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With the increasing integration of renewable power and electric vehicles, stochastic power fluctuations(stochastic excitations) have attracted much attention. The theory of nonlinear stochastic dynamics and control in Hamiltonian formulation has offered many useful tools to analyze the stochastic dynamics of multi-machine power systems. However, the quasi Hamiltonian model should be set up before...
The large-scale integration of stochastic generation requires additional operating reserves to cope with the uncertainty in power system operation, due to the large forecast error with existing methodologies. Previous research shows that allocating power reserves dynamically according to conditional distribution of power forecast error would benefit the generation scheduling in day-ahead electricity...
This paper describes a model for optimal scheduling of hydroelectric systems for a price-taking producer selling energy and capacity to separate markets. The model is based on a combination of stochastic dynamic programming (SDP) and stochastic dual dynamic programming (SDDP), and treats inflow to reservoirs and energy prices as stochastic variables. It allows sales of capacity at a deterministic...
Global targets for reduced CO2 emissions along with guaranteed energy supply have motivated governments to take drastic steps towards the large-scale integration of Renewable Energy Sources (RES). With the levels of wind integration constantly increasing, more sophisticated methods are required to ensure the economic, secure and sustainable energy provision, especially in insular power systems, where...
During the recent years, power industries have been facing significant changes due to deregulation and liberalization of the energy markets and increase of the installed capacity of renewable energy sources. These factors directly affect the transmission network planning (TNP) task and inspire a search for new, more adequate methods. This paper compares a deterministic method — the economic intervals...
This paper presents a method to generate new samples of the stochastic phenomena affecting the power system, notably the consumption, uncontrollable renewable generation and hydro inflows. The method aims at reproducing characteristics of the time series observed in historical data: their seasonality, temporal correlation, marginal distribution and spatial correlations. It has been implemented into...
We test the stochastic dual dynamic programming (SDDP) approach on a system an order of magnitude larger than previously published studies. The analysis shows that the SDDP-approach can be applied to very large system sizes to solve the hydropower scheduling problem through formal optimisation and obtain individual decision variables for every reservoir. However, this can be very time-consuming compared...
Owing to the massive deployment of renewable power production units over the last couple of decades, the use of stochastic optimization methods to solve the unit commitment problem has gained increasing attention. Solving stochastic unit commitment problems in large-scale power systems requires high computational power, as stochastic models are dramatically more complex than their deterministic counterparts...
This paper presents a hybrid stochastic and deterministic unit commitment (SDUC) algorithm which takes into account the variability of wind generation. The proposed scheme is modeled as a chance constrained optimization, where the system ramping capability, required to meet changes in demand and variable generation, is also considered. The dayahead predicted net load probability density function (PDF)...
In this study, we use a stochastic representation of wind for medium/long-term planning problems that are associated with the operation of hydro-thermal systems. The stochastic dual dynamic programming (SDDP) technique is used in this study. Synthetic wind and hydrological scenarios are generated using a periodic autoregressive model (PAR (p)). This algorithm has wide applicability in countries with...
The Brazilian power system is mainly composed of hydroelectric generation. Due to the stochasticity of inflows each hydroelectric plant receives an assured energy certificate, also known as physical guarantees. In general, the assured energy certificates correspond to the energy that each plant can produce at a 95% confidence level., They also represent the maximum energy each hydro unit can contract...
We propose a novel stochastic planning model that considers investment in conventional assets as well as in Soft Open Points, as a means of treating voltage and thermal constraints caused by the increased penetration of renewable distributed generation (DG) sources. Soft Open Points are shown to hold significant option value under uncertainty; however, their multiple value streams remain undetected...
When energy storage units, such as batteries, are installed to support photovoltaics and defer power system upgrades they are inactive or only partially used most of time. Their unused capacities could be used to provide frequency control, allowing them to generate additional revenues. However, the challenge is to decide how much of their energy and power capacities to allocate to either service....
This paper presents a multi-stage balancing market under uncertainty with a rolling horizon for European Market Structures. The goal is to settle the real-time power imbalances (i.e., discrepancies between consumption and production) and alleviate congestion by adjusting the generation schedules while respecting the network and generators constraints. The power imbalances are predicted over a defined...
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