scholarly journals Learning Optimal Solutions for Extremely Fast AC Optimal Power Flow

2020 ◽  
Author(s):  
Ahmed S. Zamzam ◽  
Kyri Baker
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Solutions ◽  
Optimal Power

scholarly journals Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 250 ◽  
Author(s):  
Yahui Li ◽  
Yang Li
Keyword(s):  
Decision Analysis ◽  
Evolutionary Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Decision Makers ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Optimal Power ◽  
Knee Point

To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated decision analysis technique is utilized to provide decision makers with decision supports by combining fuzzy c-means (FCM) clustering and grey relational projection (GRP) method together. In this way, the best compromise solutions (BCSs) that represent decision makers’ different, even conflicting, preferences can be automatically determined from the set of Pareto-optimal solutions. The primary contribution of the proposal is the innovative application of many-objective optimization together with decision analysis for addressing MaOPF problems. Through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system, it is verified that our approach is suitable for addressing the MaOPF problem of power systems.

Multi-Objective Optimal Power Flow Using Efficient Evolutionary Algorithm

2017 ◽  
Vol 18 (2) ◽  
Author(s):  
S. Surender Reddy ◽  
P.R Bijwe
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Stability Index ◽  
Pareto Optimal ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Fuel Cost ◽  
Pareto Optimal Front ◽  
Efficient Approach ◽  
Optimal Power

Abstract A novel efficient multi-objective optimization (MOO) technique for solving the optimal power flow (OPF) problem has been proposed in this paper. In this efficient approach uses the concept of incremental power flow model based on sensitivities and some heuristics. The proposed approach is designed to overcome the main drawback of conventional MOO approach, i. e., the excess computational time. In the present paper, three objective functions i. e., generation cost, system losses and voltage stability index are considered. In the proposed efficient MOO approach, the first half of the specified number of Pareto optimal solutions are obtained by optimizing the fuel cost objective while considering other objective (i. e., system loss or voltage stability index) as constraint while the second half is obtained in a vice versa manner. After obtaining the total Pareto optimal solutions, they are sorted in the ascending order of fuel cost objective function value obtained for each solution leads to the Pareto optimal front. The proposed efficient approach is implemented using the differential evolution (DE) algorithm. The proposed efficient MOO approach can effectively handle the complex non-linearities, discrete variables, discontinuities and multiple objectives. The effectiveness of the proposed approach is tested on standard IEEE 30 bus test system. The simulation studies show that the Pareto optimal solutions obtained with proposed efficient MOO approach are diverse and well distributed over the entire Pareto optimal front. The simulation results indicate that the execution speed of proposed efficient MOO approach is approximately 10 times faster than the conventional evolutionary based MOO approaches.

Optimal Power Flow Using Newton’s Method

2012 ◽  
Vol 3 (2) ◽  
pp. 167-169
Author(s):  
F.M.PATEL F.M.PATEL ◽  
◽  
N. B. PANCHAL N. B. PANCHAL
Keyword(s):  
Newton’S Method ◽  
Newton's Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Power

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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