| 1. |
- Biel, Martin
(författare)
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Distributed Stochastic Programming with Applications to Large-Scale Hydropower Operations
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Stochastic programming is a subfield of mathematical programming concerned with optimization problems subjected to uncertainty. Many engineering problems with random elements can be accurately modeled as a stochastic program. In particular, decision problems associated with hydropower operations motivate the application of stochastic programming. When complex decision-support problems are considered, the corresponding stochastic programming models often grow too large to store and solve on a single computer. This warrants a need for parallel approaches to enable efficient treatment of large-scale stochastic programs in a distributed environment. In this thesis, we develop mathematical and computational tools to efficiently store and solve distributed stochastic programs. First, we present a software framework for stochastic programming implemented in the Julia programming language. A key feature of the framework is the support for distributing stochastic programs in memory. Moreover, the framework includes a large set of structure-exploiting algorithms for solving stochastic programming problems. These algorithms are based on the classical L-shaped, progressive-hedging, and quasi-gradient algorithms and can be run in parallel on distributed stochastic programs. The distributed performance of our software framework is improved by exploring algorithmic innovations and software patterns. We present the architecture of the framework and highlight key implementation details. Finally, we provide illustrative examples of stochastic programming functionality and benchmarks on large-scale problems. Then, we pursue further algorithmic improvements to the distributed L-shaped algorithm. Specifically, we consider the use of dynamic cut aggregation. We develop theoretical results on convergence and complexity and then showcase performance improvements in numerical experiments. We suggest several aggregation schemes that are based on parameterized selection rules. In brief, cut aggregation can bring major performance improvements to L-shaped algorithms in distributed settings. Next, we consider a fast smoothing scheme for large-scale stochastic programming. We derive a smooth approximation of the subproblems in the quasi-gradient algorithm. This allows us to utilize modern acceleration methods for gradient descent. We derive problem-dependent approximation bounds and convergence properties and note a trade-off between accuracy and speed. We then pose a hybrid procedure that is both fast and accurate and show that it is competitive with the L-shaped method on large-scale benchmarks. Finally, we consider applications to hydropower operations. We consider three case studies in the Swedish river Skellefteälven. The day-ahead planning problem involves specifying optimal order volumes in a deregulated electricity market, without knowledge of the next-day market price, and then optimizing the hydropower production. We provide a detailed introduction to the day-ahead model and explain how it can be implemented in our framework. Using a sample-based algorithm that internally relies on our structure-exploiting solvers, we obtain tight confidence intervals around the optimal solution of the day-ahead problem. We then consider a maintenance scheduling problem as a variation of the day-ahead problem. Last, we consider a capacity expansion problem with a long planning horizon.
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| 2. |
- Tomasson, Egill, 1986-
(författare)
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Impact of High Levels of Variable Renewable Energy on Power System Generation Adequacy : Methods for analyzing and ensuring the generation adequacy of modern, multi-area power systems
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The generation adequacy of electricity supply has been an ongoing concern since the restructuring of the industry. Ensuring generation adequacy was a rather straightforward task in the era of natural monopolies. Whose responsibility was it to ensure generation adequacy as the industry became deregulated and more fragmented? Who is willing to finance rarely used generating units? After decades of experience with the competitive electricity market, the question of whether market forces alone are sufficient to ensure generation adequacy still remains.Recent energy policies have moreover set a goal of a high share of renewable energy in electricity markets. The presence of high levels of renewable generation makes the supply side of the market more uncertain. This volatility in energy production induces volatility in energy prices which means that the revenue stream of conventional generating technologies is more uncertain than it has traditionally been. This can even deteriorate the economics of some generators to the point where they exit the electricity market. The installed capacity of dispatchable generation can therefore be reduced.These developments bring up the question of whether the generation adequacy of modern and future, deregulated and highly variable power systems is ensured. This dissertation focuses on modeling the generation adequacy of modern power systems with a high penetration of variable renewable energy sources. Moreover, the dissertation looks at some solutions with the aim of ensuring the generation adequacy of such systems through various means such as coordinated reserves, energy storage as well as utilizing the flexibility of the demand side of the market.The models developed in this dissertation are verified using well-known test systems as well as through large-scale analysis of real-world systems. Aside from focusing on the simulation of power systems, the developed models moreover focus on achieving high computational efficiency. This is done through means such as advanced Monte Carlo simulation and optimization methods that apply decomposition to speed up the simulations.
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| 3. |
- Blom, Evelin
(författare)
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Hydropower Area Equivalents : Reduced Models for Efficient Simulation of Large-Scale Hydropower Systems
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With over 4000 TWh yearly electricity production worldwide, hydropower plays an important role in many power systems. Unlike many other renewable energy sources, hydropower has a certain degree of controllability and high levels of flexibility over several time scales. This flexibility is estimated to be integral for the transition of the energy systems towards more variable renewable energies and thus reducing greenhouse gas emissions. Given the important role that hydropower currently plays and is expected to play in future power systems, accurate models of hydropower are vital. As hydropower electricity production is a non-convex function of the discharge with for example non-linear head dependencies and forbidden zones of operation, detailed models of real hydropower systems quickly become computationally heavy. Even linear models with high numbers of interconnected stations are often too complex for large-scale power system models. For this reason, reduced or aggregated models of hydropower are commonly used to simulate its operation in different power system models. Due to the temporal and spatial connections in many hydropower systems with large rivers, the aggregation of hydropower can pose significant challenges. This means that aggregation from historical data might not be good enough to accurately simulate the hydropower operation. However, accurate reduced models of hydropower are still needed for long-term current and future studies of energy systems worldwide. In this thesis, the basic assumption is that the simplified reduced hydropower model should mimic the real hydropower operation. Thus, instead of aggregating the existing hydropower stations within a certain geographical area, one computes a new hydropower area Equivalent model with the aim to match the simulated power production of a more Detailed model of the real hydro system in that area. In this work, the area Equivalent models are calculated by computing the model parameter values. Here, this is mainly done based on a bilevel optimization problem formulation. In this thesis, different methods to compute the area Equivalents are proposed together with different model formulations and bilevel problem formulations. These are all compared using case studies of Swedish hydropower systems. Moreover, a Baseline aggregation method is outlined and compared to the developed area Equivalents. The studies presented in this thesis highlight the potential trade-offs in the accuracy of the area Equivalent model. Some problem formulations give a higher accuracy in hourly power production, others in peak power production or total power production over the simulation period. All area Equivalents perform better than the Baseline aggregation. In general, the average error in hourly power production is reduced by 50% using the area Equivalent compared to the Baseline aggregation. Moreover, they all successfully reduce the simulation time compared to the reference Detailed model with over 96%.
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| 4. |
- Khodadadi, Abolfazl
(författare)
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Electricity Market Design Strategies for Hydro-dominated Power Systems : Exploring Optimal Bidding, Planning, and Strategic Operation through Various Market Design Strategies
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The existing wholesale power markets in Nordic countries play a vital role in ensuring the planned balance between supply and demand. However, these markets do not guarantee real-time operational security of the power system. This responsibility falls on the transmission system operator (TSO), who balances consumption and generation in real-time to maintain a secure state.To address these issues, a series of research studies have been performed in this thesis to delve into the intricacies of Nordic balancing markets and propose strategies to enhance their efficiency and effectiveness. These studies have been conducted around the hydropower units as the main generation sources in the Nordic electricity markets. These studies recognize the potential benefits of versatile balancing markets and increased trade of flexible resources with Continental Europe. Additionally, the research results shed light on the optimal bidding strategies for hydropower plants (HPPs) in the day-ahead energy and manual frequency restoration reserve (mFRR) markets. HPPs play a crucial role as a flexible energy source, and their participation in these markets requires careful planning and decision-making. The studies consider various factors such as market rules, mFRR capacity market, future electricity prices, and the impact of active-time duration of balancing energy market offers on revenue generation. This inclusion provides a more realistic revenue portfolio for the operators based on the possibility of not being dispatched in the balancing market. Furthermore, the research explores the concept of flexible stochastic scheduling strategies in hydropower-dominated energy markets. By considering day-ahead energy markets, mFRR markets, and the interaction between different market setups. These strategies provide the necessary flexibility for both the planning and operational stages. The aim is to maximize the profits of the hydropower units while addressing the opportunity cost of saving water and meeting the mFRR capacity requirements imposed by the TSO. Participation in new market setups is an increasingly interesting framework for the operator after the recent introduction of those markets and the results of this section help them to form more profitable decision-making frameworks for their assets. Moreover, the optimal strategic portfolio assessment of HPPs in a multi-settlement market is discussed. Recognizing the increasing electricity prices and the growing penetration of renewable energy resources, these studies leverage bilevel programming problems to model the strategic behavior of HPPs in day-ahead and frequency containment reserve markets. The proposed approaches aim to enhance decision-making processes, promote market efficiency, and enable effective asset management in a dynamic and evolving energy landscape to make more informed multi-market trading decisions. Also, the research examines the dimensioning of frequency restoration reserves in a multi-area power system, specifically focusing on the Nordic case study. By adopting a sequential dimensioning methodology and employing chance-constrained optimization, the studies allocate reserves based on system needs, optimize line flows, and reduce total reserve requirements. The results highlight the potential for sharing reserves among bidding zones in the Nordic synchronous area, contributing to a more efficient and coordinated power system operation.Lastly, a thorough investigation has been performed to assess the effectiveness of the current contract-for-difference contracts as the main support schemes for the development of new renewable energy assets. Case studies have been conducted to demonstrate quantitatively the pros and cons of different proposals and provide new hints for policy-makers about their future decisions.
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| 5. |
- Nycander, Elis
(författare)
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Power System Operation Planning and Wind Power Curtailment : Efficient Methods for Power System Scheduling and Integration Studies of Variable Renewable Energy
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- To reduce carbon dioxide emissions, variable renewable energy (VRE) sources are replacing conventional fossil-based power plants for electricity generation. Due to the variability and uncertainty of weather dependent VRE sources, there can be situations when it is not possible to accommodate all the available VRE production, and VRE sources have to be curtailed. The need to curtail VRE production can arise, among other reasons, due to low electricity demand, lack of transmission capacity, or when operational security requires conventional units to remain online to provide intertia or reserves for balancing production and consumption. Managing VRE curtailment and integrating VRE sources into power systems in an efficient manner require tools for long-term power system planning and short-term power system operation planning, e.g., day-ahead scheduling which is handled by electricity markets. This thesis develops tools for both long-term and short-term power system planning, with a focus on estimating the need for VRE curtailment in future power systems and methods that achieve efficient operation of power systems by allowing VRE curtailment. Regarding long-term power system planning, an open source dispatch model for the Nordic power system, ODIN, is developed and used to assess the future need for VRE curtailment arising from wind power expansion mostly in the north of Sweden. Regarding short-term power system operation, further developments of the previously proposed power-based formulation for unit commitment (UC) are made, extending the formulation to include reserves which can better deal with wind power variability and uncertainty, as well as contingencies such as line and generator outages. Also, different situations when VRE curtailment can be efficient and lead to reduced system costs and carbon dioxide emissions are investigated, and an open source model for generating realistic wind power production scenarios for use in UC formulations is developed. Finally, a power-based version of ODIN is implemented to investigate the benefits of using the power-based formulation for production cost models used for long-term power system planning.The methods and models developed in this thesis can contribute to more efficient long-term planning and short-term operation of power systems, particularly in the Nordic region. Excessive VRE curtailment should be avoided through efficient long-term planning, but in the short term the flexibility of VRE production should be used to operate the power system in a way that minimizes system costs.
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| 6. |
- Shinde, Priyanka, 1993-
(författare)
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Efficient Trading in the Short-term Electricity Markets for Integration of Renewable Energy Sources : Multistage Stochastic and Agent-based Modeling Approaches for Continuous Intraday Electricity Market
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis investigates the role of different short-term electricity market design aspects that can facilitate better coordination of resources within the power system. The work also emphasizes on better cross-border integration of the short-term markets to improve the market liquidity, competition, social welfare, and flexibility in the system, which is essential for facilitating the integration of renewable sources. Apart from the policy design issues, the thesis also focuses on developing several mathematical models to support algorithmic trading decisions in short-term markets with various sources of stochasticities. The models proposed in this thesis enable improved trading decisions closer to real-time both for the production and consumption portfolio. The work presented in this thesis encompasses the short-term electricity markets with a primary focus on intraday electricity markets. The contributions of this work are in two directions, one is from the perspective of the trader in the intraday market. In this direction of the work, the aim was to develop optimization models to support algorithmic decision-making for generation and consumption portfolios. To this end, multistage stochastic programming problems have been developed to model cross-border continuous intraday (CID) trading for a price-taking virtual power plant with hydropower, wind power, and thermal power assets. The order clearing in the CID market is enabled by the two presented models, namely the Immediate Order Clearing and the Partial Order Clearing models. Further advancements in the multistage model has been achieved by proposing a bilevel model to tackle the problem of unit commitment of thermal power plant in the continuous intraday market. The lower level of the model accounts for the continuous market clearing considering for the minimum generation level of the thermal power plant. In this model, the virtual power plant is able to post its own prices in the intraday market. The resulting multistage stochastic programming problem with integer variables is tackled by Stochastic Dual Dynamic integer Programming algorithm.For the consumption portfolio, the participation of an electric vehicle aggregator in the intraday and balancing market is modeled as a multistage stochastic programming problem. Intraday markets allow the electric vehicle aggregator to trade furtherbased on their updated forecasts of consumption and price development in the market. The response of the electric vehicle aggregator to the prices in the market helps the power system tobetter manage the imbalances that might be injected by the intermittent generation sources. The algorithmic contribution in this work includes the deployment of randomized progressive hedging which was found to be faster than the conventional progressive hedging algorithm. Furthermore, the performance was accelerated by a parallel randomized progressive hedging algorithm and an asynchronous version of the randomized progressive hedging algorithm is leveraged to speed up the multistage model of electric vehicle aggregator trading.The other direction of the work is from the point-of-view of policymakers where an open-source agent-based model is proposed to model the cross-border continuous intraday electricity market. In this model, the trading behavior of different agents, including renewable, thermal power producers, storage, and consumers, in a cross-border Continuous Intraday market is simulated. The continuous market clearing is performed by a market operator agent. Two capacity calculation methods, Available Transfer Capacity, and Flow-based Market Coupling are availed to compute the cross-border transmission capacities. The agents are enabled to trade for multiple delivery products simultaneously in the CID market. Furthermore, the agents can choose between two different trading strategies, naive and modified trader adaptive aggressiveness, to decide the price-volume curves they post in the CID market. To simulate a realistic trading behavior, a user-defined parameter, switch, is introduced for the storage and thermal agents to allow them to choose the time-instant in the trading timeline when the traders can switch from trading towards increasing their profits to considering their ramping constraints in the CID market. The role of better forecasts of imbalance prices in deciding order prices and thereby the transaction prices in the CID market is also discussed.Ultimately, a forward-looking mechanism is proposed for the system operator to dispatch generators to activate their up- and down-regulation bids on the basis of having lowest expected costs, taking into account both their production costs and potential deviations from nominated outputs. The proposed method has been mathematically applied to compare three imbalance pricing models.
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