Financial Transmission Rights (FTR) as a Congestion Management Scheme in Electricity Transmission: Strategic Behavior in a Coupled FTR — Electricity Market Model

With the emergence of liberalized markets, transmission line congestion has been a prominent technical constraint that has to be accounted for in designing the new markets. Transmission line congestion is a phenomenon in electricity markets that emerges more severely in time with ever increasing demand in electricity and resultant excessive loading of transmission lines. Various congestion management techniques such as market splitting, market coupling etc. are utilized currently in energy markets. However on the long run financial transmission rights (FTR), which is readily used by some US electricity market operators such as PJM, New York and New England operators, has potential to dominate other markets too. Modelling financial transmission rights to test some strategic hypotheses is imperative to be able to introduce suitable policies and regulations. In this paper we present a modelling approach for financial transmission rights and examine strategic use of hidden knowledge in a hypothetical electricity — FTR market

Congestion Management in Hybrid Electricity Markets with FACTS Devices with Loadability Limits

Congestion management (CM) is one of the most important challenging tasks of the Independent System Operator (ISO) in the deregulated environment. In this paper, generators’ rescheduling based CM approach to manage transmission line congestion considering loadability limit has been presented for hybrid based electricity market model. The main contribution of the paper is (i) to obtain secure transactions for hybrid market model, (ii) optimal rescheduling of generators with loadability limits taken into account with secure transactions, (iii) and impact of FACTS devices on transmission line congestion management. The ISO ensures secure bilateral transactions in a hybrid market model and CM is managed with minimum preferred schedule to obtain minimum congestion cost. The results have been obtained for IEEE 24 bus test system.  Keywords: Generator re-dispatch, congestion management, pool electricity market, bid function, loadability limit.DOI:http://dx.doi.org/10.11591/ijece.v2i1.11

Alleviating Power Line Congestion Through the Use of a Renewable Generation

As the United States\u27 energy demand has grown substantially within the past few decades, the reliability of its electric grids has become even more pertinent. With millions of customers relying on having consistent electric power to fulfill their daily routines and necessary operations, electric power transmission congestion, or the overloading of the electric power transmission network, can be very costly and detrimental to the reliability of the network and the environment. Therefore, it is imperative to identify and implement methods of optimally controlling the power flows to limit transmission line congestion. Throughout recent decades, there has been an ever-increasing penetration of Renewable Energy Generation in the power grid. However, unlike in the past, where fossil fuel generating plants were mostly located in remote areas, and in the proximity of the source of energy, the most common of the renewable generations, such as solar power systems, are haphazardly sited close to the loads. This is due to the fact that energy from the sun can be harnessed almost everywhere. This unplanned siting of renewable generating systems aggravates the power distribution lines congestion that already exists due to the power distribution deregulation. This thesis presents a procedure that takes advantage of utilization and proper placement of Photovoltaic (PV) power systems to alleviate power line congestion. In this procedure, the base caseload flow, without the solar generating system, is performed on the distribution network. And the bus with the lowest voltage is identified; this low-voltage bus is indicative of congestion in the lines connecting the identified bus. A PV power system is then tied to that bus; the capacity of the PV generation is varied heuristically to determine the optimality that mitigates the congestion on the lines. The procedure is followed to test a 9-bus IEEE power system, and the results are presented. Keywords: Congestion management; Power line congestion; Renewable energy generation; Transmission line

RISK MANAGEMENT AND PARTICIPATION OF ELECTRIC VEHICLE CONSIDERING TRANSMISSION LINE CONGESTION IN THE SMART GRIDS FOR DEMAND RESPONSE

Demand response (DR) could serve as an effective tool to further balance the electricity demand and supply in smart grids. It is also defined as the changes in normal electricity usage by end-use customers in response to pricing and incentive payments. Electric cars (EVs) are potentially distributed energy sources, which support the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes, and their participation in time-based (e.g., time of use) and incentive-based (e.g., regulation services) DR programs helps improve the stability and reduce the potential risks to the grid. Moreover, the smart scheduling of EV charging and discharging activities supports the high penetration of renewable energies with volatile energy generation. This article was focused on DR in the presence of EVs to assess the effects of transmission line congestion on a 33-bit grid. A random model from the standpoint of an independent system operator was used to manage the risk and participation of EVs in the DR of smart grids. The main risk factors were those caused by the uncertainties in renewable energies (e.g., wind and solar), imbalance between demand and renewable energy sources, and transmission line congestion. The effectiveness of the model in a 33-bit grid in response to various settings (e.g., penetration rate of EVs and risk level) was evaluated based on the transmission line congestion and system exploitation costs. According to the results, the use of services such as time-based DR programs was effective in the reduction of the electricity costs for independent system operators and aggregators. In addition, the results demonstrated that the participation of EVs in incentive-based DR programs with the park model was particularly effective in this regard

Failure Localization in Power Systems via Tree Partitions

Cascading failures in power systems propagate non-locally, making the control and mitigation of outages extremely hard. In this work, we use the emerging concept of the tree partition of transmission networks to provide an analytical characterization of line failure localizability in transmission systems. Our results rigorously establish the well perceived intuition in power community that failures cannot cross bridges, and reveal a finer-grained concept that encodes more precise information on failure propagations within tree-partition regions. Specifically, when a non-bridge line is tripped, the impact of this failure only propagates within well-defined components, which we refer to as cells, of the tree partition defined by the bridges. In contrast, when a bridge line is tripped, the impact of this failure propagates globally across the network, affecting the power flow on all remaining transmission lines. This characterization suggests that it is possible to improve the system robustness by temporarily switching off certain transmission lines, so as to create more, smaller components in the tree partition; thus spatially localizing line failures and making the grid less vulnerable to large-scale outages. We illustrate this approach using the IEEE 118-bus test system and demonstrate that switching off a negligible portion of transmission lines allows the impact of line failures to be significantly more localized without substantial changes in line congestion

Real time grid congestion management in presence of high penetration of wind energy

With the increased use of wind energy the power generation several Transmission System Operators (TSO) have increasing difficulties for congestion forecasting due to the unpredictable nature of the energy source. This paper proposes to enhance the congestion management using a real time supervisor. This supervisor is developed to perform automatic and dynamic re-dispatching using both wind and conventional generators. In order to reduce the production constraints to the minimum, the real time congestion management is based on an indicator of the efficiency of a re-dispatching on the power flowing in the overloaded line. This approach leads to reduced re-dispatching costs and increased network reliability. The simulation of the supervisor and the test grid is realized using by the EUROSTAG [1]. It is shown that the real-time supervisor allows maximization of renewable production during congestions while ensuring network reliability.Power management ;Power transmission;Energy system management;Wind energy ; Variable speed drive