Spinning Reserve Optimization Model Based on Bi-Level Programming

2011 ◽  
Vol 354-355 ◽  
pp. 1047-1050
Author(s):  
Da Wei Huang ◽  
Ming Lei
Keyword(s):  
Power Systems ◽  
Electricity Market ◽  
Cost Minimization ◽  
Test System ◽  
Spinning Reserve ◽  
Proposed Model ◽  
Generation Cost ◽  
Security And Reliability ◽  
Upper Level

How to determine spinning reserve reasonably in electricity market is one of the key questions which guarantee the security and reliability of power systems. For this issue, based on bi-level programming theory, an optimal model of spinning reserve is established in this paper. In this model the generation cost minimization and the reserve cost minimization are the upper level and lower level optimization object separately, and the network and “N-1”security constraints of the power system are also considered. The determination of reserve capacity and the reliability level are related, and the reserve rate of each unit is determined. And an IEEE-14 nodes test system case is used to demonstrate the feasibility and rationality of this proposed model.

scholarly journals Voltage Coordination via Communication in Large-Scale Multi-Area Power Systems. Part II: Simulation Results

2012 ◽  
Vol 433-440 ◽  
pp. 7183-7189
Author(s):  
Mohammad Moradzadeh ◽  
René Boel
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electricity Market ◽  
Large Scale ◽  
Test System ◽  
Distributed Model ◽  
Future Evolution ◽  
Distributed Model Predictive Control ◽  
Control Actions ◽  
Simulation Results

This two-part paper deals with the coordination of the control actions in a network of many interacting components, where each component is controlled by independent control agents. As a case study we consider voltage control in large electric power systems where ever-increasing pressures from the liberalization and globalization of the electricity market has led to partitioning the power system into multiple areas each operated by an independent Transmission System Operator (TSO). Coordination of local control actions taken by those TSOs is a very challenging problem as poorly coordinated operation of TSOs may endanger the power system security by increasing the risk of blackouts. This second part of the paper presents simulation results on a 12-bus 3-area test system, using the distributed model predictive control paradigm in order to design a coordinating model-based feedback controller. Coordination requires that each agent has some information on what the future evolution of its power flows to and from its neighbors will be. It will be shown that how the communication between agents can avoid voltage collapse in circumstances where classical uncoordinated controllers fail.

scholarly journals Optimal Decision-Making Strategy of an Electric Vehicle Aggregator in Short-Term Electricity Markets

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2413 ◽  
Author(s):  
Homa Rashidizadeh-Kermani ◽  
Hamid Najafi ◽  
Amjad Anvari-Moghaddam ◽  
Josep Guerrero
Keyword(s):  
Decision Making ◽  
Electric Vehicle ◽  
Electricity Markets ◽  
Strong Duality ◽  
Test System ◽  
Optimal Decision ◽  
Measurement Tool ◽  
Proposed Model ◽  
Level Problem ◽  
Upper Level

This paper proposes the problem of decision making of an electric vehicle (EV) aggregator in a competitive market in the presence of different uncertain resources. In the proposed model, a bi-level problem is formulated where, in the upper-level, the objective of the aggregator is to maximize its expected profit through its interactions and, in the lower-level, the EV owners minimize their payments. Therefore, the objectives of the upper and the lower-level are contrary. To solve the obtained nonlinear bi-level program, Karush-Kuhn-Tucker (KKT) optimality conditions and strong duality are applied to transform the initial problem into a linear single-level problem. Moreover, to deal with various uncertainties, including market prices, EVs charge/discharge demands and the prices offered by rivals, a risk measurement tool is incorporated into the problem. The proposed model is finally applied to a test system and its effectiveness is evaluated. Simulation results show that the proposed approach has the potential to offer significant benefits to the aggregator and EV owners for better decision-making in an uncertain environment. During different situations, it is observed that with increasing risk-aversion factor, as the aggregator tries to hedge against volatilities, its purchases from day-ahead and negative balancing markets decreases significantly. However, the participation of EV aggregator in the positive balancing market increases accordingly to make more profit.

Short Term Price Forecasting Using Adaptive Generalized Neuron Model

2018 ◽  
Vol 9 (3) ◽  
pp. 44-56 ◽  
Author(s):  
Nitin Singh ◽  
S. R. Mohanty
Keyword(s):  
Power Systems ◽  
Electricity Market ◽  
Neuron Model ◽  
Linear Mapping ◽  
Electricity Price ◽  
Price Forecasting ◽  
Training Time ◽  
Proposed Model ◽  
Artificial Neural ◽  
Future Demands

This article described how in the competitive deregulated electricity market forecasting has become one of the essential planning tool that assists the planners in preparing the power systems for future demands. The commercial success of the market players depends on their competitive bidding strategy which is suffuicient enough to meet the regulatory requirements and minimize the cost. Artificial neural networks due to their capability of non-linear mapping finds extensive application in the field of price forecasting. Although, they are extensively used as forecasting model, they have certain limitations which are detrimental to system performance. The training time of the artificial neural network is affected by the complexity of the system, and moreover, they require a large amount of data for complex problems. The worl presented in this article deals with the application of the generalized neuron model for forecasting the electricity price. The generalized neuron model overcomes the limitation of the conventional ANN. The electricity price of the New South Wales electricity market is forecast to test the performance of the proposed model. The free parameters of the proposed model are trained using fuzzy tuned genetic algorithms to increase efficacy of the model.

Active Power Optimization Considering both Generation Cost and Network Loss

2014 ◽  
Vol 556-562 ◽  
pp. 1643-1646
Author(s):  
Xue Fei Chang ◽  
Xiang Yu Lv ◽  
De Xin Li
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Weighting Factor ◽  
Active Power ◽  
Model Combining ◽  
Proposed Model ◽  
Generation Cost ◽  
Objective Model

In order to improve the calculation efficiency, active power and reactive power are usually optimized separately in optimal power flow considering the decoupling characteristic. However, this would decrease the economy performance of power system. This paper proposed a weighting factor to formulate a multi-objective model, combining the generation cost and system network loss together. The optimization problem is performed using genetic algorithms and quadratic programming respectively. Finally, the feasibility and efficiency of the proposed model are verified with the IEEE 14 Bus test system.

The Equilibrium Model of Electricity Market with Consideration of the Pumped Storage GenCo

2012 ◽  
Vol 614-615 ◽  
pp. 1966-1972
Author(s):  
Jian Lin Yang ◽  
Hui Qing Lu ◽  
Fang Di Shi
Keyword(s):  
Electricity Market ◽  
Test System ◽  
Bidding Strategy ◽  
Simulation Tool ◽  
Storage Unit ◽  
Bidding Strategies ◽  
Efficient Simulation ◽  
Proposed Model ◽  
Pumped Storage ◽  
Mixed Linear Complementarity Problem

Pumped storage is the largest-capacity form of grid energy storage available. A multi-period oligopolistic model for analyzing the bidding strategies of pumped storage GenCo (PSG) is proposed in this paper. In the pumping periods, the pumped storage unit (PSU) is simulated as a special load. While in generating periods, PSU is treated as a normal generator. In this model, all GenCos are assumed to exercise Cournot strategies to maximize their own profits. The resulting equilibrium formulation is established in terms of a mixed linear complementarity problem. The purpose of this paper is to provide an efficient simulation tool for the PSG to determine its bidding strategy in an oligopolistic environment. The proposed model can also be used to study various factors that may impact PSG’s profit. Results of a six-bus test system are analyzed to illustrate the characteristics of the proposed model.

scholarly journals A Multi-Criteria Decision Framework for Optimal Augmentation of Transmission Grid - Addressing a Tool for Sensitive Zone Detection in Electricity Market

2008 ◽  
Vol 9 (4) ◽  
Author(s):  
Mohammad R. Hesamzadeh ◽  
Nasser Hosseinzadeh ◽  
Peter J Wolfs
Keyword(s):  
Sensitivity Analysis ◽  
Power Systems ◽  
Electricity Market ◽  
Large Scale ◽  
Test System ◽  
Transmission System ◽  
System Structure ◽  
Transmission Grid ◽  
Expansion Planning ◽  
Transmission Expansion

Transmission system structure has an essential effect on the reliability of the power system and electricity market performance, especially when producers bid strategically. As part of on-going research on the design of a robust algorithm for expansion planning of the transmission grid in the Australian electricity market, this paper presents a framework which addresses: (1) the security of power delivery to the load points of the transmission system in case of single line outages; (2) the minimization of transmission system lost load; (3) an efficient electricity market for market participants; (4) construction and maintenance costs of transmission augmentation options; and (5) operation efficiency of the transmission grid.The suggested algorithm benefits from the dynamic programming and sensitivity analysis approaches along with the aggregation method in its multi-criteria decision-making to locate the optimum configuration of a future transmission system. A set of indices, which account for impacts of the augmentation options of the transmission grid on five aforementioned reliability and market criteria, are proposed and used in the optimum framework for expansion planning of the transmission grid.Although the methodology is promising for expansion planning of the transmission system, considering the sensitivity analysis concept employed, the proposed methodology would be suitable to detect the sensitive areas of the transmission system to be expanded. The tool would be very useful in the case of large scale power systems for a smart reduction of the transmission expansion options.The proposed methodology has been applied to a 6-bus and a modified IEEE 30-bus test system to show the effectiveness of the sensitivity-based algorithm.

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>

scholarly journals Implementation effects of economics and market operations based model for traditionally integrated power systems

2021 ◽  
Vol 21 (3) ◽  
pp. 1247
Author(s):  
Youssef Mobarak ◽  
Nithiyananthan Kannan ◽  
Fahd Alharbi ◽  
Faisal Albatati
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electricity Market ◽  
Optimal Power Flow ◽  
Optimization Problem ◽  
System Operation ◽  
Power System Operation ◽  
Economic Operation ◽  
Generation Cost ◽  
Integrated Power Systems

<p><span id="docs-internal-guid-c7335217-7fff-17cb-2b2b-3da634576ee1"><span>The main objective of this paper is to introduce power system economic operations in traditionally integrated power systems and market operations in deregulated power systems and study its effects. The power system economic operation is mathematically treated as an optimization problem. Also, a function of economic operation is to minimize generation cost, transmission losses, and so on, subject to power system operation constraints. In this paper, we start from generation cost formulations and introduce traditional economic dispatch model, optimal power flow model, and unit commitment model. With the deregulation of the power industry, integrated power system is unbundled to generation, transmission, and distribution. Electricity is traded in the wholesale market. Small customers purchase energy from electricity retailers through the retail market. The electricity market is operated for energy trading while satisfying power system operation requirements. Electricity market is mathematically modelled as an optimization problem that is subject to power system operation constraints and market operation constraints.</span></span></p>

scholarly journals Disturbance-State Modeling and Oscillation Analysis of Modular Multilevel Converters under P/Q Control Mode

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1424
Author(s):  
Facai Xing ◽  
Zheng Xu ◽  
Zheren Zhang ◽  
Huanqing Xiao
Keyword(s):  
Power Systems ◽  
State Space ◽  
Test System ◽  
Control Mode ◽  
Multilevel Converters ◽  
Steady State Condition ◽  
Loop Control ◽  
Oscillation Analysis ◽  
Proposed Model ◽  
Modular Multilevel Converters

To investigate the oscillation problems in power systems with modular multilevel converters (MMCs), a disturbance-state model of the MMC under P/Q control mode is established based on the harmonic state-space (HSS) method. Firstly, the basic structure of the MMC with P/Q control is presented, including the circuit structure and the controller structure. Next, the dynamic characteristics of each module in the MMC are described with the time-domain state-space model or the s-domain transfer function. The complete controller structure is considered, including the P/Q outer-loop controller, the inner-loop control, the phase-locked loop (PLL), the circulating current suppression control (CCSC) and the control delay. On the basis, the disturbance-state HSS model of the MMC and its corresponding steady-state condition are established by the HSS method. Lastly, the case studies are performed to verify the accuracy of the proposed model, based on an MMC based test system in PSCAD/EMTDC. Moreover, one oscillation phenomenon in test system is illustrated by analyzing the AC-side impedance characteristics based on the proposed model. The results indicate that the MMC system under P/Q control mode has certain oscillation risk due to its negative resistance effect and the proposed model could be applied to its oscillation analysis.

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