Abstract
The paper presents a methodology for the analysis of just-in-time production systems that are expected to deliver a fixed quantity of parts to its customers on a periodical basis, and whose equipment is submitted to random failure and repair processes. The methodology is based on the determination of the density function of T-H, the cumulated halting time of the production system between deliveries. The paper firstly shows how this function can be obtained from the internal structure of the system and individual equipment failure processes. Then, it shows how the reliability of the deliveries, and several production costs, e.g., extra work, delivery failures penalties, loss of sales profit, and safety stocks, may be assessed using this function. The practical application and usefulness of the methodology is illustrated in the final part of the paper for a typical production system of the automotive industry.

Abstract
Even in a liberalized environment, managing the security of supply associated to the generating system continues to be a major task of the System Operators. The increased use of renewable energy, in particular wind power, adds new challenges to the process, namely in countries like Portugal and Spain, where strong investments in wind power have been done and are foreseen for the next years. In order to tackle this issue, REN (the Portuguese TSO), REE (the Spanish TSO) and INESC Porto (a RandD institute) joined together to develop a project where Monte Carlo simulation is used to evaluate the risk associated with specific future configurations of the generating system, until the horizon of 2025, in the framework of medium and long term generation planning of MIBEL (the Iberian electricity market). Probabilistic simulation was chosen because deterministic approaches to this problem, although simple to understand and easy to implement, are unable to tackle the complex relations between different uncertain variables. In this project, simulation is organized chronologically, in order to preserve the relations between load and the different variables associated to generation and produce meaningful risk indices of generation adequacy. A new feature is the analysis of the operational reserve, through a process that estimates, in each simulated state, the unforeseen change in load and wind generation. These unexpected changes are then compared with the total available operational reserve, defined by the secondary reserve plus the tertiary reserve units with lead time up to one hour. It is important to point out that the proposed simulation is a tool that is able to quantify the adequacy of different reserve requirements, solutions for reserve enhancement, etc. , in order to support the decision making process. This paper describes the concepts and assumptions of the simulation model and presents results and conclusions of some of the case studies carried out in the project.

Abstract
There are already several power systems coping with large amounts of wind power. Hi h penetration of wind power has impacts that have to be manage through proper plant interconnection, integration, transmission planning, and system and market operations. This report is a summary of case studies addressing concerns about the impact of wind power.s variability and uncertainty on power system reliability and costs. The case studies summarized in this report are not easy to compare due to different methodology and data used, as well as different assumptions on the interconnection capacity available. Integration costs of wind power need to be compared to something, like the production costs or market value of wind power, or integration cost of other production forms. There is also benefit when adding wind power to power systems: it reduces the total operating costs and emissions as wind fossil fuels. Severalissues that impact on the amount of wind power that can be integrated have been identified. Large balancing areas and aggregation benefits of large areas help in reducing the variability and forecast errors of wind power as well as help in pooling more cost effective balancing resources. System operation and working electricity markets at less than day-ahead time scales help reduce forecast errors of wind power. Transmission is the key to aggregation benefits, electricity markets and larger balancing areas. From the investigated studies it follows that at wind penetrations of up to 20 % of gross demand (energy), system operating cost increases arising from wind variability and uncertainty amounted to about 1.4 ./MWh. This is 10 % or less of the wholesale value of the wind energy.

Abstract
This paper provides a description of a new approach for steady-state security evaluation, using fuzzy nearest prototype classifiers. The basic method has an offline training phase, used to design the fast classifiers for online purposes, allowing more than the two traditional security classes. A battery of these fuzzy classifiers, valid for a specific configuration of the network, is adopted to produce a global evaluation for all relevant single contingencies. An important feature of this approach is that it selects automatically the most appropriate number of security clusters for each selected contingency. Natural language labeling is also used to produce standardized sentences about the security level of the system, improving in this way the communication process between the system and the operator. The paper is completed by an example on a realistic model of the Hellenic Interconnected power system, where seven contingencies were simulated.

Abstract
This paper demonstrates the application of Markov chain models to valuate generation assets within deregulated electricity markets. A new framework for modeling electricity markets with Markov chain model is proposed. The advantage of the Markov chain model is that it deploys fundamental approaches to identify the key economic forces underlying the electricity markets such as demand on electricity and supplied online generation capacity. Based on this new model, real option calculations are used to valuate generation assets. Markov chain model is combined with binomial tree to approximate the stochastic movement of prices on both electric energy and ancillary services, which are driven by the market forces. A detailed example is presented. This method is shown to provide optimal operation policies and market values of generation assets. This method also provides capability to analyze the impacts of demand growth patterns, competition strategies of competitors and other key economic forces.

Abstract
Penetration of renewable energy sources in isolated and weakly interconnected power systems can be increased in a secure and reliable way, if advanced control tools are available to the operators of these systems. In this paper the functions of MORE CARE are described. This is an advanced control software system aiming to optimize the operation of isolated and weakly interconnected systems by increasing the share of wind energy and other renewable forms, taking into account pumped hydro storage facilities and providing advanced on-line security functions, both in preventive and corrective mode. The main features of the control system comprise advanced software modules for load and wind power forecasting, unit commitment and economic dispatch of the conventional and renewable units and on-line security assessment capabilities integrated in a friendly Man-Machine environment. In this way, penetration of renewable energy sources in isolated systems can be increased in a secure and reliable way. Pilot installations of advanced control functions are foreseen on the islands of Crete, Ireland and Madeira.