scholarly journals Local Market for TSO and DSO Reactive Power Provision Using DSO Grid Resources

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3442
Author(s):  
Fábio Retorta ◽  
João Aguiar ◽  
Igor Rezende ◽  
José Villar ◽  
Bernardo Silva
Keyword(s):  
Real Time ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Time Interval ◽  
Local Market ◽  
Distribution Grid ◽  
Power Profile ◽  
System Operator

This paper proposes a near to real-time local market to provide reactive power to the transmission system operator (TSO), using the resources connected to a distribution grid managed by a distribution system operator (DSO). The TSO publishes a requested reactive power profile at the TSO-DSO interface for each time-interval of the next delivery period, so that market agents (managing resources of the distribution grid) can prepare and send their bids accordingly. DSO resources are the first to be mobilized, and the remaining residual reactive power is supplied by the reactive power flexibility offered in the local reactive market. Complex bids (with non-curtailability conditions) are supported to provide flexible ways of bidding fewer flexible assets (such as capacitor banks). An alternating current (AC) optimal power flow (OPF) is used to clear the bids by maximizing the social welfare to supply the TSO required reactive power profile, subject to the DSO grid constraints. A rolling window mechanism allows a continuous dispatching of reactive power, and the possibility of adapting assigned schedules to real time constraints. A simplified TSO-DSO cost assignment of the flexible reactive power used is proposed to share for settlement purposes.

scholarly journals Reactive Power Management Considering Stochastic Optimization under the Portuguese Reactive Power Policy Applied to DER in Distribution Networks

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4028 ◽  
Author(s):  
Abreu ◽  
Soares ◽  
Carvalho ◽  
Morais ◽  
Simão ◽  
...  
Keyword(s):  
Power Management ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Real Data ◽  
Distribution Networks ◽  
System Operator

Challenges in the coordination between the transmission system operator (TSO) and the distribution system operator (DSO) have risen continuously with the integration of distributed energy resources (DER). These technologies have the possibility to provide reactive power support for system operators. Considering the Portuguese reactive power policy as an example of the regulatory framework, this paper proposes a methodology for proactive reactive power management of the DSO using the renewable energy sources (RES) considering forecast uncertainty available in the distribution system. The proposed method applies a stochastic sequential alternative current (AC)-optimal power flow (SOPF) that returns trustworthy solutions for the DSO and optimizes the use of reactive power between the DSO and DER. The method is validated using a 37-bus distribution network considering real data. Results proved that the method improves the reactive power management by taking advantage of the full capabilities of the DER and by reducing the injection of reactive power by the TSO in the distribution network and, therefore, reducing losses.

scholarly journals Accelerated Real-Time Simulations for Testing a Reactive Power Flow Controller in Long-Term Case Studies

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Katja H. Sirviö ◽  
Mike Mekkanen ◽  
Kimmo Kauhaniemi ◽  
Hannu Laaksonen ◽  
Ari Salo ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Real Time ◽  
Power Flow ◽  
Reactive Power ◽  
Hardware In The Loop ◽  
Power Flow Control ◽  
Reactive Power Flow ◽  
System Operator ◽  
Real Time Simulations

This paper presents the development of an accelerated real-time cosimulation and testing platform, especially for long-term simulations of power systems. The platform is planned to be utilized in the development and testing of active network management functions for microgrids and smart grids. Long-term simulations are needed in order to study, for example, the potential weekly, monthly, or yearly usage of distribution-network-connected distributed energy resources for different technical flexibility services. In order to test new algorithms in long-term study cases, real-time simulations or hardware-in-the-loop tests should be accelerated. This paper analyzes the possibilities and challenges of accelerated long-term simulations in studying the potential use of a large-scale wind turbine for reactive power flow control between distribution system operator (DSO) and transmission system operator (TSO) networks. To this end, the reactive power flow control is studied for different voltage levels (HV and MV) in the Sundom Smart Grid in Vaasa, Finland. The control of reactive power flow between HV and MV networks is realized with a reactive power window control algorithm for a 3.6 MW MV-network-connected wind turbine with a full-scale power converter. The behaviour of the reactive power controller during long-term simulations is studied by offline and real-time simulations. Moreover, the real-time simulations are performed with both software-in-the-loop and controller-hardware-in-the-loop.

scholarly journals Alleviation of VAr Impact on Critical Loading Margin with Redispatch in Deregulated Power Systems

2018 ◽  
Vol 7 (1.8) ◽  
pp. 130
Author(s):  
Venkateswarlu A N ◽  
Tulasi Ram ◽  
S S ◽  
Sangameswara Raju.P
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Short Term ◽  
Critical Loading ◽  
Power Loading ◽  
System Operator ◽  
The Stability ◽  
Continuous Power

The stability management under deregulated environment has become typical task to the system due to random nature of load pattern and generation schedules. In addition, the regular uncertainties in system operation like line outage, generator outage or change in loading level are also causing to change in stability as well as security margins significantly. In order to manage transmission system security, the system operator can go for redispatch as a short term solution. In this article, an attempt is made to clear reactive power loading (VAr) impact on voltage instability margin or Critical Loading Margin (CLM). An Interior Point –Optimal Power Flow (IP-OPF) is applied to make system secured under (N-1) line contingencies. Using this secured schedule, the CLM is computed using Continuous Power Flow (CPF) for the two operating scenarios i.e., without VAr and with VAr loading on the system. The case study is simulated on IEEE 14-bus test network and outcome is validating that, the redispatch can also be apt for CLM enhancement even under contingencies as short term solution for stability management in real time.  

scholarly journals Utility-based operation management for low voltage distribution grids using online optimization

2021 ◽  
Author(s):  
Hanko Ipach ◽  
Leonard Fisser ◽  
Christian Becker ◽  
Andreas Timm-Giel
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problem ◽  
Low Voltage ◽  
The State ◽  
Operation Management ◽  
Distributed Energy ◽  
System Operator ◽  
Distribution Grids

AbstractWe present an operation management controller for low voltage (LV) grids that coordinates a multitude of distributed energy resources (DER) in real time to maximize the utilization of renewable energy production. It utilizes an LTE radio network that connects the DERs to the distribution system operator. In our approach, utility functions are assigned to the DERs, and the utility maximization is formulated as an optimization problem. The optimization problem is solved by an iterative algorithm that performs incremental updates of the DER power set values to achieve the optimum. In order to take the state of the grid in the optimization process into account, the state of the grid is estimated. During the simulation of a use case, we demonstrate the applicability and identify the benefits of our approach compared to an established optimal power flow (OPF) method. Particular emphasis is put on evaluating the communication delay and feasibility of the required communication network, as the iterative approach leads to a high communication load.

scholarly journals A Decentralized Local Flexibility Market Considering the Uncertainty of Demand

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2078 ◽  
Author(s):  
Ayman Esmat ◽  
Julio Usaola ◽  
Mª Moreno
Keyword(s):  
Real Time ◽  
Distribution System ◽  
Demand Management ◽  
Congestion Management ◽  
Local Market ◽  
Management Process ◽  
Real Distribution ◽  
System Operator ◽  
The Right ◽  
The Impact

The role of the distribution system operator (DSO) is evolving with the increasing possibilities of demand management and flexibility. Rather than implementing conventional approaches to mitigate network congestions, such as upgrading existing assets, demand flexibility services have been gaining much attention lately as a solution to defer the need for network reinforcements. In this paper, a framework for a decentralized local market that enables flexibility services trading at the distribution level is introduced. This market operates on two timeframes, day-ahead and real-time and it allows the DSO to procure flexibility services which can help in its congestion management process. The contribution of this work lies in considering the uncertainty of demand during the day-ahead period. As a result, we introduce a probabilistic process that supports the DSO in assessing the true need of obtaining flexibility services based on the probability of congestion occurrence in the following day of operation. Besides being able to procure firm flexibility for high probable congestions, a new option is introduced, called the right-to-use option, which enables the DSO to reserve a specific amount of flexibility, to be called upon later if necessary, for congestions that have medium probabilities of taking place. In addition, a real-time market for flexibility trading is presented, which allows the DSO to procure flexibility services for unforeseen congestions with short notice. Also, the effect of the penetration level of flexibility on the DSO’s total cost is discussed and assessed. Finally, a case study is carried out for a real distribution network feeder in Spain to illustrate the impact of the proposed flexibility framework on the DSO’s congestion management process.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

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