Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR

Erdinç, Ozan; Paterakis, Nikolaos G.; Mendes, Tiago D. P.; Bakirtzis, Anastasios G.; Catalào, João P. S.

doi:10.1109/tsg.2014.2352650

Cited by 414 publications

(237 citation statements)

References 23 publications

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“…Monte Carlo techniques were used to define the charging demand and charging scenarios, which revealed voltage profiles reduction during peak demand charging and should be controlled for the condition of balanced and unbalanced loads [10][11][12]. Consequently, the PEVs can reduce the impact from charging mode at the same time or in the same power transmission line by using V2G technology and in combination with smart grid control [1,[13][14][15][16][17]. The smart grid control concept is needed to manage all the relevant areas in optimal condition such as power sources, transmission system, distribution system, user benefits, and economics [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis

Kongjeen

Bhumkittipich

2018

Energies

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This paper proposes the impact of plug-in electric vehicles (PEVs) integrated into a power distribution system based on voltage-dependent control. The gasolinegate situation has many people turning to electric vehicles as a more environmentally friendly option, especially in smart community areas. The advantage of PEVs is modern vehicles that can use several types of fuel cells and batteries as energy sources. The proposed PEVs model was developed as a static load model in power distribution systems under balanced load conditions. The power flow analysis was determined by using certain parameters of the proposed electrical network. The main research objective was to determine the voltage magnitude profiles, the load voltage deviation, and total power losses of the electrical power system by using the new proposed methodology. Furthermore, it investigated the effects of the constant power load, the constant current load, the constant impedance load, and the plug-in electric vehicles load model. The IEEE 33 bus system was selected as the test system. The proposed methodology assigned the balanced load types in a steady state condition and used the new methodology to solve the power flow problem. The simulation results showed that increasing the plug-in electric vehicles load had an impact on the grids when compared with the other four load types. The lowest increased value for the plug-in electric vehicles load had an effect on the load voltage deviation (0.062), the total active power loss (120 kW) and the total reactive power loss (80 kVar), respectively. Therefore, this study verified that the load of PEVs can affect the electrical power system according to the time charging and charger position. Therefore, future work could examine the difference caused when PEVs are attached to the electrical power system by means of the conventional or complex load type.

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Section: Introductionmentioning

confidence: 99%

Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis

Kongjeen

Bhumkittipich

2018

Energies

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“…However, the domestic sector has shown less interest in SG technologies, because of their individually smaller impact on the grid and the technical difficulties in aggregating large numbers of customers [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…Since domestic buildings are a very significant share of total buildings, households are responsible for a large proportion of CO 2 emissions, through end use of both electricity and gas (or other fossil fuel) [4]. It is therefore urgent to develop cost-effective and practical methods to control energy consumption in residential dwellings.…”

Section: Introductionmentioning

confidence: 99%

“…In most work on building level Energy Hub optimisation, instead of attempting to predict load, it is assumed systems have perfect forecasts and so know energy demand in advance [2,4]. However, load prediction at building and micro-grid level can require long computation times and often performs poorly (an average error of 4.8% is given in [24] based on a number studies including [25][26][27]).…”

Section: Introductionmentioning

confidence: 99%

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Rule Based Coordinated Control of Domestic Combined Micro-CHP and Energy Storage System for Optimal Daily Cost

et al. 2017

Applied Sciences

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This paper presents a novel control algorithm for optimising operational costs of a combined domestic micro-CHP (combined heat and power), battery and heat storage system. Using a minute by minute basic time-step, this work proposes a simple and computationally efficient rule based whole-system management, developed from empirical study of realistic simulated domestic electricity and heat loads. The CHP availability is considered in two binary states which, together with leveraging storage effectively, maximises CHP efficiency, and gives the algorithm increased real world feasibility. In addition, a novel application of a dual battery system is proposed to support the micro-CHP with each battery supplying just one of the distinctive morning and evening electrical load peaks, and thus inherently improving overall battery system lifetime. A case study is presented where the algorithm is shown to yield approximately 23% energy cost savings above the base case, almost 3% higher savings than that of the closest previous work, and 96.8% of the theoretical minimum cost. In general, the algorithm is shown to always yield better than 88% of the theoretical minimum cost, a ratio that will be considerably higher when real-world CHP limitations are factored into the theoretical minimum calculation.

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“…Many studies have examined ESSs to utilize renewable integration, peak shaving, ancillary services, and microgrids [1][2][3][4][5][6][7][8][9][10]. In [11], the authors presented the feasibility of an ESS for the operation of an island AC microgrid with photovoltaic generation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Yang

Choi

et al. 2016

Energies

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An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery.

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Smart Household Operation Considering Bi-Directional EV and ESS Utilization by Real-Time Pricing-Based DR

Cited by 414 publications

References 23 publications

Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis

Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis

Rule Based Coordinated Control of Domestic Combined Micro-CHP and Energy Storage System for Optimal Daily Cost

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

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