Troms Kraft (Norway)

A deterministic reference tracking model predictive control (MPC) is in use at Skagerak Kraft for flood management of Lake Toke in Norway.An operational inflow estimate is used to predict the optimal gate opening at Dalsfos power station, with required constraints set by the Norwegian Water Resource and Energy Directorate (NVE).The operational inflow estimate is based on the meteorological forecast, and is uncertain; this may lead to broken concession requirements and unnecessary release of water through the floodgates.Currently not utilized, the meteorological uncertainty is quantified by an ensemble of possible weather forecasts.In this paper, quantified inflow uncertainty is studied and how this affects the operation of the current, deterministic MPC solution.Next, we develop an alternative, stochastic MPC solution based on multi objective optimization which directly takes the inflow uncertainty into consideration.A comparison of the results from both approaches concludes that the stochastic MPC solution seems to give better control by reducing the amount of water released through the flood gates.Furthermore, with less frequent update of the control signal, the benefit of the stochastic MPC is expected to increase.

Design of optimal operation and control of a run-of-river hydro power plant depends on good models for the elements of the plant. River reaches are often considered to be shallow channels with free surface flow. A typical model for such reaches thus use the Saint Venant model, which is a 1D model based on the mass and momentum balances. This combination of free surface and momentum balance makes the problem numerically challenging to solve. Here, the finite volume method with staggered grid is used to illustrate the dynamics of the river upstream from the Gronvollfoss run-of-river power plant in Telemark, Norway, operated by Skagerak Energi. A model of the same river in the Gronvollfoss power plant has been studied previously, but here the geometry of the river is changed due to new information from Skagerak Energi. The numerical scheme for solving the model has been further developed. In addition, the behavior of the dynamic model is compared to data from experiments, carried out on the Gronvollfoss run-of-river power plant. The essence of the experiments is to consider the time taken from an increase in the input volumetric flow, to a measured change in level in front of the dam at Gronvollfoss. The model is manual ly tuned by changin g the Strickler friction factor, the river length and the type of river slope/width (constant/varying) in order to fit the water level ahead of the Gronvollfoss dam from experimental data. Least squares model fitting is also used for the model with the constant slope and width of the river and this model shows good fitting after the manual tuning. The results of the improved model (numerically, tuned to experiments), is a model that can be further used for control synthesis and analysis.

We present a model of a purchaser of electricity in Norway, bidding into a wholesale electricity pool market that operates a day ahead of dispatch. The purchaser must arrange purchase for an uncertain demand that occurs the following day. Deviations from the day-ahead purchase are bought in a secondary market at a price that differs from the day-ahead price by virtue of regulating offers submitted by generators. Under an assumption that arbitrageurs are absent in these markets, we study conditions under which the purchaser should bid their expected demand and examine the two-period game played between a single generator and purchaser in the presence of a competitive fringe. In all our models, it is found that purchasers have an incentive to underbid their expected demand, and so the day-ahead prices will be below expected real-time prices. We also derive conditions on the optimal demand curve that purchasers should bid if the behavior of the other participants is unknown but can be modeled by a market distribution function.

In this paper, the application of adjustable speed hydro machines (ASH) has been discussed for enhancing power system stability in power networks. A direct comparison has been arranged between an ASH machine and a conventional synchronous machine. It has shown that by two dedicated rotor current regulators, the ASH machine is able to control the active and reactive power production quickly and accurately. The ASH concept represents an excellent possibility to get improved control with the network. With a more concise regulation, the power system may be utilised even better, still maintaining the necessary stability margin. This will also give an enhanced profitability for the generator owner. Furthermore, for these capabilities, being a part of the common term ancillary services, there is a potential market growing up.