Security Enhanced OPF with Transmission Cost Solution under Bilateral and Multilateral Transactions

2014 ◽  
Vol 573 ◽  
pp. 734-740
Author(s):  
J. Bastin Solai Nazaran ◽  
K. Selvi
Keyword(s):  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Operating Conditions ◽  
Human Group ◽  
Transmission Cost ◽  
Intelligent Technique ◽  
Optimal Power ◽  
Deregulated Electricity Market ◽  
Generation Cost

In a deregulated electricity market, it is important to dispatch the generation in an economical manner. While dispatching it is also important to ensure security under different operating conditions. In this study intelligent technique based solution for optimal power flow is attempted. Transmission cost is calculated using Bialek’s upstream tracing method. Generation cost, transmission costs are combined together for pre and post contingency periods to form objective function. Different bilateral and multilateral conditions are considered for analysis. A human group optimization algorithm is used to find the solution of the problem. IEEE 30 bus system is taken as test systems.

scholarly journals Optimal power flow with transmission cost solution under bilateral and multilateral transactions

2014 ◽  
Vol 63 (2) ◽  
pp. 227-245
Author(s):  
Bastin Solai Nazaran J. ◽  
K. Selvi
Keyword(s):  
Objective Function ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Severity Index ◽  
Test System ◽  
Operating Conditions ◽  
Real Power ◽  
Transmission Cost ◽  
Optimal Power

Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.

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 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.

scholarly journals Multi-objective optimal power flow in the presence of intermittent renewable energy sources

2018 ◽  
Vol 7 (4) ◽  
pp. 2766 ◽  
Author(s):  
S. Surender Reddy
Keyword(s):  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Wind Farms ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost

This paper solves a multi-objective optimal power flow (MO-OPF) problem in a wind-thermal power system. Here, the power output from the wind energy generator (WEG) is considered as the schedulable, therefore the wind power penetration limits can be determined by the system operator. The stochastic behavior of wind power and wind speed is modeled using the Weibull probability density function. In this paper, three objective functions i.e., total generation cost, transmission losses and voltage stability enhancement index are selected. The total generation cost minimization function includes the cost of power produced by the thermal and WEGs, costs due to over-estimation and the under-estimation of available wind power. Here, the MO-OPF problems are solved using the multi-objective glowworm swarm optimiza-tion (MO-GSO) algorithm. The proposed optimization problem is solved on a modified IEEE 30 bus system with two wind farms located at two different buses in the system.  

scholarly journals Optimal Power Flow Considering Intermittent Solar and Wind Generation using Multi-Operator Differential Evolution Algorithm

2021 ◽  
Author(s):  
Md Alamgir Hossain ◽  
Karam M. Sallam ◽  
Seham S. Elsayed ◽  
Ripon K. Chakrabortty ◽  
Michael J. Ryan
Keyword(s):  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Differential Evolution Algorithm ◽  
Adaptive Method ◽  
Optimal Power ◽  
Generation Cost ◽  
Algorithmic Framework ◽  
Evolution Algorithm

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow (OPF) problem and is called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution (DE) operator in a single algorithmic framework. Additionally, an adaptive method (AM) is proposed to update the number of solutions evolved by each DE operator based on both the diversity of population and quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering the intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results and thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%.

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