The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services. In this study, a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration. The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation, consumption and heat storage units which are available in district heating systems.
Abstract-This paper presents a Hidden Markov Model (HMM) based method to predict the prices and trading volumes in the electricity balancing markets. The HMM are quite powerful in modelling stochastic processes where the underlying dynamics are not apparent. The proposed method provides both one hour and 12-36 hour ahead forecasts. The first is mostly useful to wind/solar producers in order to compensate their production imbalances while the second is important when submitting the offers to the day ahead markets. The results are compared to the ones from Markov-autoregressive model.
Abstract-The production scheduling of combined heat and power plants is a challenging task. The need for simultaneous production of heat and power in combination with the technical constraints results in a problem with high complexity. Furthermore, the operation in the electricity markets environment means that every decision is made with unknown electricity prices for the produced electric energy. In order to compensate the increased risk of operating under such uncertain conditions, tools like stochastic programming have been developed. In this paper, the short-term operation scheduling model of a CHP system in the day-ahead electricity market is mathematically described and solved. The problem is formulated in a stochastic programming framework where the uncertain parameters of dayahead electricity prices and the heat demand are incorporated into the problem in the form of scenarios. A case study is also performed with a CHP system operating in a district heating network and the value of heat storage capacity is estimated.
I. INTRODUCTIONThe short-term operation scheduling of a system of power plants is a decision making problem regarding how much power and by which units is going to be produced during a short time period in the future, usually one day to one week ahead. This is a typical optimization problem, called unit commitment and economic dispatch, which is faced by power producers in order to minimize their costs and maximize their profits. In the special case of combined heat and power (CHP) systems this problem becomes more complex since the production of both power and heat need to be scheduled. Traditionally CHP systems find application in cases where there is a demand for both power and heat like industry and district heating. Small CHP systems, called micro CHP, are also used in commercial and residential buildings to provide heating and cooling. Compared to conventional power plants, CHP systems achieve a higher overall efficiency, resulting in reduced fuel consumption and exhaust gas emissions.Various models have been proposed for the CHP shortterm production scheduling. The economic dispatch problem has been initially described and solved in [1], [2] and [3] where the problem is quadratic with linear constraints. In [4] a methodology based on dynamic programming and Lagrange relaxation is proposed. More recent works can be found in [5] and [6]. A comprehensive study of the various models and solutions that have been proposed for the CHP operation scheduling can be found in [7] and [8]. This paper describes a three-stage stochastic model with recourse which takes
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