Flexible Operation of Industrial Processes Acting as Power Reserves

Harvesting energy from renewable resources, such as wind and sun, is our priority. Wind power installed capacity in the UK and Nordic systems is increasing dramatically in recent years. However, one cannot precisely predict renewable energy output: if wind stops blowing, turbines don’t produce electricity. Moreover, we expect to receive power whenever we switch on or plug in electrical appliances. Since electricity cannot be stored efficiently, reserves must be available to continuously match the difference between generation and consumption. The number of occasions in which not enough reserves are available is growing because of renewable generation, increasing the risk of blackout. Conventional generators (e.g. gas-fired power stations) can control their power output to keep the frequency as close as possible to 50 Hz. This poster concentrates on flexible use of industrial plants, which can vary their electricity consumption and act as reserves whenever an imbalance arises. However, since flexibility is only a by-product of the plant, special care is devoted to assure stable and safe operation of the main industrial production: for instance, a plant that uses electricity to liquefy metal at high temperatures may reduce its power consumption for some time, provided that the metal doesn’t solidify. Industrial load flexibility is the largest unexploited resource in power system reliability: frequency control schemes must be revisited in light of load participation. The aim of this research is to prove that flexibility of industrial plants allows for more renewable energy integration while preserving supply stability

Frequency Restoration Reserve Control Scheme with Participation of Industrial Loads

In order to accommodate larger amounts of renewable energy resources, whose power output is inherently unpredictable, there is an increasing need for frequency control power reserves. Loads are already used to provide replacement reserves, i.e. the slowest kind of reserves, in several power systems. This paper proposes a control scheme for frequency restoration reserves with participation of industrial loads. Frequency restoration reserves are required to change their active power within a time frame of tens of seconds to tens of minutes in response to a regulation signal. Industrial loads in many cases already have the capacity and capability to participate in this service. A mapping of their process constraints to power and energy demand is proposed in order to integrate industrial loads in existing control schemes. The proposed control scheme has been implemented in a 74-bus test system. Dynamic simulations show that industrial loads can be successfully integrated into the power system as frequency restoration reserves. © 2013 IEEE

Monitoring and management of power transmission dynamics in an industrial smart grid

This article is a position paper whose purpose is to give the context for presentations in a special session at PowerTech 2013. The special session is being proposed by the EU FP7 Real-Smart Consortium, a Marie Curie Industry-Academic Pathways and Partnerships project. The paper gives an overview of topics on modeling, monitoring and management of power transmission dynamics with participation from large industrial loads. © 2013 IEEE

Model predictive control for power system frequency control taking into account imbalance uncertainty

© IFAC.Model predictive control (MPC) is investigated as a control method for frequency control of power systems which are exposed to increasing wind power penetration. For such power systems, the unpredicted power imbalance can be assumed to be dominated by the fluctuations in produced wind power. An MPC is designed for controlling the frequency of wind-penetrated power systems, which uses the knowledge of the estimated worst-case power imbalance to make the MPC more robust. This is done by considering three different disturbances in the MPC: one towards the positive worst-case, one towards the negative worst-case, and one neutral in the middle. The robustified MPC is designed so that it finds an input which makes sure that the constraints of the system are fulfilled in case of all three disturbances. Through simulations on a network with concentrated wind power, it is shown that in certain cases where the state-of-the-art frequency control (PI control) and nominal MPC violate the system constraints, the robustified MPC fulfills them due to the inclusion of the worst-case estimates of the power imbalance

Applying model predictive control to power system frequency control

Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) controller, and simulations show that the MPC improves frequency deviation and control performance. © 2013 IEEE

A profit model for spread trading with an application to energy futures

This paper proposes a profit model for spread trading by focusing on the stochastic movement of the price spread and its first hitting time probability density. The model is general in that it can be used for any financial instrument. The advantage of the model is that the profit from the trades can be easily calculated if the first hitting time probability density of the stochastic process is given. We then modify the profit model for a particular market, the energy futures market. It is shown that energy futures spreads are modeled by using a meanreverting process. Since the first hitting time probability density of a mean-reverting process is approximately known, the profit model for energy futures price spreads is given in a computable way by using the parameters of the process. Finally, we provide empirical evidence for spread trades of energy futures by employing historical prices of energy futures (WTI crude oil, heating oil, and natural gas futures) traded on the New York Mercantile Exchange. The results suggest that natural gas futures trading may be more profitable than WTI crude oil and heating oil due to its high volatility in addition to its long-term mean reversion, which offers supportive evidence of the model prediction. --futures spread trading,energy futures markets,mean-reverting process,first hitting,time probability density,profit model,WTI crude oil,heating oil,natural gas