S. J. P. S. Mariano

Scheduling of Head-Sensitive Cascaded Hydro Systems: A Nonlinear Approach

In this paper, we propose a novel nonlinear approach to solve the short-term hydro scheduling problem under deregulation, considering head-dependency. The actual size of hydro systems, the continuous reservoir dynamics and constraints, the hydraulic coupling of cascaded hydro systems, and the complexity associated with head-sensitive hydroelectric power generation still pose a real challenge to the modelers. These concerns are all accounted for in our approach. Results from a case study based on one of the main Portuguese cascaded hydro systems are presented, showing that the proposed nonlinear approach is proficient.

An Artificial Neural Network Approach for Short-Term Electricity Prices Forecasting

This paper presents an artificial neural network approach for short-term electricity prices forecasting. In the new deregulated framework, producers and consumers require short-term price forecasting to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. A three-layered feedforward artificial neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting the next 168 hour electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed approach, reporting the numerical results from a real-world case study based on an electricity market.

Profit-Based Short-Term Hydro Scheduling considering Head-Dependent Power Generation

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a method, based on nonlinear programming, for optimizing power generation efficiency. The proposed method considers not only that the hydroelectric power generation is a function of the water discharge and of the head, but also that the maximum power generation is head-dependent. Numerical results based on a realistic cascaded hydro system illustrate the proficiency of the proposed method.

Profit-Based Unit Commitment with Emission Limitations: A Multiobjective Approach

This paper is on the problem of profit-based unit commitment with emission limitations. We propose a multiobjective approach to handle the problem with conflicting profit and emission objectives. A trade-off curve between profit and emission in a way to aid decision-makers concerning emission allowance trading is obtained due to this multiobjective approach. Numerical results based on the standard IEEE 30-bus test system illustrate the proficiency of the proposed approach.

Optimal output control: Load frequency control of a large power system

This paper addresses the stabilization and performance of the load frequency regulator. The problem is solved by using the theory of the optimal control. An algorithm, based on the new technique, proposed by the authors, to overcome the difficulties of specifying the weighting matrices Q and R, is presented. The algorithm here proposed considers the multi-area electric energy system. The paper presents illustrative numerical simulation results for this model. The results indicate that the obtained controller exhibits better performance then those based on classic control.

Application of Neural Networks on Next-Day Electricity Prices Forecasting

This paper presents an application for next-day electricity prices forecasting based on neural networks. Good forecasting tools hedging against daily price volatility are becoming increasingly important in nowadays competitive electricity markets, avowing misjudgement of future price movements and preventing considerable losses for consumers and producers. Next-day electricity price forecast is essential to consumers and to producers in planning the operations of their electric energy resources and for developing negotiation skills in order to achieve better profits. We evaluate the accuracy of the proposed application of neural networks for next-day electricity prices forecasting based on case studies for a real world electricity market and report our experience with this application.

Design of a new linear generator for wave energy conversion based on analytical and numerical analyses

This paper addresses the problem of the sea wave energy conversion. The power delivery at low speeds is one of the barriers imposed by the irregular movement of sea waves, requiring the use of electric machines that can produce large amounts of force to compensate the low speeds of that motion. The main concern is the proposal of a new linear switched reluctance generator. The proposed generator has high power density, robustness, and easy modeling and construction. Its analytical design and optimization based on finite element method are presented. Results and design challenges are discussed.

Dispatch of Head Dependent Hydro Units: Modeling for optimal generation in electricity market

Deregulation and liberalization of electric power industry, among other things, has created new requirements for the market participants. The power system engineer, operator, and, in general, the market participant is being faced with requirements for which he does not have adequate training and the proper software tools. In this framework, among others, a pure hydro-generation company has to (1) operate its hydro units, throughout the operating day, trying to fulfill the market clearing schedule, and modify the program in the intra-day energy markets if necessary (or more suitable) as real-time operation is getting closer and (2) make the offers for the regulation service market. In this scenario the Dispatch of Head Dependent Hydro Units is a problem that must be solved before dealing with the hourly hydro resource scheduling for energy and reserve optimization.

Optimal control: Load frequency control of a large power system

This paper addresses the stabilization and performance of the load frequency regulator. The problem is solved by using the theory of the optimal control. An algorithm, based on the new technique, proposed by the authors in [1], to overcome the difficulties of specifying the weighting matrices Q and R, is presented. The algorithm here proposed considers the multi-area electric energy system. The paper presents illustrative, numerical simulation results for this model. The results indicate that the obtained controller exhibits better performance then those based on classic control.

Power Quality Experimental Analysis on Rural Home Grid-Connected PV Systems

Microgeneration is the small-scale generation of heat or electric power or both, by individuals or buildings to meet their own needs. Recently, microgeneration is being regarded as a means to decentralize the power production of renewable energies, reducing the impacts on the grid caused by unexpected energy demands. Given the increase in microgeneration facilities, determining the quantity of energy produced and the power quality assumes growing importance in low, medium, or high voltage facilities. This paper presents a power quality analysis of two different facilities with photovoltaic generation localized in a rural area of Portugal, describing the voltage and frequency behaviour, the harmonic contents, and the total harmonic distortion. Statistical data are presented regarding the number of voltage events and occurrence of dips and swells in both facilities as a percentage of rated voltage. We conclude that some PV systems can severely affect voltage quality, forcing the grid to work at and even above the maximum voltage standard limit.