scholarly journals Optimal Operation of Isolated Micro-Grids-cluster Via Coalitional Energy Scheduling and Reserve Sharing

2021 ◽  
Vol 9 ◽  
Author(s):  
Hasan Saeed Qazi ◽  
Tianyang Zhao ◽  
Nian Liu ◽  
Tong Wang ◽  
Zia Ullah

Microgrids (MG) cluster are isolated from the utility grid but they have the potential to achieve better techno-economic performance by using joint energy and reserve sharing among MGs. This paper proposes a techno-economic framework for the optimal operation of isolated MGs-cluster by scheduling cooperative energy sharing and real-time reserve sharing for ancillary services based on the cooperative game theory. In the day-ahead scheduling, a coalitional sharing scheme is formulated as an adjustable robust optimization (ARO) problem to optimally schedule the energy and reserves of distributed generators (DGs) and energy storage systems (ESSs), thereby responding to the uncertainties of photovoltaic systems, wind turbines, and loads. These uncertainties are the main reason for power system imbalance which is mitigated by regulating the frequency in real-time and a dynamic droop control process is used to realize the reserves in a distributed manner. This control process is embedded into the ARO problem, which is formulated as an affine ARO problem and then transformed into a deterministic optimization problem that is solved by off-shore solvers Apart from the reduction in the operation cost, the frequency restoration can be improved jointly, resulting in the coupled techno-economic contribution of the MGs in the coalition. The contribution of each MG is quantified using shapely value, a cooperative game approach. Simulations are conducted for a case study with 4 MGs and the results demonstrate the merits of the proposed cooperative scheduling scheme.

Author(s):  
Zhiyao Zhong ◽  
Danji Huang ◽  
Kewei Hu ◽  
Xiaomeng Ai ◽  
Jiakun Fang

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 522
Author(s):  
Qiu-Yun Huang ◽  
Ai-Peng Jiang ◽  
Han-Yu Zhang ◽  
Jian Wang ◽  
Yu-Dong Xia ◽  
...  

As the leading thermal desalination method, multistage flash (MSF) desalination plays an important role in obtaining freshwater. Its dynamic modeling and dynamic performance prediction are quite important for the optimal control, real-time optimal operation, maintenance, and fault diagnosis of MSF plants. In this study, a detailed mathematical model of the MSF system, based on the first principle and its treatment strategy, was established to obtain transient performance change quickly. Firstly, the whole MSF system was divided into four parts, which are brine heat exchanger, flashing stage room, mixed and split modulate, and physical parameter modulate. Secondly, based on mass, energy, and momentum conservation laws, the dynamic correlation equations were formulated and then put together for a simultaneous solution. Next, with the established model, the performance of a brine-recirculation (BR)-MSF plant with 16-stage flash chambers was simulated and compared for validation. Finally, with the validated model and the simultaneous solution method, dynamic simulation and analysis were carried out to respond to the dynamic change of feed seawater temperature, feed seawater concentration, recycle stream mass flow rate, and steam temperature. The dynamic response curves of TBT (top brine temperature), BBT (bottom brine temperature), the temperature of flashing brine at previous stages, and distillate mass flow rate at previous stages were obtained, which specifically reflect the dynamic characteristics of the system. The presented dynamic model and its treatment can provide better analysis for the real-time optimal operation and control of the MSF system to achieve lower operational cost and more stable freshwater quality.


2018 ◽  
Vol 15 (8) ◽  
pp. 750-759 ◽  
Author(s):  
Fatemeh Jafari ◽  
S. Jamshid Mousavi ◽  
Jafar Yazdi ◽  
Joong Hoon Kim

Energies ◽  
2017 ◽  
Vol 10 (8) ◽  
pp. 1239 ◽  
Author(s):  
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2013 ◽  
Vol 4 (3) ◽  
pp. 47-57
Author(s):  
Rafik Lasri ◽  
Ignacio Rojas ◽  
Héctor Pomares ◽  
M. Nemiche

A new methodology of Fuzzy Controllers that can change the internal parameters of the controller in real time is presented in this paper. The Self-structured algorithm is able to adapt their rules consequents and re-organize their MFs in real time according to the current state of the controlled plant. Via a simulation of a temperature control process, the authors have proved and demonstrated the effectiveness and usefulness of their control algorithm compared to a conventional FLC under the same condition and using the same Simulated plant.


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