TY - BOOK

T1 - Operations Management in Short Term Power Markets

AU - Heide-Jørgensen, Ditte Mølgård

PY - 2016

Y1 - 2016

N2 - Electricity market models have often been modelled as deterministic or at mosttwo-stage stochastic models with an hourly time resolution. This thesis looks intopossible ways of extending such models and formulating new models to handleboth higher time resolution than hourly and stochastics without losing computationaltractability. The high time resolution is crucial to correctly describe renewables,such as wind power, and capture how they affect the system and thesystem costs, since they are often fluctuating and hard to predict, also within thehour.The thesis consists of four chapters. The first is an introduction to the backgroundfor the work with stochastic electricity market models with a high timeresolution. It is followed by three self-contained chapters.The second chapter Short-term balancing of supply and demand in an electricitysystem: forecasting and scheduling is on a balancing market model like in the Nordiccountries with high time resolution, and it takes extensive balancing rules intoconsideration. We look into how wind forecast errors can be handled in a systemwith a large and increasing amount of wind power and at what costs. The projectwas done in collaboration with Jeanne Aslak Petersen, a PhD student at AarhusUniversity and the Danish TSO Energinet.dk, and the chapter is identical to thepublished paper Petersen et al. (2016) except that the reference list is part of thecommon reference list for the thesis.The third chapter A dynamic programming approach to the ramp-constrained intrahourstochastic single-unit commitment problem considers a real-time market setup.We describe two stochastic multi-stage single-unit commitment model in whichcommitment decisions are made on an hourly basis and dispatch decisions aremade on a higher time resolution, e.g. 5 minutes. The stochastic input is the electricityprice modelled as a time inhomogenous Markov chain that the power produceruses to maximise profits. To maintain computational tractability with suchhigh time resolution and stochastics the model is solved with dynamic programming.The two models differ in the way the dynamic programming algorithmhandles the integer variables leading to two different non-anticipativity assumptions.In the fourth chapter Open- and closed-loop equilibrium models for the day-aheadand balancing markets we look into how power producers act in market whichis not perfectly competitive. Specifically, we look into the possibility of exercising market power when the electricity market consists of two sequential markets– the day-ahead market and the balancing market – and some power producershave access to both markets whereas others only can participate in the firstmarket. The model is formulated with both an open-loop and closed-loop approach,and we find that the solution to the more realistic, but also computationallyharder closed-loop model differs substantially from the open-loop solution.Again the day-ahead market is assumed to have hourly time resolution, but thebalancing market has a higher time resolution, e.g. 5 minutes.

AB - Electricity market models have often been modelled as deterministic or at mosttwo-stage stochastic models with an hourly time resolution. This thesis looks intopossible ways of extending such models and formulating new models to handleboth higher time resolution than hourly and stochastics without losing computationaltractability. The high time resolution is crucial to correctly describe renewables,such as wind power, and capture how they affect the system and thesystem costs, since they are often fluctuating and hard to predict, also within thehour.The thesis consists of four chapters. The first is an introduction to the backgroundfor the work with stochastic electricity market models with a high timeresolution. It is followed by three self-contained chapters.The second chapter Short-term balancing of supply and demand in an electricitysystem: forecasting and scheduling is on a balancing market model like in the Nordiccountries with high time resolution, and it takes extensive balancing rules intoconsideration. We look into how wind forecast errors can be handled in a systemwith a large and increasing amount of wind power and at what costs. The projectwas done in collaboration with Jeanne Aslak Petersen, a PhD student at AarhusUniversity and the Danish TSO Energinet.dk, and the chapter is identical to thepublished paper Petersen et al. (2016) except that the reference list is part of thecommon reference list for the thesis.The third chapter A dynamic programming approach to the ramp-constrained intrahourstochastic single-unit commitment problem considers a real-time market setup.We describe two stochastic multi-stage single-unit commitment model in whichcommitment decisions are made on an hourly basis and dispatch decisions aremade on a higher time resolution, e.g. 5 minutes. The stochastic input is the electricityprice modelled as a time inhomogenous Markov chain that the power produceruses to maximise profits. To maintain computational tractability with suchhigh time resolution and stochastics the model is solved with dynamic programming.The two models differ in the way the dynamic programming algorithmhandles the integer variables leading to two different non-anticipativity assumptions.In the fourth chapter Open- and closed-loop equilibrium models for the day-aheadand balancing markets we look into how power producers act in market whichis not perfectly competitive. Specifically, we look into the possibility of exercising market power when the electricity market consists of two sequential markets– the day-ahead market and the balancing market – and some power producershave access to both markets whereas others only can participate in the firstmarket. The model is formulated with both an open-loop and closed-loop approach,and we find that the solution to the more realistic, but also computationallyharder closed-loop model differs substantially from the open-loop solution.Again the day-ahead market is assumed to have hourly time resolution, but thebalancing market has a higher time resolution, e.g. 5 minutes.

UR - https://soeg.kb.dk/permalink/45KBDK_KGL/fbp0ps/alma99122244760505763

M3 - Ph.D. thesis

BT - Operations Management in Short Term Power Markets

PB - Department of Mathematical Sciences, Faculty of Science, University of Copenhagen

ER -