Multi-Objective Operation Optimization of a Micro-Grid Using Modified Honey Bee Mating Optimization Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 1593-1597 ◽  
Author(s):  
Li Zhen Wu ◽  
Xiao Hong Hao
Keyword(s):  
Honey Bee ◽  
Renewable Energy Sources ◽  
Operating Cost ◽  
Pollutant Emissions ◽  
Superior Performance ◽  
Emissions Reduction ◽  
Nonlinear Constraint ◽  
Multi Objective ◽  
Micro Grid ◽  
Honey Bee Mating Optimization

Recently, it becomes the head of concern for the Micro-grid to derive an optimal operational planning with regard to energy costs minimization, pollutant emissions reduction and better utilization of renewable energy sources (RESs), which accompanied by a Wind Turbine/Fuel Cell/Photovoltaic and Battery hybrid power source to level the power mismatch or to store the surplus of energy when its needed. In this paper, a new method based on multi-objective Modified Honey Bee Mating Optimization (MHBMO) algorithm is proposed and implemented to dispatch the generations in a typical micro-grid considering economy and emission as competitive objectives. The problem is formulated as a nonlinear constraint multi-objective optimization problem to minimize the total operating cost and the net emission simultaneously. The proposed algorithm is tested on a typical MG and its superior performance is compared to those from other evolutionary algorithms such as GA (Genetic Algorithm) and the original Honey Bee Mating Optimization (HBMO).

scholarly journals Multi-Objective Day-Ahead Optimal Scheduling of Isolated Microgrid Considering Flexibility

2018 ◽  
Vol 53 ◽  
pp. 01024
Author(s):  
Liang Zhang ◽  
Bo Pang ◽  
Ruipeng Yi ◽  
Pengyu Gai ◽  
Chunqing Xin ◽  
...  
Keyword(s):  
Renewable Energy Sources ◽  
Operating Cost ◽  
Optimal Solution ◽  
Economic Losses ◽  
Optimal Operating ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Schedule Flexibility ◽  
Optimal Solution Set ◽  
Optimizing Model

In isolated microgrid, renewable energy sources including photovoltaic and wind power, have the nature of intermittence and variability. Making a reasonable day-ahead generation schedule could improve system ability to cope with uncertainty. Therefore, based on day-ahead generation schedule, flexibility insufficiency rate is proposed considering economy and flexibility. Aiming at the lowest flexibility insufficiency rate and optimal operating cost, a day-ahead generation schedule optimizing model of isolated microgrid is established. Under multi-objective particle swarm optimization, Pareto optimal solution set of the day-ahead generation schedule is found. Simulation results of an isolated microgrid show that, day-ahead generation schedule made with the proposed method can improve ability of power system to cope with uncertainty and reduce economic losses.

scholarly journals Cooperative Multi-Objective Optimization of DC Multi-Microgrid Systems in Distribution Networks

2021 ◽  
Vol 11 (19) ◽  
pp. 8916
Author(s):  
Zhiwen Xu ◽  
Changsong Chen ◽  
Mingyang Dong ◽  
Jingyue Zhang ◽  
Dongtong Han ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Operating Cost ◽  
Distribution Networks ◽  
Double Loop ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Ac Converters

By constructing a DC multi-microgrid system (MMGS) including renewable energy sources (RESs) and electric vehicles (EVs) to coordinate with the distribution network, the utilization rate of RESs can be effectively improved and carbon emissions can be reduced. To improve the economy of MMGS and reduce the network loss of the distribution network, a cooperative double-loop optimization strategy is proposed. The inner-loop economic dispatching reduces the daily operating cost of MMGS by optimizing the active power output of RESs, EVs, and DC/AC converters in MMGS. The outer-loop reactive power optimization reduces the network loss of the distribution network by optimizing the reactive power of the bidirectional DC/AC converters. The double-loop, which synergistically optimizes the economic cost and carbon emissions of MMGS, not only improves the economy of MMGS and operational effectiveness of the distribution network but also realizes the low-carbon emissions. The Across-time-and-space energy transmission (ATSET) of the EVs is considered, whose impact on economic dispatching is analyzed. Particle Swarm Optimization (PSO) is applied to iterative solutions. Finally, the rationality and feasibility of the cooperative multi-objective optimization model are proved by a revised IEEE 33-node system.

scholarly journals Multi-objective multi-verse optimization of renewable energy sources-based micro-grid system: Real case

2021 ◽  
Author(s):  
Ashraf Mohamed Hemeida ◽  
Ahmed Shaban Omer ◽  
Ayman M. Bahaa-Eldin ◽  
Salem Alkhalaf ◽  
Mahrous Ahmed ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Real Case ◽  
Energy Sources ◽  
Grid System ◽  
Multi Objective ◽  
Micro Grid

Micro-Grid Multi-Objective Optimizing Operation

2014 ◽  
Vol 1070-1072 ◽  
pp. 1307-1311
Author(s):  
Fang Liu ◽  
Xiu Yang
Keyword(s):  
Operation Mode ◽  
Operating Cost ◽  
Single Object ◽  
Multi Objective ◽  
Pollution Emission ◽  
Economic Operation ◽  
Micro Grid ◽  
Optimizing Model ◽  
Minimum Operating ◽  
The Membership Function

Reducing environmental pollution and achieving economic operation have become focus of the research about micro-grid (MG). The minimum operating cost and the minimum pollution emission cost are taken as optimizing objects, and the multi-object optimizing model of MG is established. The membership function is used to process multi-objective function, then the conversion of multi-object to single object is achieved. Genetic Algorithm is used to optimize the operating state of each unit, then the best operation mode is formed.

scholarly journals Multi-Objective Economic Dispatch of Cogeneration Unit with Heat Storage Based on Fuzzy Chance Constraint

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 103 ◽  
Author(s):  
Xiuyun Wang ◽  
Junyu Tian ◽  
Rutian Wang ◽  
Jiakai Xu ◽  
Shaoxin Chen ◽  
...  
Keyword(s):  
Wind Power ◽  
Heat Storage ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Operating Cost ◽  
Pollutant Emissions ◽  
Stable Operation ◽  
Economic Costs ◽  
Spinning Reserve ◽  
Multi Objective

With the increasing expansion of wind power, its impact on economic dispatch of power systems cannot be ignored. Adding a heat storage device to a traditional cogeneration unit can break the thermoelectric coupling constraint of the cogeneration unit and meet the economic and stable operation of a power system. In this paper, an economy-environment coordinated scheduling model with the lowest economic cost and the lowest pollutant emissions is constructed. Economic costs include the cost of conventional thermal power generating units, the operating cost of cogeneration units, and the operating cost of wind power. At the same time, green certificate costs are introduced into the economic costs to improve the absorption of wind power. Pollutant emissions include SO2 and NOx emissions from conventional thermal power units and cogeneration units. The randomness and uncertainty of wind power output are fully considered, and the prediction error of wind power is fuzzy treated according to the fuzzy random theory, and the electric power balance and spinning reserve fuzzy opportunity conditions are established, which are converted into the explicit equivalent. The improved multi-objective particle swarm optimization (MOPSO) was used to solve the model. With this method, the validity of the model is verified by taking a system with 10 machines as an example.

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