The massive integration of renewable energy resources increases the uncertainty with respect to realtime operation of the electrical systems. This transition introduces new challenges and opportunities for various entities that are involved in energy generation, transmission, distribution and consumption such as system operators and market participants in the wholesale electricity market. The concept of Decentralized Energy Management or Demand Response is emerging as one of the main approaches to resolve the violations of the network operation limits and to increase the flexibility of the system. This paper introduces an interaction framework for trading flexibility among proactive end-users in an economically efficient way. It proposes new market participants with their roles and functionalities, that will operate alongside the existing ones to ensure market efficiency and to enable secure operation of distribution grids. The proposed framework consists of a main mechanism called 'ahead-markets scheduling'. The ahead-markets scheduling includes two sub-mechanisms, day-ahead and intra-day, which are operated by a local flexibility market operator. The ahead-markets scheduling provides a trading platform that allows market participants to reflect their need(s) for flexibility and to monetize flexibility services in a fair and competitive manner. It enables flexibility trades which will eventually facilitate network management for the system operator.
The limited predictability and controlability of distributed energy resources has resulted in an increasing need for managing the available demand side flexibility from proactive endusers. In this regard, distribution system operators are expected to take a coordinating role in facilitating the utilization of the available flexibility. This paper proposes a novel optimization method to solve the optimal flexibility dispatch problem for a system operator such that it deploys the demand response resource effectively. We use the second-order cone relaxation of the problem to keep the problem convex, tractable and representing electric flows to a high accuracy. The analytical solution to the problem gives the locational pricing of flexibility services. To demonstrate the applicability and scalability of the proposed framework, it is applied to two case studies. We study a stylized 9-bus distribution network and a modified version of the IEEE 30-Bus System. Simulation results are interpreted in economic terms and show the effectiveness of the proposed approach.
Abstract-There is significant interest in building HVDC transmission to carry out transnational power exchange and deliver cheaper electricity from renewable energy sources which are located far from the load centers. This paper presents an approach to solve a long-term transmission planning problem for meshed VSC-HVDC grids that connect regional markets. This is in general a nonlinear non-convex large-scale optimization problem with high computational burden, partly due to the many combinations of wind and load that become possible. We developed a two-step iterative algorithm that first selects a subset of operating hours using a clustering technique, and then seeks to maximize the social welfare of all regions and minimize the investment capital of transmission infrastructure subject to technical and economic constraints. The outcome of the optimization is an optimal grid design with a topology and transmission capacities that results in congestion revenue paying off investment by the end the project's economic lifetime. Approximations are made to allow an analytical solution to the problem and demonstrate that an HVDC pricing mechanism can be consistent with an AC counterpart existing onshore. The model is used to investigate development of the offshore grid in the North Sea. Simulation results are interpreted in economic terms and show the effectiveness of our proposed two-step approach.
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