Abstract
Renewable energy integration is gradually increasing in several European countries, such as Portugal and Spain, aiming to reduce emissions in power system operations. Particularly, significant investments in hydro energy systems are envisaged in Portugal, representing a secure and reliable energy source towards sustainable development. Additionally, a pool market structure implies that producers should aim at maximizing profits on a day-ahead basis. Usually, hydro power producers have been considered as price-takers, accepting the price signal as input data. Instead, a MILP approach is provided in this paper to determine the operations planning of a hydro producer acting as a price-maker in a day-ahead electricity market. A realistic case study is presented, based on a hydro energy system in cascaded configuration characterized by spatial-temporal interdependency between reservoirs, in order to thoroughly evaluate the expertise of the proposed approach.

Abstract
This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Abstract
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning cascaded and head-dependent reservoirs. We propose an efficient method, based on nonlinear programming (NLP), for power generation efficiency improvement. This method considers hydroelectric power generation as a function of water discharge and also of the head. The proposed method provides higher profit for the generating company (GENCO), at a negligible extra computational effort, in comparison with classical optimisation methods based on linear programming (LP) that ignore head dependence.

Abstract
This paper proposes a practical approach to solve the short-term thermal scheduling (STTS) problem with environmental concerns. Under deregulation, minor changes in the energy price may give a significant change in the power generation of thermal units. Hence, the influence of price forecasting on STTS with environmental concerns is an important research issue, which is analysed in this paper considering different price profiles. This analysis is made in connection with a case study based on the standard IEEE 30-bus system.

Abstract
Under a market framework, the development of optimal offering strategies is crucial for wind power producers to achieve maximum profit. In this paper, a two-stage stochastic programming approach is proposed, considering the uncertainties on wind power production and electricity market prices. An artificial intelligence model allows generating wind-price scenarios. Also, risk management is appropriately addressed. Results from a real-world case study are presented, in order to illustrate the proficiency of the proposed approach. Finally, conclusions are duly drawn.

Abstract
Under the current European energy policy towards a sustainable environment, the optimization of the hydropower resources is of crucial importance. In this paper, a mixed-integer nonlinear programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency and discontinuous operating regions. As new contributions to earlier studies, market uncertainty is introduced via price scenarios and risk management is incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Besides, plant scheduling and pool offering by the hydro power producer are simultaneously considered to solve a realistic hydro system with three cascaded reservoirs. Finally, conclusions are duly drawn.