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Optimal Control of Generation and Thermal Loads Using MPC


G. Ledva

Semester Thesis, FS12 (10141)

Up to recent years, electricity consumers were passive actors in the network who were allowed to consume any desired amount of power at any desired time. However, recent developments, including the increase in renewable sources as well as the liberalization of the electricity sector, are encouraging a more intelligent use of energy from the consumers side. In this context, the idea of controlling the consumption either via coercive signals (direct control) or via economic incentives (price based control) has emerged, and in many places has become everyday practice. Yet, control practices in this areas are far from consolidated. In this work we investigate the economic potential of exploiting the consumers' exibility for the purpose of self-balancing within a balance group (BG). Market mechanisms encourage balance groups not to sway from scheduled positions, which becomes a challenging objective from the BG perspective as the amount of uncertainties (intermittent generation, loads discrepancies with respect to the forecasts, etc.) increases. In order to prevent economic penalties, the BG will typically have to counteract these imbalances using "aggressive" generators, which, depending on the power generation mix, can be more expensive and more polluting than baseload generators. Thus the idea advanced in this work is to use exible loads instead of these generators and gauge the corresponding benets the BG attains from doing this. The work will start from an estimation of the constraints within which loads can be controlled, and end up in the formulation of a nite horizon, constrained, optimal control problem, whose solution determines the optimal generators' and exible loads' power injection setpoints. Real data from Dutch BGs will be used. This work is carried out within the framework of the European Project E-Price: http://www.eprice- iii


Type of Publication:

(13)Semester/Bachelor Thesis

R. Vujanic

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2012:IFA_4360
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