Probabilistic methods have been largely employed in the past by vertically integrated utilities for the adequacy assessment of power systems, especially for planning purposes. In the last twenty years, with the introduction of deregulated structures, the security assessment of the working point defined by the energy markets has become one of the main tasks of any System Operator (SO), in the framework of the so-called "day-ahead operational planning". The experience previously gathered in the use of probabilistic methods has proved to be very useful, so an increasing number of SOs is reinforcing, with probabilistic tools, the traditional deterministic criteria employed to validate the ex-ante dispatching. Very challenging, promising and discussed, but not yet well-established, is the use of probabilistic tools for real-time decision-support and advanced dispatching; the computational complexity of many time-consuming algorithms has constituted for years a crucial barrier, but nowadays the availability of cheap and fast computers discloses new opportunities also for the on-line security assessment. In this field, the demand for robust and quick decision-making tools, able to support the activities of control rooms, is significant. In fact, the separation of supply, transmission and system supervision has not yet resulted in more stressed operating conditions, but also compelled the SO to justify the real-time selection of balancing resources both from a technical and an economical point of view. That consideration results in a strong need for formalizing in open procedures the skills previously condensed in the experience of operators. In the present paper, a probabilistic technique for real-time security assessment and operational decision-making is proposed and described. The use of a power system simulator, based on a sequential Monte Carlo technique, is applied to advance dispatching purposes, in order to alert the SO if the system reliability is about to decrease, thus anticipating critical contingencies and supporting the control room to find the most cost-effective corrective action. More in detail, starting from the present behaviour of the power system, provided by a state estimator, the simulator investigates what could happen in the following hours if no significant amendment is applied to the dispatching resulting from the market, as corrected by the contingencies already occurred in the previous hours. The software calculates the risk indices associated to this baseline simulation and indicates to the SO the main weakness points of the power system, assessing the operational security both of transmission network and generating park. Then the tool proposes to the SO quick redispatching procedures able to enhance the system reliability, preventing cascadings and load shedding events; the operator is free to start new simulations, in order to investigate the effectiveness and the cost of the actions suggested by the software, as well as the outcome of corrections recommended by his experience. Furthermore, the tool can help the SO to size the additional spinning reserve to be acquired in the very next infra-daily session of the balancing market. A case study relevant to the IEEE Reliability Test System (RTS96) is shown and discussed.
A Monte Carlo approach to advanced load dispatching in multi-area deregulated systems
POLI, DAVIDE
2011-01-01
Abstract
Probabilistic methods have been largely employed in the past by vertically integrated utilities for the adequacy assessment of power systems, especially for planning purposes. In the last twenty years, with the introduction of deregulated structures, the security assessment of the working point defined by the energy markets has become one of the main tasks of any System Operator (SO), in the framework of the so-called "day-ahead operational planning". The experience previously gathered in the use of probabilistic methods has proved to be very useful, so an increasing number of SOs is reinforcing, with probabilistic tools, the traditional deterministic criteria employed to validate the ex-ante dispatching. Very challenging, promising and discussed, but not yet well-established, is the use of probabilistic tools for real-time decision-support and advanced dispatching; the computational complexity of many time-consuming algorithms has constituted for years a crucial barrier, but nowadays the availability of cheap and fast computers discloses new opportunities also for the on-line security assessment. In this field, the demand for robust and quick decision-making tools, able to support the activities of control rooms, is significant. In fact, the separation of supply, transmission and system supervision has not yet resulted in more stressed operating conditions, but also compelled the SO to justify the real-time selection of balancing resources both from a technical and an economical point of view. That consideration results in a strong need for formalizing in open procedures the skills previously condensed in the experience of operators. In the present paper, a probabilistic technique for real-time security assessment and operational decision-making is proposed and described. The use of a power system simulator, based on a sequential Monte Carlo technique, is applied to advance dispatching purposes, in order to alert the SO if the system reliability is about to decrease, thus anticipating critical contingencies and supporting the control room to find the most cost-effective corrective action. More in detail, starting from the present behaviour of the power system, provided by a state estimator, the simulator investigates what could happen in the following hours if no significant amendment is applied to the dispatching resulting from the market, as corrected by the contingencies already occurred in the previous hours. The software calculates the risk indices associated to this baseline simulation and indicates to the SO the main weakness points of the power system, assessing the operational security both of transmission network and generating park. Then the tool proposes to the SO quick redispatching procedures able to enhance the system reliability, preventing cascadings and load shedding events; the operator is free to start new simulations, in order to investigate the effectiveness and the cost of the actions suggested by the software, as well as the outcome of corrections recommended by his experience. Furthermore, the tool can help the SO to size the additional spinning reserve to be acquired in the very next infra-daily session of the balancing market. A case study relevant to the IEEE Reliability Test System (RTS96) is shown and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
