnad. Sammanfattningsvis kan följande sägas om prisvolatiliteten: 1) Det är av stort värde för elmarknaden att det finns finansiella verktyg att hanteraelprisvariationer för de aktörer som så önskar. Det är bra att någon myndighet har till uppgift attstudera detta. 2) Prisvolatiliteten, mätt som standardavvikelse på elpriset i Euro/MWh har dock varit lägre iSverige jämfört med, t ex, Tyskland, Frankrike och Nederländerna under 2022-2023. 3) Prisvolatilitet gynnar flexibilitet. Den konsument som kan vara flexibel, t ex ladda sin elbil vid lågefterfrågan, får därmed ett lägre elpris. 4) En troligen central fråga gällande volatilitet är prisvariationer mellan olika år. För framtidenerbjuder då sol+vind den lägsta volatiliteten (plus/minus 4.4 procent baserat på data frånSvenska Kraftnät för tidsperioden 1982-2006) jämfört med faktisk kärnkraft (plus-minus 9.2 procent baserat på data från Energimyndigheten för tidsperioden 1996-2022). 5) Det finns en tyvärr spridd missuppfattning att kärnkraft automatiskt skulle minska prisvolatiliteten.Kärnkrafts-landet Frankrike hade såväl 2022 som 2023 en högre volatilitet änSverige, mät, QC 20240109

Svenska kraftnät använder metoden ”Effekttillräcklighet enligt statisk metod”. Vad denna egentligen beräknar är: Hur mycket effekt behöver importeras: · Under den timmen med den högsta elförbrukning som kan inträffa under ett normalår eller under den mest extrema timmen vart 10:e eller 20:e år (dvs en mycket ovanlig situation). · om: Vindkraften producerar på en nivå som överskrids under 91 procent av tiden · om: Kärnkraften producerar på en genomsnittlig nivå (90%), vilken är den nivå som underskrids under ca 35-42 procent av tiden. Dvs under 58-65 procent av tiden är tillgänglig effekt högre. · om: Även andra kraftslag producerar på en given procent av installerad effekt. Detta innebär (med de värden de använder) att det är cirka 4 procent sannolikhet att såväl kärnkraften som vindkraften skulle ge lägre effekt än det som antas, och detta vid den mest extrema timmen under 10 eller 20 år. Och frågan är inte ”effektbrist” utan ”behov av import” vid dessa mycket osannolika enstaka timmar. Det som studerats i denna rapport är inverkan av en mer rimlig ansats av vilka tillgänglighetsdata man ska använda för vindkraft för att den ska ge samma effektbidrag (samma sannolikhet) som kärnkraft. Resultatet är att vindkraftens ”tillgänglighetsfaktor” bör ändras från ca 9-11 procent till ca 27 procent. Detta kommer därmed, med denna metod, minska ”effekt-bristen” (dvs underskottet enligt den statiska metoden). Med ca 18000 MW vindkraft som totalt förväntas finnas installeras inom de närmaste åren så innebär en tillgänglighetsfaktor om 27.6% istället för den använda nivån 9% en ”effektförstärkning” om 3300 MW. Detta sätt att räkna innebär att man fortsätter anta 90% tillgänglighet för kärnkraften och använder samma percentil för vindkraft och kärnkraft. Med antagande om att 2014-2023 är en representativ period så blir ”effektbidraget” för vindkraft ca 100 MW/TWh och för kärnkraft ca 124 MW/TWh. Men denna metod är fortfarande lite märklig då den inte a, QC 20240903

The growing adoption of electric vehicles (EVs) has introduced substantial challenges to the grid. Uncontrolled EV charging may lead to grid overloading, voltage instability, increased power losses, accelerated aging of distribution transformers, and risk of outages. Therefore, a strategic approach is required to tackle the adverse impacts of uncontrolled EV charging to the grid. A promising approach is using EV batteries collectively as a flexible load. Residential areas have the most pronounced EV flexibility potential due to the significant length of uninterrupted parking. In this paper, models of EV charging in residential areas are formulated, followed by Monte Carlo simulations. Three charging models are developed: uncontrolled charging, controlled charging without considering grid limitation and controlled charging considering grid limitation. An optimization problem based on quadratic programming is used in the controlled charging. A residential area based on the IEEE European LV test feeder adopting the deregulated Swedish electricity market is taken as a case study for the simulation. The case study findings indicate that incorporating grid limitation into controlled charging strategies can prevent grid overload and significantly reduce charging and battery degradation costs. In this case study, controlled charging can reduce the charging costs to approximately 42% compared to uncontrolled charging. Considering the battery degradation costs, controlled charging costs are 24% lower than uncontrolled charging. It is possible to postpone the costly grid reinforcement by applying strategic EV charging scheduling. The methods and outcomes pave the way for developing, testing, and implementing business models to manage the grid impacts of growing EV charging., Part of ISBN 9798350317664QC 20240829

Hydrogen electrolyzers are promising tools for frequency regulation of future power systems with high penetration of renewable energies and low inertia. This is due to both the increasing demand for hydrogen and their flexibility as controllable load. The two main electrolyzer technologies are Alkaline Electrolyzers (AELs) and Proton Exchange Membrane Electrolyzers (PEMELs). However, they have trade-offs: dynamic response speed for AELs, and cost for PEMELs. This paper proposes the combination of both technologies into a Hybrid Hydrogen Electrolyzer System (HHES) to obtain a fast response for frequency regulation with reduced costs. A decentralized dynamic power sharing control strategy is proposed where PEMELs respond to the fast component of the frequency deviation, and AELs respond to the slow component, without the requirement of communication. The proposed decentralized approach facilitates a high reliability and scalability of the system, what is essential for expansion of hydrogen production. The effectiveness of the proposed strategy is validated in simulations and experimental results., QC 20240628

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., QC 20240229Part of ISBN 979-8-3503-9678-2

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., Part of ISBN 978-1-6654-8778-8QC 20231016

Part of ISBN [9781800882119, 9781800882102]QC 20240625

Mycket talar för att vi i Sverige kommer ha betydligt mer vindkraft i framtiden. Men hur fungerar detta elsystem vid låg vind? Kan vindkraften lagras? Frågan är egentligen felställd. Elektricitet transporteras med nära ljushastigheten, så all elkonsumtion i Norden måste varje sekund balanseras med lika mycket produktion som inte alls behövs ligga på samma plats som konsumtionen. Den flexibilitet samt lager som finns används för all typ av variation, vare sig det är vindkraft som mojnar, ett kärnkraftverk som snabbstoppar, eller någon som startar en brödrost. I denna rapport, samt en mer kortfattad krönika, finns en sammanfattning om olika typer av lager som används i kraftsystem för att se till att hålla den kontinuerliga balansen mellan elkonsumtion och elproduktion., QC 20230310

To simulate a hydropower system, one can use what s known as a Detailed model. However, due to the complexity of river systems, this is often a computationally heavy task. Equivalent models, which aim to reproduce the result of a Detailed model, are used to significantly reduce the computation time for large-scale hydropower simulations. This paper computes Equivalent models for hydropower systems in Sweden by categorizing the water inflow data using a spectral clustering method. Computing the Equivalent models is done using a variant of the particle swarm optimization algorithm. Then, the Equivalent models are evaluated based on their similarity to the Detailed model in terms of power production and objective value. The Equivalent models range from 8% - 12% error in terms of the relative power production difference and the computation time is reduced by at least 99.9%., QC 20231122

The increase in hydrogen production to support the energy transition in different sectors, such as the steel industry, leads to the utilization of large scale electrolyzers. These electrolyzers have the ability to become a fundamental tool for grid stability providing grid services, especially frequency regulation, for power grids with a high share of renewable energy sources. Alkaline electrolyzers (AELs) have low cost and long lifetime, but their slow dynamics make them unsuitable for fast frequency regulation, especially in case of contingencies. Proton Exchange Membrane electrolyzers (PEMELs) have fast dynamic response to provide grid services, but they have higher costs. This paper proposes a dynamic power allocation control strategy for hybrid electrolyzer systems to provide frequency regulation with reduced cost, making use of advantages of AELs and PEMELs. Simulations and experiments are conducted to verify the proposed control strategy., QC 20230901

Power systems are experiencing a decrease of synchronous generation along with increased penetration of inverter based renewable generation leading to reduced system inertia and a need for flexible resources. Non-generating resources such as thermostatically controlled loads (TCLs) are flexible due to their thermal energy storage capacity. When aggregated, TCLs can arbitrage energy prices and provide reserves to the power system. We approach the operational flexibility of the TCLs by modeling a risk-averse aggregator that controls decentralized TCLs and aims to maximize its own profit. The high number and low power rating of residential TCLs makes it difficult to model and assess their flexibility potential on national level. Thus, we make use of a high-level thermal energy storage model for aggregations of TCLs to quantify their flexibility potential. We present a method to aggregate temperature, TCL parameters, and building stock data into a thermal battery equivalent. We propose a multi-period multi-market multi-zonal two-stage chance constrained rolling horizon optimization problem formulation for the risk-averse day-ahead self-scheduling problem of a price-taker TCL aggregator bidding in energy and reserve markets under uncertainty and recast the problem as a linear program. We perform several case studies in the Swedish power system based on a survey of single -and two-family dwellings with electric heating and assess the flexibility potential. Additionally, a sensitivity analysis provides insights regarding market design and policy implications., QC 20230412

In this paper, an hourly dispatch model was developed to analyze the system balancing and wind power curtailment challenges in the future of the Ethiopian electric power grid system. The developed model was validated using historical data and was used for the analysis of the grid system in 2030 with different scenarios. The model was used to examine the impacts of transmission capacity, regulation reserve requirement, and daily minimum generation of hydropower for irrigation with three cases of wind annual energy share of 14.5%, 17.8%, and 25.2%. Thus, the curtailment was found to be below 0.2%, 1.1%, and 9.8% for each case, respectively. The cost of wind energy increases in proportion to the percentage of curtailment and the increase in transmission line capacity. Reducing the minimum hydropower generation results in smaller wind power curtailment and better generation-consumption balancing., QC 20230810

Combined heat and power (CHP) plants are main generation units in district heating systems that produce both heat and electric power simultaneously. Moreover, CHP plants can participate in electricity markets, selling and buying the extra power when profitable. However, operational decisions have to be made with unknown electricity prices. The distribution of unknown electricity prices is also not known exactly and uncertain in practice. Therefore, the need of tools to schedule CHP units' production under distributional uncertainty is necessary for CHP producers. On top of that, a heating network could serve as a heat storage and an additional source of flexibility for CHP plants. In this paper, a distributionally robust short-term operational model of CHP plants in the day-ahead electricity market is developed. The model accounts for the heating network and considers temperature dynamics in the pipes. The problem is formulated in a data-driven manner, where the production decisions explicitly depend on the historical data for the uncertain day-ahead electricity prices. A case study is performed, and the resulting profit of the CHP producer is analyzed. The proposed operational strategy shows high reliability in the out-of-sample performance and a profit gain of the CHP producer, who is aware of the temperature dynamics in the heating network., QC 20230503

With the increasing integration of power plants into the frequency-regulation markets, the importance of optimal trading has grown substantially. This paper conducts an in-depth analysis of their optimal trading behavior in sequential day-ahead, intraday, and frequency-regulation markets. We introduce a probabilistic multi-product optimization model, derived through a series of transformation techniques. Additionally, we present two reformulations that re-frame the problem as a mixed-integer linear programming problem with uncertain parameters. Various aspects of the model are thoroughly examined to observe the optimal multi-product trading behavior of hydro power plant assets, along with numerous case studies. Leveraging historical data from Nordic electricity markets, we construct realistic scenarios for the uncertain parameters. Furthermore, we then proposed an algorithm based on the No-U-Turn sampler to provide probability distribution functions of cleared prices in frequency-regulation and day-ahead markets. These distribution functions offer valuable statistical insights into temporal price risks for informed multi-product optimal-trading decisions., Comment: 10 pages, 9 figures

The Spine Toolbox is open-source software for defining, managing, simulating and optimising energy system models. It gives the user the ability to collect, create, organise, and validate model input data, execute a model with selected data and finally archive and visualise results/output data. Spine Toolbox has been designed and developed to support the creation and execution of multivector energy integration models. It conveniently facilitates the linking of models with different scopes, or spatio-temporal resolutions, through the user interface. The models can be organised as a direct acyclic graph and efficiently executed through the embedded workflow management engine. The software helps users to import and manage data, define models and scenarios and orchestrate projects. It supports a self-contained and shareable entity-relationship data structure for storing model parameter values and the associated data. The software is developed using the latest Python environment and supports the execution of plugins. It is shipped in an installation package as a desktop application for different operating systems., QC 20220406

As the inverter-based generation replaces the conventional synchronous generators, it may also need to fill in the missing ancillary service support. One of these ancillary services is dynamic reactive power provision and voltage control. This paper analyzes optimal strategy of reactive and active fault-current support of the inverter-based generation leading to fast voltage recovery of the system. For the purpose of the analysis, new ramping active current controller able to emulate different behavior of active current injection is proposed. By optimizing its parameters for different case studies of the system, the conclusions about optimal behavior of the inverter based generation with respect to system parameters and operating conditions are drawn. It is observed that the optimal combination of active and reactive fault-current is the most sensitive to the dynamic load component penetration levels in the system. With the increasing penetration levels, the significance of active fault-current injection increases. The results show that with higher penetration levels of dynamic load component in the heavy load areas, the ramping down of the inverter-based generation active fault-current results in slower voltage recovery of the system. Following this conclusion, a recommendation on update of current European grid codes is proposed., QC 20220404

The planning of future power systems with high shares of renewable generation requires modelling large and complex systems over long time periods, resulting in models which are computationally heavy to solve. For this reason methods that can be used to decrease the size of power system dispatch models are needed. A common method in large scale planning models is to decrease the model size by increasing the size of the time steps. However, using larger time steps makes the representation of variability of renewable generation and load less accurate, which can affect the results from the model. In this paper, we investigate the possibility to use a power-based version of an economic dispatch model to decrease the model time resolution while getting results which are close to the original high-resolution model. We implement both power-based and the conventional, energy-based, versions of a dispatch model with different time resolutions, and show that the power-based model has better agreement with the high-resolution model, especially as the model time step increases. For example, using the power-based model gives more accurate results for wind power curtailment in a high-renewable scenario., QC 20220202

This paper presents ODIN, an open dispatch model for the Nordic power system. We begin by performing a survey of existing models, and conclude that no model which simulates the different price areas in the Nordic power system and is truly open exists. Existing models either lack data to do an out-of-the-box simulation which accurately represents the Nordic power system, rely on proprietary software, or have a more coarse representation of the Nordic region. In contrast, ODIN has the following properties: (1) It is developed completely in Python and can be solved with open-source optimization tools, thus using no proprietary software. (2) It includes all data needed to do yearly simulations for the Nordic power system, with 35 years of data for weather-dependent production such as hydro power and wind power. (3) It represents all Nordic price areas and has been validated to reproduce historical production and transfer patterns. This paper describes the methodology and structure of the model and illustrates its features with examples and a case study., QC 20220214

This paper presents power-based unit commitment (UC) formulations with N-l security constraints. Two different formulations are proposed, one with constant reserves within the hour and one with time-varying reserves. The formulations are compared to a conventional energy-based UC formulation using different examples. We show that the energy-based formulation does not ensure N-l security at all times within the hour, since it does not account for the power profile of units. In contrast, the proposed power-based formulations guarantee N-l security within the whole hour for a piecewise linear demand profile. The formulations are also evaluated using a 5-min economic dispatch based on a real load profile, simulating the real-time operation of the power system, showing that the power-based formulations also provide increased security in this case. Compared to using a power-based formulation with constant reserves, using time-varying reserves decreases the reserve cost while ensuring a similar level of security., QC 20230227

Actual hydropower systems often contain complex river systems, making simulations of hydropower systems computationally extensive. With the help of an Equivalent model, which is an artificial simpler hydropower system, the computational issue can be avoided. The Equivalent model aims to imitate the actual hydropower system, hence can be used for studies of large power systems with faster computational time. In this paper, different Equivalent models of hydropower systems in different periods and trading areas in Sweden have been computed, which are then evaluated and validated by comparing the hourly relative power generation difference. The relative power difference is 4.89% - 19.36%, depending on the period and trading area. Different Equivalent model performance over time indicates that the Equivalent parameters should change over time. By dividing a year appropriately, a well performing Equivalent can be obtained, which is shown by the Equivalent with low relative power difference., Part of proceedings: ISBN 978-1-6654-2052-5QC 20221025

The development of power system models relies on large data sets, the quality, and openness of which determine the models' accuracy and efficacy. There are numerous data sources publicly available, for the Nordic region though spread across diverse repositories and organised in different schemas. Their combination and cross-validation is a tedious process, usually undertaken by researchers or practitioners, in an ad hoc fashion. This paper identifies, compares, and validates various publicly available power systems data sets, pertaining to the Nordic region. Their quality, level of detail, granularity, and similar characteristics are highlighted, while the challenges of data warehousing procedures are addressed, for the purpose to be used in realistic power systems-related case studies., QC 20220617Part of proceedings: ISBN 978-166541008-3

The current energy transition needed to meet the world climate objectives is causing stability challenges in all the power systems. As a consequence, finding solutions that allow dealing with those frequency stability issues is critical to achieving the sustainability objectives. In this context, batteries can find new revenue opportunities by being part of the solution to this problem. This paper develops a mathematical model that provides the optimal bidding strategy and the most convenient operational planning for batteries participating in balancing markets. More specifically, this project is focused on the Swedish frequency markets whose minimum bid size is smaller than 5 MW. The proposed optimization problem is a two-stage stochastic mixed-integer and linear optimization from the battery operator's point of view that includes a novel step-by-step process for properly selecting the bid prices by the quantification of the risks, control costs and amortization of the battery. The originality of the work resides in the aforementioned process that allows risk assessment together with the linear modelling of paid-as-bid markets, commonly solved through non-linear problems. As a result, not only the profitability of this application for batteries is demonstrated, but it is also possible to observe the seasonal differences when it comes to revenue and power requirements. The model is tested with data from Sweden, but it is designed to be adjustable to other balancing markets., QC 20220818

This paper presents a novel methodological approach for the optimal day-ahead energy market bidding behavior of a cascaded hydropower plants (HPPs) portfolio in the sequential electricity markets. The understudy markets are day-ahead energy market and manual frequency restoration reserve (mFRR) markets in both capacity and energy setups. The introduction of the mFRR capacity market ensures transmission system operators (TSOs) about the availability of energy bids in the real-time market, which acts as binding constraints in the mFRR energy markets. As a determining factor, the active-time duration of mFRR energy bids is uncertain at the time of day-ahead bidding, which is modeled as the intervals in our robust optimization, while the electricity prices are considered as the scenarios in the stochastic optimization. Hence, we have proposed a novel stochastic adaptive robust optimization to address the bidding problem in the face of uncertainties accurately. The results show a considerable improvement compared to the conventional fully-stochastic approach in the case study of Swedish cascaded hydropower plants., QC 20220809

Sol och vindenergi erbjuder nu den billigaste nya elproduktionen i huvuddelen av världen, och den fortsätter att bli allt billigare. Expansionen globalt är mycket stor och vindkraft + solkraft producerade 2021 2894 TWh globalt vilket är mer än kärnkraften. Kärnkraften tangerar 2021 (2800.3 TWh) den nivå som producerades 2006 (2803.4 TWh) vilket var den historiskt maximala produktionen. Trenden är tydlig med en kraftigt expanderande förnybar sektor och en kärnkraftsproduktion som tidigare ökade starkt, 1970-2000, men där vissa nya reaktorer tillkommer men också många äldre stängs vilket totalt har lett till en relativt konstant global produktion. Utbyggnaden av vindkraften i Sverige sker utan subventioner efter det att priset på elcertifikaten närmat sig noll. I Sverige har de allt lägre kostnaderna för sol- och vindel gjort det ekonomiskt lätt att ersätta fossila bränslen i transportsektorn och rimligt att investera för att ersätta kol med vätgas i stålindustrin. Svenskt Näringsliv har presenterat slutsatser från en datormodell gjord av en konsult som hävdar att det vore ekonomiskt optimalt att bygga nya kärnkraftsreaktorer i Sverige. Den nya studien, som i juni 2022 uppdaterats med ytterligare ökad elkonsumtion till totalt 290 TWh/år för bland annat vätgasframställning, påstås vara en ”teknikneutral kostnadsminimering”. Optimering innebär (sidan 22-23): ”Precis som i tidigare scenarieanalys inom projektet Kraftsamling Elförsörjning utförs investeringsoptimering – den beräkning som bestämmer vilken uppsättning kraftverk, lagersystem och elledningar kraftsystemet bör ha för att uppnå lägsta möjliga totalkostnad”. Detta innebär att man låter programmet bestämma vilken kombination som ger lägsta möjliga kostnad. Det centrala är att det därmed är antaganden om data och kostnader samt programmets konstruktion som bestämmer resultatet. Om man, t ex, antar att kraftslag X är mycket billigt, så blir den givna slutsatsen att programmet väljer mycket av kraftslag X. Mycket ä, QC 20220811

Tomas Tangerås skriver i en replik på DN debatt 220708 under rubriken ”Dagens regler gynnar väderberoende elproduktion” ( https://www.dn.se/debatt/dagens-regler-gynnar-vaderberoende-elproduktion/ ) bland annat att: ”…. I stället gynnas väderberoende elproduktion på bekostnad av planerbar elproduktion. En orsak är att varje anläggning formellt uppfyller sitt leveranskrav om anläggningen producerar den kontrakterade mängden el för varje hel leveranstimme. Positiva och negativa obalanser som uppstår inom leveranstimmen tar ut varandra.” Min slutsats om systemkostnader (om man jämför vindkraft och kärnkraft) är att en subvention (oklart år vilket håll) ligger i storleksordningen tiondels ören på kWh. Men mer studier behöver göras för att få en mer korrekt uppfattning., QC 20220714

We propose a power-based unit commitment formulation with capacity and intra-hour ramp reserves for dealing with intra-hour wind power variability and uncertainty. Although the formulation has an hourly resolution, the intra-hour ramp requirements capture wind power ramp excursions with a time duration below one hour, and thus allows the formulation to consider intra-hourly wind variability and uncertainty. This increases the security of the formulation compared to using hourly ramp reserves and allows more efficient scheduling of units with high ramp rates. We test the formulation with different durations for the intra-hour reserves, and using both hourly and intra-hourly ramp reserves, to find the best reserve formulation. The formulations are evaluated using a 5-min economic dispatch, which simulates the real-time operation of the system, for hundreds of out-of-sample realizations of wind power production. The proposed formulations are then compared to two hourly stochastic formulations and a stochastic formulation with 5-min time resolution. The proposed formulations outperform the stochastic formulations in terms of security, showing that they provide a scheduling which is more robust against intra-hour wind power variations. The proposed formulations also outperform the hourly stochastic formulations in terms of total costs, giving a better trade-off between scheduling costs and security., Not duplicate with DiVA 1638601QC 20220707

This paper presents an electricity market that in-cludes day-ahead energy and manual frequency replacement reserve (mFRR) markets and consists of cascaded hydropower plants (HPs) offering their aggregated capacity to these markets. The proposed model is a two-stage bilevel offering strategy to show the hierarchical decision-making process in the European electricity market. The upper-level describes the day-ahead profit maximization optimization considering the opportunity cost of saving water which is controlled through the real-time dispatch in the operation day and mFRR capacity requirements imposed from TSO. In the lower-level, the mFRR energy market with their corresponding active-time duration is modeled to control the real-time discharge of water and upward or downward offering strategies. The new approach provides the flexibility for the planning and operational stages to define their own objective functions, maximize their profits and conserve the proper interaction between them through linking variables., Part of ISBN 9798350399660QC 20230802

This article presents a new approach for finding the optimal multimarket trading strategy of cascaded hydropower plants (HPPs) in the sequential electricity markets. These markets are day-ahead energy market, the market for frequency containment reserve in normal mode (FCR-N), and manual frequency restoration reserve markets for both energy production and capacity reserve. The active-time duration (ATD) of an mFRR energy offer is an important required parameter and it is uncertain at the time of day-ahead offer-function submission. Hence, we suggest a distributional regression approach for ATD modeling in an optimal multimarket setup. Also, a modified machine learning approach is proposed to generate price scenarios for the mFRR energy market taking into account uncertain ATD parameters. To illustrate our proposed approach, various numerical experiments are performed. Our numerical results show how proper modeling of ATD parameters can lead to a more realistic multimarket offer-function for cascaded HPPs. Furthermore, the results show how the inclusion of FCR-N and mFRR capacity markets change the optimal day-ahead offer-function., QC 20230706