Uncertainty Management in Power System Operation Decision Making

Due to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for power system; therefore the need for accurate decision-making in a power system under the penetration of uncertainties is essential. However, decision makers should use suitable methods for uncertainty management. In this chapter, some of the uncertainty modeling methods in power system studies are analyzed. At first, multiple uncertain parameters that the power system deals with are introduced, then some useful uncertainty modeling methods are introduced. To show the uncertainty modeling process and its effect on the decision-making, a microgrid consisting of multiple uncertain parameters is considered, and stochastic scenario-based approach is used for uncertainty modeling. The scheduling of microgrids in the presence of different types of uncertainty is solved from the profit-maximization point of view. The simulation results are presented for a 33-bus microgrid that shows the effectiveness of the proposed method for decision-making under high level of uncertainty

Defeating Trolls: The Impact Of Octane and Highmark On Patent Trolls

This Comment discusses two Supreme Court cases, Octane Fitness, LLC v. ICON Health & Fitness, Inc. and Highmark, Inc. v. Allcare Health Management Systems, Inc., and their impact on patent litigation involving patent trolls. Prior to these cases, patent troll litigation was on a continual rise and Congress’s proposed measures were failing to curb the problem. Many companies, particularly startups, were left vulnerable to a patent troll threat because they could not afford the potential court costs to defend their case. This problem was compounded by the fact that traditional attorney fee shifting awards were extremely rigid and difficult to prove. This Comment argues that Octane and Highmark are able to hinder patent troll litigation because they reduce the standard by which attorney fees may be awarded to the prevailing party. Moreover, Octane and Highmark are better able to address this problem better than other proposed and implemented solutions such as Alice Corp. Pty. v. CLS Bank and the Innovation Act. The argument is that Octane and Highmark allow an easier award of attorney fees while minimizing the adverse affects the other two alternatives carry. Lastly, by implementing a mandatory bonding requirement on patent plaintiffs, the patent troll business model will be severely impacted and result in a decline in frivolous patent litigation

An auction framework to integrate dynamic transmission expansion planning and pay-as-bid wind connection auctions. ESRI WP523. January 2016

Efficient renewables deployment requires the minimisation of both internal generation costs and external transmission expansion planning (TEP) costs. Competitive pay- as-bid connection auctions allow wind energy generators to reveal their costs of generation such that internal generation costs may be minimised. TEP costs have not been incorporated into such auctions to date. Integrating these procedures may allow for a global minimisation of internal generation and external TEP costs over many time periods. This paper develops an auction mechanism and associated modelling framework to carry this out. The contributions of this framework are verified using a numerical example. Our results show that ignoring generation costs in transmission expansion planning has quantifiable economic consequences, while traditional pay-as-bid auctions can benefit from incorporating features associated with TEP, such as multi-period optimisation. Full integration of both modelling frameworks leads to efficiency improvements, both in terms of reduced investor rent-seeking and a more efficient deployment path

Power to air transportation via hydrogen

This study proposes a framework to analyse the concept of power to hydrogen (P2H) for fuelling the next generation of aircraft. The impact of introducing new P2H loads is investigated from different aspects namely, cost, carbon emission, and wind curtailment. The newly introduced electric load is calculated based on the idea of replacing the busiest international flight route in the Europe, Dublin‐London Heathrow, by hydrogen fuel‐powered aircraft as a high potential candidate for the next generation of air travel systems to cope with the ambitious targets set in Europe Flight Path 2050 by the Advisory Council for Aeronautics Research in Europe. The simulation is performed on a representative Irish transmission network to demonstrate the effectiveness of the proposed solution

Optimal Deployment of Mobile MSSSC in Transmission System

With the rapid development of the renewable energy source (RES), network congestion management is increasingly important for transmission system operators (TSOs). The limited transmission network capacity and traditional intervention methods result in high RES curtailment. The near-term, powerful, and flexible solutions, such as advanced flexible AC transmission systems (FACTS), are considered to mitigate the risks. The mobile modular static synchronous series compensator (MSSSC) is one of the grid-enhancing solutions. The mobility of the solution allows it to offer fast deployment and seasonal redeployability with limited cost. The demonstration of the mobile MSSSC solution has shown significant benefits for RES curtailment reduction, network congestion alleviation, and facilitating the demand and RES connection. For unlocking the true value of the mobile solution, they should be optimally allocated in the transmission networks. This paper develops a security-constrained DCOPF-based optimisation tool to investigate the optimal allocation of the mobile MSSSC solution in transmission networks. A linear mobile MSSSC model with the operation dead-band was introduced that can be used in large-scale realistic power system planning. The proposed model was implemented in the IEEE 118-bus system to assess the performance of the mobile MSSSC.University College Dubli

Fast Resource Scheduling for Distribution Systems Enabled with Discrete Control Devices

This paper proposes a framework for fast short-term scheduling and steady-state voltage control in distribution systems enabled with both continuous control devices, e.g., inverter interfaced DGs and discrete control devices (dcds), e.g., on-load tap changers (oltcs). The voltage-dependent nature of loads is taken into account to further reduce the operating cost by managing the voltage levels. The branch and cut method is applied to handle the integrality constraints associated with the operation of dcds. A globally convergent trust-region algorithm (tra) is applied to solve the integer relaxed problems at each node during the branching process. The tra sub-problems are solved using the interior point method. To reduce the branching burden of the branch and cut algorithm, before applying tra at each node, a simplified optimization problem is first solved. Using the convergence status and value of the objective function of this problem, a faster decision is made on stopping the regarding branch. Solving the simplified problem obviates the application of tra at most nodes. It is shown that the method converges to the optimal solution with a considerable saving in computation time according to the numerical studies

Optimising Load Flexibility for the Day Ahead in Distribution Networks with Photovoltaics

This paper has been presented at: 2019 IEEE Milan PowerTechIn this paper a methodology is proposed to calculate the load demand flexibility that could be activated within the next 24-hours for solving the technical impacts of contingencies that may come up in an unbalanced low voltage distribution networks with high penetration of intermittent DG sources. The methodology is formulated within a Demand Response program environment via load shifting as flexibility enabler mechanism. To achieve that, a non-linear optimisation problem is formulated based on an unbalanced optimal power flow, which allows the determination of the load flexibility that each Demand Response customer could provide at the request of the Distribution System Operator. The demand as well as weather conditions are forecasted for the day ahead. The optimisation problem is solved in a sequence fashion, within a daily framework, splitting the whole problem in optimisation blocks. In each block, the flexible load demand is obtained and the load demand forecasting its updated for the upcoming blocks based on the changes in the scheduled load demand. The methodology is applied to a real distribution network with the load data received from the smart metering infrastructure. The results obtained show the strength of the methodology in solving the technical problems of the network under high unbalanced operation.The work done by Valentin Rigoni and Alireza Soroudi is supported by a research grant from Science Foundation Ireland (SFI) under the SFI Strategic Partnership Programme Grant No. SF/15/SPP/E3125. The opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Science Foundation Ireland. Jose Angel Velasco and Hortensia Amaris are supported by the Spanish Ministry of Economy and Competitiveness through the National Program for Research under the project OSIRIS (RTC-2014-1556-3)

Prediction of Spark Ignition Performance in an Industrial Gas Turbine Combustor

Abstract Spark ignition performance of an annular combustor has been analyzed using computational modeling approach. Main steps of this approach include: (1) LES of the combustor non-reacting flow field, (2) using time-averaged LES results in a stochastic code in order to identify probable propagation behavior of the flame front using Lagrangian particle tracking, and (3) repeating the computations by an engineering approach and prediction of the combustor lean light-off (LLO) limit. By using this approach, effects of the ignition system location and specifications, fuel type and composition, and operating conditions on the gas turbine ignition performance can be evaluated effectively. Corresponding author: [email protected] Proceedings of the European Combustion Meeting 2015 Introduction Ignition is the process of transferring a flammable mixture from the non-reacting state to the selfsustaining combustion. Ignition is a transient phenomenon in which a complex interaction of chemical and physical processes occurs. Ignition in a flammable environment can be achieved by two general methods: forced ignition and self-ignition. During the forced ignition, a small volume of the mixture is ignited by an external force and the flame spreads across the whole system if the flame propagation conditions exist. In self-ignition or auto-ignition process, there is no local ignition source and the whole mixture ignites simultaneously Currently, practical gas turbine engine ignition systems include spark ignition (electrical spark and laser-induced spark or LIS) and torch systems (including both flame and plasma torches) Different studies have shown that the spark ignition in an annular gas turbine combustor is conducted at three phases. At the first phase, with starting discharge process and through breakdown, arc discharge, and glow discharge stages a flame kernel with sufficient size and temperature forms. At the second phase, this flame core spreads and the continuous spread of the flame from this kernel fills the primary combustion zone o