scholarly journals Collaborative Autonomous Optimization of Interconnected Multi-Energy Systems with Two-Stage Transactive Control Framework

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 171 ◽  
Author(s):  
Yizhi Cheng ◽  
Peichao Zhang ◽  
Xuezhi Liu
Keyword(s):  
Cost Minimization ◽  
Mathematical Proof ◽  
Energy Systems ◽  
Energy Integration ◽  
Two Stage ◽  
Control Framework ◽  
Upper Level ◽  
Transformer Overloading ◽  
Cost Minimization Problem ◽  
Autonomous Optimization

Motivated by the benefits of multi-energy integration, this paper establishes a bi-level two-stage framework based on transactive control, to achieve the optimal energy provision among interconnected multi-energy systems (MESs). At the lower level, each MES autonomously determines the optimal setpoints of its controllable assets by solving a cost minimization problem, in which rolling horizon optimization is adopted to deal with the load and renewable energies’ stochastic features. A technique is further implemented for optimization model convexification by relaxing storages’ complementarity constraints, and its mathematical proof verifies the exactness of the relaxation. At the upper level, a coordinator is responsible for minimizing total costs of interconnected MESs while preventing transformer overloading. This collaborative problem is solved iteratively in a proposed two-stage transactive control framework that is compatible with operational time requirement while retaining scalability, information privacy and operation authority of each MES. The effectiveness of the proposed framework is verified by simulation cases that conduct a detailed analysis of the collaborative autonomous optimization mechanism.

scholarly journals Sustainable energy path

2005 ◽  
Vol 9 (3) ◽  
pp. 7-14 ◽  
Author(s):  
Hiromi Yamamoto ◽  
Kenji Yamaji
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Fossil Fuels ◽  
Cost Minimization ◽  
Sustainable Energy ◽  
Energy Systems ◽  
Primary Energy ◽  
Primary Energy Consumption ◽  
Photo Voltaic ◽  
Global Energy Supply

The uses of fossil fuels cause not only the resources exhaustion but also the environmental problems such as global warming. The purposes of this study are to evaluate paths to ward sustainable energy systems and roles of each renewable. In order to realize the purposes, the authors developed the global land use and energy model that figured the global energy supply systems in the future considering the cost minimization. Using the model the authors conducted a simulation in C30R scenario, which is a kind of strict CO2 emission limit scenarios and reduced CO2 emissions by 30% compared with Kyoto protocol forever scenario, and obtained the following results. In C30R scenario bio energy will supply 33% of all the primary energy consumption. How ever, wind and photo voltaic will supply 1.8% and 1.4% of all the primary energy consumption, respectively, because of the limits of power grid stability. The results imply that the strict limits of CO2 emissions are not sufficient to achieve the complete renewable energy systems. In order to use wind and photo voltaic as major energy resources we need not only to reduce the plant costs but also to develop unconventional renewable technologies. .

scholarly journals Bi-Level Optimization for Electricity Transaction in Smart Community With Modular Pump Hydro Storage

2020 ◽  
Author(s):  
Yang Chen ◽  
Xiao Kou ◽  
Mohammed Olama ◽  
Helia Zandi ◽  
Chenang Liu ◽  
...  
Keyword(s):  
Stackelberg Game ◽  
Cost Minimization ◽  
Necessary Optimality Conditions ◽  
Local Energy ◽  
Energy Prices ◽  
Profit Distribution ◽  
Level Model ◽  
Upper Level ◽  
Smart Community ◽  
Best Responses

Abstract Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Particle Swarm Optimization for Cost Reduction in Mobile Location Management Using Reporting Cell Planning Approach

2017 ◽  
pp. 171-189 ◽  
Author(s):  
Smita Parija ◽  
Sudhansu Sekhar Singh ◽  
Swati Swayamsiddha
Keyword(s):  
Particle Swarm Optimization ◽  
Cellular Network ◽  
Cost Minimization ◽  
Location Management ◽  
Particle Swarm ◽  
Location Update ◽  
Swarm Optimization ◽  
Cell Planning ◽  
Wireless Mobile Communication ◽  
Cost Minimization Problem

Location management is a very critical and intricate problem in wireless mobile communication which involves tracking the movement of the mobile users in the cellular network. Particle Swarm Optimization (PSO) is proposed for the optimal design of the cellular network using reporting cell planning (RCP) strategy. In this state-of-the-art approach, the proposed algorithm reduces the involved total cost such as location update and paging cost for the location management issue. The same technique is proved to be a competitive approach to different existing test network problems showing the efficacy of the proposed method through simulation results. The result obtained is also validated for real network data obtained from BSNL, Odisha. Particle Swarm Optimization is used to find the optimal set of reporting cells in a given cellular network by minimizing the location management cost. This RCP technique applied to this cost minimization problem has given improved result as compared to the results obtained in the previous literature.

Core-Based GRASP for Delay-Constrained Group Communications

2013 ◽  
Vol 4 (4) ◽  
pp. 1-22
Author(s):  
Zrinka Lukač ◽  
Manuel Laguna
Keyword(s):  
Data Stream ◽  
Cost Minimization ◽  
Multimedia Technology ◽  
Computational Results ◽  
Adaptive Search ◽  
End To End Delay ◽  
Efficient Delivery ◽  
Asymmetric Networks ◽  
Cost Minimization Problem

The recent development in network multimedia technology has created numerous real-time multimedia applications where the Quality-of-Service (QoS) requirements are quite rigorous. This has made multicasting under QoS constraints one of the most prominent routing problems. The authors consider the problem of the efficient delivery of data stream to receivers for multi-source communication groups. Efficiency in this context means to minimize cost while meeting bounds on the end-to-end delay of the application. The authors adopt the multi-core approach and utilize SPAN (Karaman and Hassane, 2007)—a core-based framework for multi-source group applications — as the basis to develop greedy randomized adaptive search procedures (GRASP) for the associated constrained cost minimization problem. The procedures are tested in asymmetric networks and computational results show that they consistently outperform their counterparts in the literature.

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