Abstract
Crete Island has significant natural resources when it comes to wind and solar energy. Likewise other European territories, renewable sources already are being explored for power production. Currently, a large amount of wind energy on Crete is curtailed during certain daily periods as a result of reduced demand and minimum operating levels of thermal generators. Reducing curtailment losses requires additional sources of flexibility in the grid, and electric energy storage is one of them. This paper address wind generation losses minimization through the storage of wind energy surplus. Sodium Sulfur (NaS) battery modeling is used in this study and an energy time-shift storage scheme is implemented to assess the overall storage system performance. The obtained results are supported on real data of renewable resources (wind and solar), conventional power production and demand of Crete Island in 2011. Conclusions are duly drawn.

Abstract
The volatility of the wind generation reduces the profits of wind generators as a consequence of the differences between the real wind generation and the wind power offered in the electricity markets. This paper presents two models: i) wind and generic storage system offering without a physical connection and ii) wind and generic storage system offering with a physical connection to mitigate the wind positive imbalances (excess of the wind generation with respect to the wind power offered). The objective of the models is to maximize the expected profit of selling the energy in the day-ahead market, where the energy can come from the wind power and the storage system. Moreover, the wind power imbalance is penalized in the balancing market reducing the profits. The problems are modeled using stochastic mixed integer linear programming. A case study of a week (168 hours) is simulated to evaluate the models. After the simulations, the results are discussed and a summary of the main conclusions are presented.

Abstract
The introduction of Variable Renewable Energy Sources (VRESs) such as wind to the future power portfolio can have significant effects on raising the daily net load variations and consequently may cause more operation costs as well as inefficient operation of units, and even in the worst case put the system's security at risk. On this basis, the need for a greater flexibility is essential to ensure efficient operation of the power system with significant amount of VRESs. Under this perspective, this paper presents a coordinated dispatch model in energy and reserve markets taking into account the role of bulk Battery Energy Storages (BESs) as well as Demand Response Programs (DRPs) as most favorable options in order to achieve a greater flexibility based on a Network Constrained Unit Commitment (NCUC) model. Numerical studies indicate that the coordinated operation of the existing units and the new flexible technologies could provide this additional required flexibility with a reasonable cost.

Abstract
In this study, a home energy management system structure is developed in order to determine the optimal commitment of a smart-household. Two types of loads are explicitly modeled: non-thermostatically controllable (electric vehicle, shiftable appliances) and thermostatically controllable loads (air conditioner, electric water heater). Furthermore, small-scale self-production is considered by means of a photovoltaic system. A test case using realistic data is presented in order to investigate the combined effect of the aforementioned assets under real-time pricing demand response.

Abstract
In this paper, an agent-based model is proposed to improve market efficiency by using different Demand Response Programs (DRPs) in the day-ahead electricity market. To this end, both incentive-based and price-based DRPs are considered. On this basis, time of use, real time pricing, emergency demand response program, interruptible/curtailable services and critical peak pricing are investigated. The tariffs of the considered price-based programs and the amount of incentive in the incentive-based programs are optimized through the proposed model. Furthermore, a market power index, i.e., Share Weighted Average Lerner Index (SWALI) and the operation cost are used to evaluate the market efficiency and the market power. The proposed model optimizes the DRPs to improve the electricity market efficiency by using a multi-attribute decision-making approach. The results show that the market operator can mitigate the potential occurrence of market power in a power system by finding the optimal DRP.

Abstract
This paper models the offers and bids of a generic storage system in an electricity market through stochastic mixed integer linear programming. The objective function aims at maximizing the profit from buying or selling energy for a general storage system. Some parameters such as storage system efficiency, losses of the energy stored and marginal costs are parameterized to evaluate the offers and bids. Market prices are forecasted for 24 hours using AR, MA and ARIMA time series models. The problem is tested for a case study, analyzing the behaviour of the offers and bids. Also, the results obtained are studied and relevant conclusions are presented.