Résultats de recherche pour « Electric Power System »

Accurate day-ahead electricity price forecasts are critical for power system operation and market participation, yet growing renewable penetration and recent crises have caused unprecedented volatility that challenges standard models. This paper revisits variance stabilizing transformations (VSTs) as a preprocessing tool by introducing a novel parametrization of the asinh transformation, systematically analyzing parameter sensitivity and calibration window size, and explicitly testing performance under volatile market regimes. Using data from Germany, Spain, and France over 2015-2024 with two model classes (NARX and LEAR), we show that VSTs substantially reduce forecast errors, with gains of up to 14.6% for LEAR and 8.7% for NARX relative to untransformed benchmarks. The new parametrized asinh consistently outperforms its standard form, while rolling averaging across transformations delivers the most robust improvements, reducing errors by up to 17.7%. Results demonstrate that VSTs are especially valuable in volatile regimes, making them a powerful tool for enhancing electricity price forecasting in today's power markets.

This paper presents a conceptual framework to successfully integrate electric vehicles into electric power systems. The proposed framework covers two different domains: the grid technical operation and the electricity markets environment. All the players involved in both these processes, as well as their activities, are described in detail. Additionally, several simulations are presented in order to illustrate the potential impacts/benefits arising from the electric vehicles grid integration under the referred framework, comprising steady-state and dynamic behavior analysis.

A dynamic state estimation method of integrated natural gas and electric power systems (IGESs) in proposed. Firstly, the coupling model of gas pipeline networks and power systems by gas turbine units (GTUs) is established. Secondly, the Kalman filter based linear DSE model for the IGES is built. The gas density and mass flow rate, as well as the real and imaginary parts of bus voltages are taken as states, which are predicted by the linearized fluid dynamic equations of gases and exponential smoothing techniques. Boundary conditions of pipeline networks are used as supplementary constraints in the system model. At last, the proposed method is applied to an IGES including a 30-node pipeline network and IEEE 39-bus system coupled by two GTUs. Two indexes are used to evaluate the DSE performance under three measurement error conditions, and the results show that the DSE can obtain the accurate dynamic states in different conditions.

In order to unifiedly coordinate economy and voltage deviations, a novel multi-objective optimal power flow (MOPF) algorithm is proposed for an AC/DC system with VSC-HVDC based on cooperative multi-objective particle swarm optimization (CMOPSO). In order to minimize power generation costs and voltage deviations, the MOPF model of the AC/DC system is firstly built based on the VSC-HVDC steady-state model. Then, the CMOPSO is adopted for solving the MOPF model to find well-distributed Pareto-optimal solutions. Next, the solutions are divided into different groups via the fuzzy C-means algorithm, and finally the best compromise solutions reflecting decision-makers' different preferences are identified from each group by comparing the priority memberships which are calculated by using the grey relation projection method. The validity of the proposed approach is verified by using the modified IEEE 14-bus and 118- bus systems.

A key mission of the U.S. Department of Energy (DOE) Office of Electricity Delivery and Energy Reliability (OE) is to enhance the security and reliability of the nation’s energy infrastructure. Improving the security of control systems, which enable the automated control of our energy production and distribution, is critical for protecting the energy infrastructure and the integral function that it serves in our lives. The DOE-OE Control Systems Security Program provides research and development to help the energy industry actively pursue advanced security solutions for control systems. The focus of this report is analyzing how, where, and what type of wireless communications are suitable for deployment in the electric power system and to inform implementers of their options in wireless technologies. The discussions in this report are applicable to enhancing both the communications infrastructure of the current electric power system and new smart system deployments. The work described in this report includes a survey of the following wireless technologies: • IEEE 802.16 d and e (WiMAX) • IEEE 802.11 (Wi-Fi) family of a, b, g, n, and s • Wireless sensor protocols that use parts of the IEEE 802.15.4 specification: WirelessHART, International Society of Automation (ISA) 100.11a, and Zigbee • The 2, 3, and 4 generation (G )cellular technologies of GPRS/EDGE/1xRTT, HSPA/EVDO, and Long-Term Evolution (LTE)/HSPA+UMTS.

The dynamic behaviour of a power system can be described by a system of differential-algebraic equations. Time-domain simulations are used to simulate the evolution of these dynamics. They often require the use of small time step sizes and therefore become computationally expensive. To accelerate these simulations, we propose a simulator - PINNSim - that allows to take significantly larger time steps. It is based on Physics-Informed Neural Networks (PINNs) for the solution of the dynamics of single components in the power system. To resolve their interaction we employ a scalable root-finding algorithm. We demonstrate PINNSim on a 9-bus system and show the increased time step size compared to a trapezoidal integration rule. We discuss key characteristics of PINNSim and important steps for developing PINNSim into a fully fledged simulator. As such, it could offer the opportunity for significantly increasing time step sizes and thereby accelerating time-domain simulations.

This paper describes the effects of distributed generation on electric power systems. Distributed generation is a term that refers to the production of electricity near the consumption place. The effects of distributed generation are: short circuit levels are increased, load losses change, voltage profiles change along the network, voltage transients will appear, congestions can appear in system branches, power quality and reliability may be affected and the networks protections may not function properly. A load flow analysis is done for the IEEE 14 system in which a distributed generator is added, that is on-grid or off-grid.

In order to mitigate cascading failure blackout risks in power systems, the critical components whose failures lead to high blackout risks should be identified. In this paper, such critical components are identified by the state-failure network (SF-network) formed by cascading failure chain and loss data, which can be gathered from either utilities or simulations. The failures along the chains are recombined in the SF-network, where each failure is allocated a value that can reveal the blackout risks after their occurrences. Thus, critical failures can be identified in the SF-network where the failures raise up blackout risks, and thus the critical components can be found based on their critical failure risks. The simulation results validate the effectiveness of the proposed method.

Narrow body and wide body aircraft are responsible for more than 75% of aviation greenhouse gas (GHG) emission and aviation, itself, was responsible for about 2.5% of all GHG emissions in the United States in 2018. This situation becomes worse when considering a 4-5% annual growth in air travel. Electrified aircraft is clearly a promising solution to combat the GHG challenge; thus, the trend is to eliminate all but electrical forms of energy in aircraft power distribution systems. However, electrification adds tremendously to the complexity of aircraft electric power systems (EPS), which is dramatically changing in our journey from conventional aircraft to more electric aircraft (MEA) and all electric aircraft (AEA). In this article, we provide an in-depth discussion on MEA/AEA EPS: electric propulsion, distributed propulsion systems (DPS), EPS voltage levels, power supplies, and EPS architectures are discussed. Publications on power flow (PF) analysis and management of EPS are reviewed, and an initial schematic of a potential aircraft EPS with electric propulsion is proposed. In this regard, we also briefly review the components required for MEA/AEA EPS, including power electronics (PE) converters, electric machines, electrochemical energy units, circuit breakers (CBs), and wiring harness. A comprehensive review of each of the components mentioned above or other topics except for those related to steady state power flow in MEA/AEA EPS is out of this article's scope and should be found somewhere else. At the close of the paper, some challenges in the path towards AEA are presented. Unless the discussed challenges are satisfactorily addressed and solved, arriving at an AEA that can properly operate over commercial missions will not be possible.