Electric Energy Management for Plug-in Electric Vehicles Charging in the Distribution System by a dual cascade scheduling algorithm

This paper presents an algorithm for plug-in electric vehicles (PEVs) charging in the three-phase distribution system for residential houses. It aims to prevent violent voltage level deviation and increasing losses on the three-phase distribution system due to uncontrolled charging and allocate power to each plug-in electric vehicle. The algorithm is comprised of two processes. The first process is power limitation and limited power of load imbalance by if-else rules, while the second process is power allocation to each PEV by the dual cascade scheduling algorithm which is the integration of tasking scheduling algorithms. A 100 kVA distribution transformer and 30 houses are defined in the simulation situation. Also, the available PEVs in single-phase, two-phase, and three-phase systems are assigned for verification of the proposed algorithm. Root-mean-square deviation (RMSD) referred to the satisfaction of PEV owners, total PEVs charged energy, and the average percentage of achieved charging time, as the result indicators. The results show the proposed algorithm can provide good results without rejected PEVs charging. Furthermore, this paper also displays the analysis of voltage level, percentage of voltage unbalance factor, and loss in the distribution system. In the future, coordination with home appliances to gain a high load margin or electric energy cost control will be improved in the proposed algorith

Integrated framework for modeling the interactions of plug-in hybrid electric vehicles aggregators, parking lots and distributed generation facilities in electricity markets

This paper presents an integrated framework for the optimal resilient scheduling of an active distribution system in the day-ahead and real-time markets considering aggregators, parking lots, distributed energy resources, and Plug-in Hybrid Electric Vehicles (PHEVs) interactions. The main contribution of this paper is that the impacts of traffic patterns on the available dispatchable active power of PHEVs in day-ahead and real-time markets are explored. A two stage framework is considered. Each stage consists of a four-level optimization procedure that optimizes the scheduling problems of PHEVs, parking lots and distributed energy resources, aggregators, and active distribution system. The distribution system procures ramp-up and ramp-down services for the upward electricity market in a real-time horizon. The active distribution system can utilize a switching procedure to sectionalize its system into a multi-microgrid system to mitigate the impacts of external shocks. The model was assessed by the 123-bus test system. The proposed algorithm reduced the interruption and operating costs of the 123-bus test system by about 94.56% for the worst-case external shock. Further, the traffic pattern decreased the available ramp-up and ramp-down of parking lots by about 58.61% concerning the no-traffic case.© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

Coordination of EVs Participation for Load Frequency Control in Isolated Microgrids

Increasing the penetration levels of renewable energy sources (RESs) in microgrids (MGs) may lead to frequency instability issues due to intermittent nature of RESs and low inertia of MG generating units. On the other hand, presence of electric vehicles (EVs), as new high-electricity- consuming appliances, can be a good opportunity to contribute in mitigating the frequency deviations and help the system stability. This paper proposes an optimal charging/discharging scheduling of EVs with the goal of improving frequency stability of MG during autonomous operating condition. To this end, an efficient approach is applied to reschedule the generating units considering the EVs owners’ behaviors. An EV power controller (EVPC) is also designed to determine charge and discharge process of EVs based on the forecasted day-ahead load and renewable generation profiles. The performance of the proposed strategy is tested in different operating scenarios and compared to those from non-optimized methodologies. Numerical simulations indicate that the MG performance improves considerably in terms of economy and stability using the proposed strategy

Robust optimization for energy transactions in multi-microgrids under uncertainty

Independent operation of single microgrids (MGs) faces problems such as low self-consumption of local renewable energy, high operation cost and frequent power exchange with the grid. Interconnecting multiple MGs as a multi-microgrid (MMG) is an effective way to improve operational and economic performance. However, ensuring the optimal collaborative operation of a MMG is a challenging problem, especially under disturbances of intermittent renewable energy. In this paper, the economic and collaborative operation of MMGs is formulated as a unit commitment problem to describe the discrete characteristics of energy transaction combinations among MGs. A two-stage adaptive robust optimization based collaborative operation approach for a residential MMG is constructed to derive the scheduling scheme which minimizes the MMG operating cost under the worst realization of uncertain PV output. Transformed by its KKT optimality conditions, the reformulated model is efficiently solved by a column-and-constraint generation (C&CG) method. Case studies verify the effectiveness of the proposed model and evaluate the benefits of energy transactions in MMGs. The results show that the developed MMG operation approach is able to minimize the daily MMG operating cost while mitigating the disturbances of uncertainty in renewable energy sources. Compared to the non-interactive model, the proposed model can not only reduce the MMG operating cost but also mitigate the frequent energy interaction between the MMG and the grid

Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage

This paper presents a two-level optimization model for the optimal scheduling of an active distribution system in day-ahead and real-time market horizons. The distribution system operator transacts energy and ancillary services with the electricity market, plug-in hybrid electric vehicle parking lot aggregators, and demand response aggregators. Further, the active distribution system can utilize a switching procedure for its zonal tie-line switches to mitigate the effects of contingencies. The main contribution of this paper is that the proposed framework simultaneously models the arbitrage strategy of the active distribution system, electric vehicle parking lot aggregators, and demand response aggregators in the day-ahead and real-time markets. This paper's solution methodology is another contribution that utilizes robust and lexicographic ordering optimization methods. At the first stage of the first level, the optimal bidding strategies of plug-in hybrid electric vehicle parking lot aggregators and demand response aggregators are explored. Then, at the second stage of the first level, the day-ahead optimization process finds the optimal scheduling of distributed energy resources and switching of electrical switches. Finally, at the second level, the real-time optimization problem optimizes the scheduling of system resources. Different case studies were carried out to assess the effectiveness of the algorithm. The proposed algorithm increases the system's day-ahead and real-time revenues by about 52.09% and 47.04% concerning the case without the proposed method, respectively.© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed