scholarly journals Insights on Germany’s Future Congestion Management from a Multi-Model Approach

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4176
Author(s):  
Dirk Hladik ◽  
Christoph Fraunholz ◽  
Matthias Kühnbach ◽  
Pia Manz ◽  
Robert Kunze
Keyword(s):  
Electricity Market ◽  
Power Flow ◽  
Power Plants ◽  
Optimal Power Flow ◽  
System Analysis ◽  
Congestion Management ◽  
Market Model ◽  
Design Parameters ◽  
Investment Incentives ◽  
German Market

In Germany, the political decision to phase out nuclear and coal-fired power as well as delays in the planned grid extension are expected to intensify the current issue of high grid congestion volumes. In this article, we investigate two instruments which may help to cope with these challenges: market splitting and the introduction of a capacity mechanism. For this purpose, we carry out a comprehensive system analysis by jointly applying the demand side models FORECAST and eLOAD, the electricity market model PowerACE and the optimal power flow model ELMOD. While a German market splitting has a positive short-term impact on the congestion volumes, we find the optimal zonal delimination determined for 2020 to become outdated by 2035 resulting in new grid bottlenecks. Yet, readjusting the zonal configuration would lower the ability of the market split to provide regional investment incentives. Introducing a capacity mechanism with a congestion indicator allows allocating new power plants in regions with higher electricity demand. Consequently, we find the required congestion management to be substantially reduced in this setting. However, given the large amount of design parameters, any capacity mechanism needs to be carefully planned before its introduction to avoid new inefficiences on the market side.

scholarly journals Decentralized Prosumer-Centric P2P Electricity Market Coordination with Grid Security

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4665
Author(s):  
Duarte Kazacos Winter ◽  
Rahul Khatri ◽  
Michael Schmidt
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Power Flow ◽  
Power Plants ◽  
Optimal Power Flow ◽  
Free Market ◽  
Economic Value ◽  
New Paradigm ◽  
Grid Security ◽  
Virtual Power Plants

The increasing number of prosumers and the accompanying greater use of decentralised energy resources (DERs) bring new opportunities and challenges for the traditional electricity systems and the electricity markets. Microgrids, virtual power plants (VPPs), peer-to-peer (P2P) trading and federated power plants (FPPs) propose different schemes for prosumer coordination and have the potential of becoming the new paradigm of electricity market and power system operation. This paper proposes a P2P trading scheme for energy communities that negotiates power flows between participating prosumers with insufficient renewable power supply and prosumers with surplus supply in such a way that the community welfare is maximized while avoiding critical grid conditions. For this purpose, the proposed scheme is based on an Optimal Power Flow (OPF) problem with a Multi-Bilateral Economic Dispatch (MBED) formulation as an objective function. The solution is realized in a fully decentralized manner on the basis of the Relaxed Consensus + Innovations (RCI) algorithm. Network security is ensured by a tariff-based system organized by a network agent that makes use of product differentiation capabilities of the RCI algorithm. It is found that the proposed mechanism accurately finds and prevents hazardous network operations, such as over-voltage in grid buses, while successfully providing economic value to prosumers’ renewable generation within the scope of a P2P, free market.

Optimal Power Flow Based Economic Generation Scheduling in Day-ahead Power Market

2017 ◽  
Vol 6 (3) ◽  
pp. 124
Author(s):  
Kshitij Choudhary ◽  
Rahul Kumar ◽  
Dheeresh Upadhyay ◽  
Brijesh Singh
Keyword(s):  
Power System ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Congestion Management ◽  
Test Results ◽  
Loss Minimization ◽  
Optimal Power ◽  
Generation Scheduling ◽  
Generation Cost

The present work deals with the economic rescheduling of the generation in an hour-ahead electricity market. The schedules of various generators in a power system have been optimizing according to active power demand bids by various load buses. In this work, various aspects of power system such as congestion management, voltage stabilization and loss minimization have also taken into consideration for the achievement of the goal. The interior point (IP) based optimal power flow (OPF) methodology has been used to obtain the optimal generation schedule for economic system operation. The IP based OPF methodology has been tested on a modified IEEE-30 bus system. The obtained test results shows that not only the generation cost is reduced also the performance of power system has been improved using proposed methodology.

Optimal Rescheduling of Generators for Congestion Management and Benefit Maximization in a Decentralized Bilateral Multi-transactions Power Network

2013 ◽  
Vol 14 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Brijesh Singh ◽  
Ranjit Mahanty ◽  
S.P. Singh
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Congestion Management ◽  
Global Optimum ◽  
Market Model ◽  
Optimal Dispatch ◽  
Optimum Solution ◽  
Decentralized Market

Abstract This paper presents a framework to achieve an optimal power flow solution in a decentralized bilateral multitransaction-based market. An independent optimal dispatch solution has been used for each market. The interior point (IP)-based optimization technique has been used for finding a global economic optimal solution of the whole system. In this method, all the participants try to maximize their own profits with the help of system information announced by the operator. In the present work, a parallel algorithm has been used to find out a global optimum solution in decentralized market model. The study has been carried out on a modified IEEE-30 bus system. The results show that the suggested decentralized approach can provide a better optimal solution. The obtained results show the effectiveness of IP optimization-based optimal generator schedule and congestion management in the decentralized market.

An electricity market model with generation capacity expansion under uncertainty

2012 ◽  
Author(s):  
Andreas Schroeder
Keyword(s):  
Electricity Market ◽  
Electricity Generation ◽  
Power Plants ◽  
Thermal Power ◽  
Capacity Expansion ◽  
Carbon Price ◽  
Market Model ◽  
Investment Incentives ◽  
Investment Portfolio ◽  
Generation Capacity

This article presents an electricity dispatch model with endogenous electricity generation capacity expansion for Germany over the horizon 2035. The target is to quantify how fuel and carbon price risk impacts investment incentives of thermal power plants. Results point to findings which are in line with general theory: Accounting for stochasticity increases investment levels overall and the investment portfolio tends to be more diverse.

scholarly journals Exploring the Profitability and Efficiency of Variable Renewable Energy in Spot Electricity Market: Uncovering the Locational Price Disadvantages

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2820
Author(s):  
Ruhang Xu ◽  
Zhilin Liu ◽  
Zhuangzhuang Yu
Keyword(s):  
Renewable Energy ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Strategic Behavior ◽  
Market Model ◽  
Ancillary Service ◽  
Service Levels ◽  
Locational Marginal Price ◽  
Strategic Market

While variable renewable energy (VRE) has been developed for decades, VRE market participation is developing relatively slowly, despite the potential economic efficiency it may bring. This paper tries to specify the efficiency of VRE in a deregulated pool-based electricity market. Based on standard pool-based market design, this paper built a direct current optimal power flow (DC-OPF) based simplified 2-settlement spot electricity market model conjugating electricity and ancillary service clearing. To address the outcomes of the imperfect market in the real world, this paper studied the consequences brought by agents’ learning and strategic behaviors. Simulations under different ancillary service levels and reliability cost levels are carried out. The results show that VRE may be unprofitable in the market, especially when learning and strategic behavior is considered. Learning and strategic market behavior will also hamper the role of VRE as a “better” energy source. This paper shows and proves a locational marginal price (LMP) disadvantage phenomenon, which will lead to low profitability of VRE. Three major suggestions are given based on the results.

scholarly journals Optimal power flow based congestion management using enhanced genetic algorithms

2019 ◽  
Vol 9 (2) ◽  
pp. 875 ◽  
Author(s):  
Seong-Cheol Kim ◽  
Surender Reddy Salkuti
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Minimization ◽  
Congestion Management ◽  
Market Model ◽  
Congestion Cost ◽  
Optimal Power ◽  
Generation Cost

<p>Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.</p>

Optimal Power Flow Based Economic Generation Scheduling in Day-ahead Power Market

2017 ◽  
Vol 6 (3) ◽  
pp. 123
Author(s):  
Kshitij Choudhary ◽  
Rahul Kumar ◽  
Dheeresh Upadhyay ◽  
Brijesh Singh
Keyword(s):  
Power System ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Congestion Management ◽  
Test Results ◽  
Loss Minimization ◽  
Optimal Power ◽  
Generation Scheduling ◽  
Generation Cost

The present work deals with the economic rescheduling of the generation in an hour-ahead electricity market. The schedules of various generators in a power system have been optimizing according to active power demand bids by various load buses. In this work, various aspects of power system such as congestion management, voltage stabilization and loss minimization have also taken into consideration for the achievement of the goal. The Interior Point (IP) based Optimal Power Flow (OPF) methodology has been used to obtain the optimal generation schedule for economic system operation. The IP based OPF methodology has been tested on a modified IEEE-30 bus system. The obtained test results shows that not only the generation cost is reduced also the performance of power system has been improved using proposed methodology.

Designing the Electricity Market with Energy Storage Devices

2020 ◽  
Vol 12 (12) ◽  
pp. 31-43
Author(s):  
Tatiana A. VASKOVSKAYA ◽  
◽  
Boris A. KLUS ◽  
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Energy System ◽  
Energy Storage Systems ◽  
Storage Model ◽  
Optimal Power ◽  
Wide Range

The development of energy storage systems allows us to consider their usage for load profile leveling during operational planning on electricity markets. The paper proposes and analyses an application of an energy storage model to the electricity market in Russia with the focus on the day ahead market. We consider bidding, energy storage constraints for an optimal power flow problem, and locational marginal pricing. We show that the largest effect for the market and for the energy storage system would be gained by integration of the energy storage model into the market’s optimization models. The proposed theory has been tested on the optimal power flow model of the day ahead market in Russia of 10000-node Unified Energy System. It is shown that energy storage systems are in demand with a wide range of efficiencies and cycle costs.

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