Abstract
This paper proposes an offering strategy for a wind power producer (WPP) that participates in both day-ahead (DA) and balancing oligopoly markets as a price maker. Penetration of demand response (DR) resources into smart grids is modeled by intraday demand response exchange (IDRX) architecture. A bilevel optimization framework is proposed based on multiagent system and incomplete information game theory. Modeling the WPPs in high penetration of wind power as price makers can reflect the capability of this market player to directly affect the market prices. Simulation results indicate that the price-taker model ofWPP is not accurate for WPPs that have significant market shares. By comparing the results obtained from modeling the WPPs as price makers with the ones as price takers, it can be concluded that WPPs have the market power not only to increase the prices of both DA and balancing markets, but also to reduce the amount of DR through IDRX market mechanism.

Abstract
This paper addresses the stochastic security constrained unit commitment (SSCUC) problem with flexibility resources for managing the uncertainty of wind power generation (WPG). Departing from the traditional flexibility resources such as the thermal units with fast up/down spinning reserves and transmission switching (TS), this paper explores also the use of demand response (DR) and energy storage (ES) systems in an innovative integrated scheme. The proposed scheme utilizes a stochastic optimization framework to coordinate the flexibility resources dealing with the uncertainty of WPGs and equipment failures. The stochastic optimization model is formulated as a mixed-integer linear programming (MIP), and this problem is large and computationally complex even for medium sized systems. Accordingly, we present a novel accelerating decomposition technique aimed at solving this problem and reducing the number of iterations and CPU time. Numerical simulation results on the modified 6-bus system and on large-scale power systems, i.e. IEEE 118 and 300-bus systems, clearly demonstrate the benefits of applying flexibility resources for uncertainty management and the efficacy of the proposed solution strategy for large-scale systems.

Abstract
The concept of Carrier-Based Demand Response (CBDR) programs in Smart Multi-Energy Systems (MES) is proposed in this paper. It is discussed that by establishing the bi-directional relation between multi-energy demand and MES through the penetration of multi-carrier device technologies, the opportunity of demand-side participation in system operation can be activated. In this paper, the external dependency caused by multi-carrier devices is employed as a demand response. The CBDR is introduced as the flexibility of end-use to change the conversion pattern of input carriers into required demand. As the CBDR program is influenced by energy carrier prices, upstream network obligations and also the customer's behavior, its uncertainty is effectively modeled in this paper. The results compare the difference between the stochastic and deterministic approaches to the problem and show the improved accuracy through the stochastic modeling. The role of those customers that are not taking part in CBDR program is also investigated.

Abstract
Emerging trends in electric vehicles both in science and industry, as well as increasing popularity of these devices among end-users have laid serious issues in front of a system operator or planner. Higher deployment of available resources in the system will lead to higher flexibility for system operator in its interactions, besides to higher level of user satisfaction. In this study, various states of a 13 bus radial distribution network have been considered for allocation of Plug-in Electric Vehicles' (PEVs') parking lots. As Renewable Energy Resources (RERs) are becoming a main element of power systems, it is investigated how the future distribution network planning has to be organized by employing both RERs and PEV parking lots. Also, it is investigated how the allocation of parking lots varies in the system where these resources exist. Moreover, the costs and revenues obtained by the system operator in such systems are also studied.

Abstract
A recent solution to tackle environmental issues is the electrification of transportation. Effective integration of plug-in electric vehicles (PEVs) into the grid is important in the process of achieving sustainable development. One of the key solutions regarding the need for charging stations is the installation of PEV parking lots (PLs). However, contrary to common parkings, PLs are constrained by various organizations such as municipalities, urban traffic regulators, and electrical distribution systems. Therefore, this paper aims to allocate PLs in distribution systems with the objective of minimizing system costs including power loss, network reliability, and voltage deviation as possible objectives. A two-stage model has been designed for this purpose. PLs' behavior considering market interactions is optimized at the first stage to provide profit to the PL owner. At the second stage, the PL allocation problem is solved considering various network constraints. Conclusions are duly drawn with a realistic example.

Abstract
In this paper, a management strategy to be used in the scheduling of insular electrical systems with energy storage system (EES) is presented. Integration of ESS allows reducing generation costs and greenhouse gases (GHG) emissions, as well as improving wind power penetration levels. The methodology presented in this paper is particularly useful for those systems provided with battery ESS, due to it is ability to include the effects of the most relevant components, such as thermal and renewable generation, bidirectional power converter, and charge controller operation. From the analysis of a case study considering a diesel-powered system and a Vanadium Redox Flow Battery (VRFB), it is possible to estimate the potential reduction on fuel consumption and wind power curtailment, in comparison with a case without EES.