Robust Optimization Method for Obtaining Optimal Scheduling of Active Distribution Systems Considering Uncertain Power Market Price

2019 ◽  
pp. 293-308 ◽  
Author(s):  
Morteza Nazari-Heris ◽  
Saeed Abapour ◽  
Behnam Mohammadi-ivatloo
Keyword(s):  
Robust Optimization ◽  
Distribution Systems ◽  
Market Price ◽  
Power Market ◽  
Optimization Method ◽  
Optimal Scheduling

scholarly journals Optimal Scheduling Method of Controllable Loads in Smart Home Considering Re-Forecast and Re-Plan for Uncertainties

2019 ◽  
Vol 9 (19) ◽  
pp. 4064 ◽  
Author(s):  
Akihiro Yoza ◽  
Kosuke Uchida ◽  
Shantanu Chakraborty ◽  
Narayanan Krishna ◽  
Mitsunaga Kinjo ◽  
...  
Keyword(s):  
Smart Home ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimization Method ◽  
Optimal Scheduling ◽  
Optimization Approach ◽  
Operational Cost ◽  
System Operator ◽  
Scheduling Method ◽  
Smart Grid Technology

Renewable energies (REs) such as photovoltaic generation (PV) have been gaining attention in distribution systems. Recently, houses with PV and battery systems, as well as electric vehicles (EV) are expected to contribute to not only the suppression of global warming but also reducing electricity bill on the consumer side. However, there are numerous challenges with the introduction of REs at the demand side such as the actual output of REs often deviating from the forecasted output, which causes fluctuation of the power flow and this is challenging for the distribution or transmission system operator. For this challenge, it is expected that smart grid technology using controllable loads such as a fixed battery or EV battery, can suppress fluctuation of power flow. This paper presents a decision method of optimal scheduling of controllable loads to suppress the fluctuation of power flow by PV output in the smart home. An optimization method to cope with uncertainties such as variability of PV power and effective forecasting methods are considered in the proposed scheme. In order to decrease the expected operational cost and to validate the robustness for the uncertainty’s optimization approach, statistical analysis is executed for the optimal scheduling scheme. From the optimization results, the proposed methodology suppressed the fluctuation of power flow in the smart home and also minimized the consumer operational cost.

Optimal scheduling of electric vehicles aggregator under market price uncertainty using robust optimization technique

2020 ◽  
Vol 117 ◽  
pp. 105628 ◽  
Author(s):  
Yan Cao ◽  
Liang Huang ◽  
Yiqing Li ◽  
Kittisak Jermsittiparsert ◽  
Hamed Ahmadi-Nezamabad ◽  
...  
Keyword(s):  
Robust Optimization ◽  
Electric Vehicles ◽  
Optimization Technique ◽  
Market Price ◽  
Optimal Scheduling ◽  
Price Uncertainty

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Adaptive Robust Optimization-Based Optimal Operation of Microgrids Considering Uncertainties in Arrival and Departure Times of Electric Vehicles

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2646 ◽  
Author(s):  
Se-Hyeok Choi ◽  
Akhtar Hussain ◽  
Hak-Man Kim
Keyword(s):  
Robust Optimization ◽  
Electric Vehicles ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Market Price ◽  
Optimal Operation ◽  
Worst Case ◽  
Price Signals ◽  
Power Trading ◽  
The Impact

The optimal operation of microgrids is challenging due to the presence of various uncertain factors, i.e., renewable energy sources, loads, market price signals, and arrival and departure times of electric vehicles (EVs). In order to incorporate these uncertainties into the operation model of microgrids, an adaptive robust optimization-based operation method is proposed in this paper. In particular, the focus is on the uncertainties in arrival and departure times of EVs. The optimization problem is divided into inner and outer problems and is solved iteratively by introducing column and constraint cuts. The unit commitment status of dispatchable generators is determined in the outer problem. Then, the worst-case realizations of all the uncertain factors are determined in the inner problem. Based on the values of uncertain factors, the generation amount of dispatchable generators, the amount of power trading with the utility grid, and the charging/discharging amount of storage elements are determined. The performance of the proposed method is evaluated using three different cases, and sensitivity analysis is carried out by varying the number of EVs and the budget of uncertainty. The impact of the budget of uncertainty and number of EVs on the operation cost of the microgrid is also evaluated considering uncertainties in arrival and departure times of EVs.

Research on Human and Vehicles Coordination Evacuation Simulation Optimization Method under Emergency Incidents

2011 ◽  
Vol 71-78 ◽  
pp. 3091-3096
Author(s):  
Yun Long Ma ◽  
Jian Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Simulation Optimization ◽  
Optimization Method ◽  
Emergency Planning ◽  
Optimal Scheduling ◽  
Regular Pattern ◽  
Improved Genetic Algorithm ◽  
Evacuation Simulation ◽  
Evacuation Strategy ◽  
Coordination System

Among researches on crowd flow evacuation under emergency, there are no deep touch of coordinating evacuation strategy of crowd and traffic, and also can not set models and simulate the whole picture of evacuation. The purpose of this research is to realize the coordinating evacuation of both traffic and crowd. The author divided the situations into Not Intervene and May Intervene, analyzed the coordination system and probed the model of coordinating evacuation. A series of coordinate evacuation method has been put forward based on swarm intelligence and simulation optimization. Based on the result of crowd simulation and Ant colony algorithm, in order to find the optimal traffic evacuation proposal, the author took use of the improved Genetic Algorithm as well as the distributed coordinating simulation, finally found a systematic optimal scheduling program. Also the internal regular pattern of coordinating evacuation has also been revealed. All these will provide support for emergency planning and decision making.

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