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Charging scheduling of electric vehicles with local renewable energy under uncertain electric vehicle arrival and grid power price
- IEEE Trans. Veh. Technol
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Exploring Power-Voltage Relationship for Distributed Peak Demand Flattening in Microgrids
"... Due to limited energy storage units in microgrids, how to regulate peak demand is one of the main challenges. Thus, researchers propose di↵erent techniques to flatten peak de-mand in individual residential buildings. However, if each home in the grid flattens peak demand only with its own power cons ..."
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Due to limited energy storage units in microgrids, how to regulate peak demand is one of the main challenges. Thus, researchers propose di↵erent techniques to flatten peak de-mand in individual residential buildings. However, if each home in the grid flattens peak demand only with its own power consumption information, it is possible that peak demand of the microgrid would not be flattened but only shifted to another period. Therefore, it is critical for homes to cooperate with each other to flatten peak demand. In this paper, we utilize the power-voltage relationship in individual homes to enable that each home can infer the information of power consumption in the community by locally moni-toring the voltage value on the common power line. The inferred information is then used for homes to flatten peak demand of the microgrids in a distributed manner. Further-more, we leverage existing thermal appliances (e.g., water heaters) as thermal “batteries ” in individual homes instead of purchasing batteries to flatten peak demand. We eval-uate our system’s performance by conducting experiments and extensive empirical data driven simulations. Evaluation results indicate that our design enables homes to e↵ectively flatten peak demand by more than 29 % without a↵ecting homeowners ’ behaviors.
1Real-Time PEV Charging/Discharging Coordination in Smart Distribution Systems
"... Abstract—This paper proposes a novel online coordination method for the charging of plug-in electric vehicles (PEVs) in smart distribution networks. The goal of the proposed method is to optimally charge the PEVs in order to maximize the PEV owners ’ satisfaction and to minimize system operating cos ..."
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Abstract—This paper proposes a novel online coordination method for the charging of plug-in electric vehicles (PEVs) in smart distribution networks. The goal of the proposed method is to optimally charge the PEVs in order to maximize the PEV owners ’ satisfaction and to minimize system operating costs without violating power system constraints. Unlike the solutions reported in the literature, the proposed charging architecture guarantees the feasibility of the charging decisions by means of a novel prediction unit that can forecast future PEVs power demand and through an innovative two-stage optimization unit that ensures effective charging coordination. Coordinated PEV discharging also enables improved utilization of power system resources. Simulation results for a typical distribution network are provided as a demonstration of the effectiveness of the proposed architecture. Index Terms—Distribution systems, energy management, elec-tric vehicle, smart parking lot, M/G/ ∞ queue. I.
1Heuristic Optimization for the Discrete Virtual Power Plant Dispatch Problem
"... Abstract—We consider a virtual power plant, which is given the task of dispatching a fluctuating power supply to a portfo-lio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the discrete virtual power plant dis ..."
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Abstract—We consider a virtual power plant, which is given the task of dispatching a fluctuating power supply to a portfo-lio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the discrete virtual power plant dispatch problem (DVPPDP). First, the nondeterministic polynomial time (NP)-completeness of the discrete virtual power plant dispatch problem is proved formally. We then proceed to develop tailored versions of the meta-heuristic algorithms hill climber and greedy randomized adaptive search procedure (GRASP). The algorithms are tuned and tested on portfolios of varying sizes. We find that all the tailored algorithms perform satisfactorily in the sense that they are able to find sub-optimal, but usable, solutions to very large problems (on the order of 105 units) at computation times on the scale of just 10 s, which is far beyond the capabilities of the optimal algorithms we have tested. In particular, GRASP sorted shows with the most promising performance, as it is able to find solutions that are both agile (sorted) and well balanced, and consistently yields the best numerical performance among the developed algorithms. Index Terms—Algorithms, computation time, scheduling, suboptimal control.
A NOVEL MODEL FOR SMART GRID AS A NETWORK OF NETWORKS WITH HYBRID COMPOSITE CROSS LAYER DESCRIPTION
"... Original scientific paper This paper is an effort towards constructing a comprehensive model for the smart grid as a network of networks with the ability of evaluating events in presence of every smart grid feature. To this end, the network modelling laws are employed to attain a proper structure fo ..."
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Original scientific paper This paper is an effort towards constructing a comprehensive model for the smart grid as a network of networks with the ability of evaluating events in presence of every smart grid feature. To this end, the network modelling laws are employed to attain a proper structure for the model, the automata theory is used to explain the performance of the proposed model, and the hybrid function theory is utilized to define an appropriate mathematical description for it. By evaluating the smart grid cooperative processes, and determining the role of special smart grid features in these processes, a six-layered hierarchical structure is chosen. Each layer of this structure is considered as an automaton and its autonomous performance is described by a hybrid function, mathematically. The composition of these six hybrid functions introduces the final formulation of the model. To verify the suitability of the proposed
