An expected-cost realization-probability optimization approach for the dynamic energy management of microgrid

2022 ◽  
Vol 136 ◽  
pp. 107620
Author(s):  
Jianquan Zhu ◽  
Yelin Zhuo ◽  
Jiajun Chen ◽  
Ye Guo ◽  
Xiemin Mo ◽  
...  
Keyword(s):  
Energy Management ◽  
Optimization Approach ◽  
Expected Cost ◽  
Probability Optimization ◽  
Dynamic Energy Management

scholarly journals AN OPTIMISATION APPROACH TOWARD ONBOARD ENERGY MANAGEMENT SYSTEMS: MODELLING AND SIMULATION OF SUPPLY SIDE

2012 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
HADI SUROSO ◽  
ONTOSENO PENANGSANG
Keyword(s):  
Energy Management ◽  
Economic Dispatch ◽  
Operating Cost ◽  
Electric Power System ◽  
Management Systems ◽  
Supply Side ◽  
Optimization Approach ◽  
Demand Side ◽  
Cost Index ◽  
Energy Management Systems

Optimization in the operation of electric power system is an important task for both inland and onboard. The objective is to minimize operating cost index. Taking advantage of thescheme that onboard operator has the authority not only in the supply side but also in the demandside, an optimization approach toward onboard energy management systems based onintegrated model for supply and demand side is being developed. The model utilizes unit commitmentand economic dispatch in the supply side and load management based on multipleattribute decision-making in the demand side. As a part of the whole concept, this paper focuseson the modeling and simulation of demand side. A user friendly demand side model consistingof Unit Commitment and Economic Dispatch is developed by using LabVIEW, LaboratoryVirtual Instrument Engineering Workbench. Data taken from 3 units of Steam Power Plantare simulated. It is then eventually confirmed that 9% total cost saving can be achieved in theselected load demand range

scholarly journals Energy management strategies for combined heat and electric power micro-grid

2016 ◽  
Vol 20 (4) ◽  
pp. 1091-1103 ◽  
Author(s):  
Marina Barbaric ◽  
Drazen Loncar
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Optimization Technique ◽  
Management Strategies ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Optimization Approach ◽  
Micro Grid ◽  
Additional Rule

The increasing energy production from variable renewable energy sources such as wind and solar has resulted in several challenges related to the system reliability and efficiency. In order to ensure the supply-demand balance under the conditions of higher variability the micro-grid concept of active distribution networks arising as a promising one. However, to achieve all the potential benefits that micro-gird concept offer, it is important to determine optimal operating strategies for micro-grids. The present paper compares three energy management strategies, aimed at ensuring economical micro-grid operation, to find a compromise between the complexity of strategy and its efficiency. The first strategy combines optimization technique and an additional rule while the second strategy is based on the pure optimization approach. The third strategy uses model based predictive control scheme to take into account uncertainties in renewable generation and energy consumption. In order to compare the strategies with respect to cost effectiveness, a residential micro-grid comprising photovoltaic modules, thermal energy storage system, thermal loads, electrical loads as well as combined heat and power plant, is considered.

Velocity Optimization and Robust Energy Management of Connected Power-Split Hybrid Electric Vehicles

2021 ◽  
Author(s):  
Seyedeh Mahsa Sotoudeh ◽  
Baisravan HomChaudhuri
Keyword(s):  
Energy Management ◽  
Time Horizon ◽  
Control Method ◽  
Optimization Approach ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Short Term ◽  
Power Split ◽  
Energy Manager

Abstract This paper focuses on an eco-driving based hierarchical robust energy management strategy for connected automated HEVs in the presence of uncertainty. The proposed control strategy includes a velocity optimizer, which evaluates the optimal vehicle velocity, and a powertrain energy manager, which evaluates the optimal power split between the engine and the battery in a hierarchical framework. The velocity optimizer accounts for regenerative braking and minimizes the total driving power and friction braking over a short control horizon. The hierarchical powertrain energy manager employs a long- and short-term strategy where it first approximately solves its problem over a long time horizon (the whole trip time in this paper) using the traffic data obtained from vehicle-to-infrastructure (V2I) connectivity. This is followed by a short-term decision maker that utilizes the velocity optimizer and long-term solution, and solves the energy management problem over a relatively short time horizon using robust prediction control methods to factor in any uncertainty in the velocity profile due to uncertain traffic. We solve the long-term energy management problem using pseudospectral optimal control method, and the short-term problem using robust tube-based model predictive control(MPC) method. Simulation results show the competence of our proposed approach, where our proposed co-optimization approach with long- and short-term solution results in ≈ 12% more energy efficiency than a baseline co-optimization approach.

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