Experimental demonstration of smart charging and vehicle-to-home technologies for plugin electric vehicles coordinated with home energy management systems for automated demand response.
In this paper, we consider smart charging and vehicle-to-home (V2H) technologies for plugin electric vehicles coordinated with home energy management systems (HEMS) for automated demand response. In this system, plugin electric vehicles automatically react to demand response events with or without HEMS's coordination, while vehicles are charged and discharged (i.e., V2H) in appropriate time slots by taking into account demand response events, time-ofuse rate information, and users' vehicle usage plan. We introduce three approaches on home energy management: centralized energy control, distributed energy control, and coordinated energy control. We implemented smart charging and V2H systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0, and SAE standards and the other using OpenADR 2.0b, ECHONET Lite, and ISO/EC 15118. We show that the both communication protocol sets enable the same energy management by adding some properties and class into ECHONET Lite that are equivalent to existing function sets in SEP 2.0 such as demand response, pricing, energy flow reservation. We evaluated developed systems in a demonstration platform, called the Energy Management System (EMS) Shinjuku Demonstration Center established by Waseda University upon the initiative by the Ministry of Economy, Trade and Industry (METI) in Japan. We show that developed systems enable automated demand response and peak shift by automatically reacting to demand response events without users' inconvenience. We also show that smart charging and V2H system with HEMS's coordination provides more peak demand reduction than one without HEMS's coordination and one without V2H capability.
CITATION: Shimizu, T., Ono, T., Hirohashi, W., Kumita, K. et al., "Experimental Demonstration of Smart Charging and Vehicle-to-Home Technologies for Plugin Electric Vehicles Coordinated with Home Energy Management Systems for Automated Demand Response," SAE Int. J. Passeng. Cars--Electron. Electr. Syst. 9(2):2016.
Smart grid concept has drawn much attention as it significantly improves the energy efficiency, reliability, security, and cost of electricity grids, by using two-way digital communication and distributed computing technologies for remote and automated control. Smart grid technologies enable demand-side management  such as demand response (DR), which is considered as a promising technology to efficiently reduce the peak of power electricity demand. DR is a mechanism to realize that objective by encouraging consumers to reduce their power consumption or shift the demand from peak to off-peak hours (i.e., peak demand cut/shift) in response to DR events called by utility companies or DR aggregators. DR events comprise price-based programs (e.g., critical peak pricing and dynamic pricing) and incentive-based programs (e.g., peak time rebate and direct load control). DR is cost effective because utility companies can save the cost of building additional power generation to meet peak power demand, and also consumers can save the electricity cost and/or receive payments for peak demand cut and shift. DR events can be categorized into two types: price-based DR events and incentive-based DR events. In price-based DR events, a utility offers customers a time-varying tariff based on wholesale electricity costs. This type of events includes time-of-use (TOU) pricing, critical peak pricing (CPP), and real time pricing (RTP). In incentive-based programs, a utility pays incentives to consumers if the consumers reduce their power consumption as per the utility's requests. This type of events includes load control (LC) and peak time rebate (PTR).
Automated demand response (ADR) is a key component of smart grids, which realizes DR in an automated manner by using two-way digital communication between utilities and consumers' equipment (see Figure 1). In ADR concept, consumers' devices automatically react to DR events and reduce or shift the power consumption by using smart home appliances  and/or relying on home automation systems such as home energy management systems (HEMS) . HEMS technologies play an important role in smart grids and ADR to optimize the energy use of home appliances in smart homes by utilizing standardized two-way communication in home area networks (HAN). HEMS provide three main capabilities (or some of them): 1) visualizing how much energy is consumed in a home, 2) controlling home appliances automatically or manually based on users' preferences, and 3) controlling home appliances based on pricing information and/or DR events, provided by utility servers and/or demand response automation servers (DRAS), for reducing the energy cost and reducing peak demand with the least impact on users' lifestyle.
Plug-in electric vehicles (PEV) are gaining in popularity because of their fuel efficiency and economic benefit and also because they reduce the dependency on fossil fuel, greenhouse gas emission, and air pollution, which make a society more environmental and sustainable. However, increasing market penetration of PEV will lead to a considerable increase of peak demand  and thus require more electricity generation and transmission capacity, which results in additional costs for utilities and consumers. Therefore, it is crucial to consider solutions for reducing the increased peak demand. A favorable aspect of PEV for ADR is that PEV can be considered as flexible loads, i.e., loads that users can reduce charging power and defer charging start time when the grid is stressed. Therefore, we can optimize charging schedules so that we can reduce peak demand and take into account DR events without impairing users' convenience . In addition, PEV has the capability to provide its energy to home loads (V2H: vehicle-to-home) and/or to grids (V2G: vehicle-to-grid) [6, 7]. Particularly, V2H is useful for customers by using PEV as an emergency backup power when power outage occurs and also it is beneficial for peak shift by charging PEV in off-peak periods and discharging it in peak periods. One of the challenges in V2H is that PEV needs to coordinate with HEMS in order to optimize the schedules of PEV's charging and V2H.
For ADR, home energy management, and smart PEV charging/discharging, various standard communication protocols have been developed. For sending DR signals, OpenADR  is often used as an application layer protocol between DRAS and the home. SEP 2.0  and ECHONET Lite  are application layer protocols for use in smart home energy management. SAE J2836/J2847/J2931  and ISO/EEC 15118  are suites of standards of two-way digital communication between PEV and electric vehicle supply equipment (EVSE) for smart charging and discharging control.
In this paper, we consider systems for smart PEV charging and V2H, coordinated with HEMS for ADR. In this system, PEV automatically react to demand response events with or without HEMS's coordination, while vehicles are charged and discharged (i.e., V2H) in appropriate time slots by taking into account DR events, time-ofuse rate information, and users' vehicle usage plan. For realizing different levels of HEMS's coordination, we introduce three approaches on home energy management: centralized energy control, distributed energy control, and coordinated energy control. Also, we implemented smart charging and V2H systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0, and SAE standards and the other using OpenADR 2.0b, ECHONET Lite, and ISO/IEC 15118. We evaluate developed systems in a demonstration platform, called the Energy Management System (EMS) Shinjuku Demonstration Center established by Waseda University upon the initiative by the Mnistry of Economy, Trade and Industry (METI) in Japan. Through demonstration experiments, we show the feasibility of smart PEV charging and V2H for ADR by employing standard communication protocols.
HOME ENERGY MANAGEMENT APPROACHES FOR AUTOMATED DEMAND RESPONSE
In this section, we introduce three approaches of home energy management for ADR, depending on who and how to manage and control home appliances, as shown in Figure 2: 1) centralized energy control, 2) distributed energy control, and 3) coordinated energy control.
Home appliances can be divided into two categories from energy management perspective:
* Passive home appliances: appliances that can be passively controlled by HEMS (e.g., TV displays, heating ventilation, air conditioners, thermostats, lights)
* Active home appliances: appliances that have inherently some intelligence on energy management for ADR by themselves (PEV, home battery storage, heat pumps)
Centralized Energy Control
In the centralized energy control approach, HEMS receives DR signals from DRAS and controls home appliances based on the received DR signals in a centralized manner. This approach is suitable for a specific type of home appliances that can be controlled by simply setting operation parameters (e.g., ON/OFF state, temperature, and illumination level) such as TV displays, air conditioners, thermostats, and lights. This approach allows us to efficiently control multiple home appliances because of its centralized architecture, by aggregating the power consumption of each home appliance and taking into account user's preferences and prioritization for home appliances. However, this approach has some limitations on control of home appliances when we use a standardized communication protocol for controlling multi-vendor appliances. Since HEMS is able to use only limited types of messages defined by a standardized communication protocol, the functionality of HEMS for controlling passive alliances is also limited.
Distributed Energy Control
In the distributed energy control approach, home appliances receive DR signals from DRAS via HEMS or home gateways (HGW) and control their operation by themselves based on the received DR signals in a distributed manner. This approach is suitable for home appliances storing energy (e.g., PEV, home battery storage, and heat pumps) that inherently have some intelligence for energy management. The major advantage of this approach is that it is easy to deploy the system because we can easily add on additional smart home appliances into existing home energy management systems due to its distributed architecture. Another advantage is that since active home appliances control themselves, this approach does not necessarily require HEMS and thus this approach is cost effective.
However, in this approach, it is difficult to optimize the whole house energy use and energy management schedules due to the lack of coordination among active and passive home appliances.
Coordinated Energy Control
The coordinated energy control approach is a combination of centralized energy control and distributed energy control by utilizing coordination between HEMS and active home appliances. In this approach, HEMS, passive home appliances, and active home appliances coexist. The major advantage is that we can optimize the whole house energy usage for both passive and active home appliances by virtue of the coordination between HEMS, passive appliances, and active appliances. One of the technical challenges is that since both HEMS and active home appliances have intelligence for energy management, they need to coordinate with each other to avoid the conflict of energy management. In the following sections, we propose a solution to realize the coordination between HEMS and active home appliances and thus avoid energy management conflict.
We propose one-way energy scheduling for the coordination between HEMS and active home appliances. Here is an example:
1. HEMS allocates available energy resources (e.g., maximum available power and/or energy) for each time slot to each active home appliance (e.g. by imposing direct load control events defined in SEP 2.0)
2. Active appliances determine energy management schedules for themselves based on the allocated energy resources and users' preferences for their operation and ADR
3. Active appliances send the determined schedule information to HEMS (e.g., by using the Flow Reservation Function Set defined in SEP 2.0)
4. HEMS determines energy management schedules for passive home appliances based on the energy management schedule of active appliances and user's preference for their operation and ADR
5. Based on the determined schedules, active home appliances control themselves and HEMS control passive home appliances
Communication Protocols for Home Energy Management
In this section, we consider two communication protocols for smart home management from the viewpoint of the three energy control approaches stated above. In our experiments, we used SEP 2.0  and ECHONET Lite  as application layer protocols for use in smart home energy management. Table 1 shows the comparison of SEP 2.0 and ECHONET Lite. In SEP 2.0, each device manages its own energy control based on DR signals. Also, HEMS can control devices by sending a control event that includes the start time, duration, and control information. In addition, SEP 2.0 supports Flow Reservation Function Set, which enables information exchange of energy management schedules between devices. Therefore, SEP2.0 is suitable for realizing the three energy control approaches. In ECHONET Lite, HEMS manages each device by aggregating the status of every device and controlling each device in a real-time manner based on their status and DR signals. Therefore, it is suitable for the centralized energy control. However, ECHONET Lite does not support some functions defined in SEP 2.0 such as Pricing Function Set and Direct Load Control. Due to this fact, it limits the realization of the distributed energy control. Also, if we want to implement the coordinated energy control approach, some additional functions such as Flow Reservation Function Set in SEP 2.0 is required for coordination between HEMS and active home appliance to avoid the conflict of energy management. In order to realize the distributed energy control and coordinated energy control using ECHONET Lite, we add some classes and properties to ECHONET Lite as explained in the later section.
SMART CHARGING SYSTEMS USING OPENADR 2.0, SEP 2.0, AND SAE STANDARDS
Figure 3 shows the system architecture of smart charging systems that we implemented. In this system, DRAS sends tariff information, i.e. electricity price information, and DR events to HEMS. HEMS forwards that information to the vehicle via EVSE. The cloud server gathers the vehicle information and DR information via HGW, in which the vehicle information includes the vehicle ID, the current state of charge (SoC) of the battery, the battery capacity, and the charging rate. Then, the cloud server calculates the charging schedule based on the vehicle and DR information. The charging schedule is sent to the vehicle and the vehicle is charged according to this schedule. Note that although the cloud server manages the charging schedule of the vehicle in this system, it is also technically possible that the vehicle has the capability of the cloud server. Using a mobile app of a tablet computer, the user can check the charging schedule and the charging status and also set the charging preference (i.e., charging completion time and the amount of energy to be charged). We retrofitted a Prius Plug-in Hybrid vehicle (PHV) with 4.4 kWh batteries and EVSE so that they can communicate with each other by using power line communications over the AC charging cable. In charging PHV, the nominal voltage is 200 V and the nominal current is 10 A.
We implemented the system by using some standardized communication protocols, including OpenADR 2.0b  between DRAS and HEMS, SEP 2.0  between HEMS and HGW, SAE standards (J2931/4  and J2847/1 ) between EVSE and PHV. SAE J2931/4 adopts HomePlug GreenPHY (HP-GP)  for the communication of the physical layer between PHV and EVSE over the control pilot (CPLT) of the AC charging cable. Also, SAE J2847/1 adopts SAE2.0 for the application layer protocol, which is designed for smart grid applications and thus it supports various types of DR events and pricing structures. By using SAE J2931/4 and J2847/1, PHV and EVSE can exchange the information of DR events and pricing information provided by DRAS.
Energy Management Policies
In this system, we assume that DR events are direct control events. For that purpose, we use SIMPLE events defined in OpenADR 2.0b, which are converted by HGW to End Device Control events, defined in the DRLC function set of SEP 2.0. With the mobile app, the user can set the DR preference from two modes:
* DR priority mode:
The charging power is reduced during DR events to comply with the DR events.
* Charging priority mode:
The vehicle can be charged even in DR events.
Based on the selected preference, the cloud server calculates the optimal charging schedule that minimizes the charging cost by following energy management policies.
The energy management policy in the DR priority mode:
1. Comply with DR events if the user selects the DR priority mode
2. Under 1), satisfy the target SoC by the departure time set by the user
3. Under 1) and 2), select the cheapest time slots for charging
4. Under 1)-3), select earlier time slots for charging as long as the charging cost is the cheapest
The energy management policy in the charging priority mode:
1. Satisfy the target SoC by the departure time set by the user
2. Under 1), select the cheapest time slots for charging
3. Under 1) and 2), select earlier time slots for charging as long as the charging cost is the cheapest
SMART CHARGING AND VEHICLE-TO-HOME SYSTEMS USING OPENADR 2.0, ECHONET LITE, AND ISO/IEC 1511815118
Figure 4 shows the system architecture of smart charging and V2H systems that we implemented. In this system, the functionality of each equipment is almost the same as the previous system. The differences from the previous system are two things. One is that we retrofitted a Prius Plug-in Hybrid vehicle and EVSE so that they can support a V2H capability (the maximum discharging power of 1kW). The other is that the cloud server calculates the schedule of charging and V2H based on the information of the vehicle and DR events.
We implemented the system by using some standardized communication protocols, including OpenADR 2.0b between DRAS and HEMS, ECHONET Lite (Release D)  between HEMS and EVSE, ISO/EC 15118  between EVSE and PHV. ISO/EC 15118 is designed for smart grid applications and thus it supports some DR messages and pricing messages. Also, ISO/EC 15118 adopts HP-GP over CPLT for the communication of the physical layer between EVSE and PHV. By using ISO/EC 15118, PHV and EVSE can exchange the information of DR events and pricing information provided by DRAS. Figure 5 shows pictures of the developed equipment.
We found out that ECHONET Lite lacks some message sets required to realize distribution energy control and coordinated energy control such as charging/discharging schedule notification, direct load control, price information. Therefore, we added and extended some properties and class into ECHONET Lite as shown in Table 2 by reference to corresponding function sets already defined in SEP 2.0.
Energy Management Policies
In this system, we assume that DR events are CPP, PTR, and LC events, defined in the DR object of ECHONET Lite. With the mobile app, the user can set the DR preference from three modes:
* DR priority (with V2H) mode:
The vehicle performs V2H as much as possible during DR events. If V2H is not possible due to the lack of battery, charging and V2H are not performed in the DR events.
* DR priority (without V2H) mode:
The charging power is reduced during DR events to comply with the DR events.
* Charging priority mode:
The vehicle can be charged even in DR events.
Based on the selected preference, the cloud server calculates the optimal schedule of charging and V2H that minimizes the charging cost by following energy management policies.
The energy management policy in the DR priority (with V2H) mode:
1. Comply with DR events if the user selects the DR priority mode
2. Under 1), satisfy the target SoC by the departure time set by the user
3. Under 1) and 2), perform V2H during the DR events as much as possible
4. Under 1)-3), select the cheapest time slots for charging
5. Under l)-4), select earlier time slots for charging as long as the charging cost is the cheapest
The energy management policies of the DR priority (without V2H) mode and the charging priority mode are the same as the previous system.
EXPERIMENTAL PLATFORM AND RESULTS
We evaluated developed systems in a demonstration platform, called the Energy Management System (EMS) Shinjuku Demonstration Center. This platform was established by Waseda University in November 2012, upon the initiative of the Ministry of Economy, Trade and Industry (METI) in Japan, for the purpose of establishing DR technology frameworks using standardized communication protocols and facilitating the industrialization of ADR technologies in Japan. 26 industry-wide companies joined this project, including utility companies, telecommunication operators, housing manufactures, home appliance manufactures, and automotive companies, for testing and evaluating ADR technologies and verifying interoperability among different manufactures' equipment.
The system model of the EMS Shinjuku Demonstration Center is depicted in Figure 6. This system consists of a power distribution control simulator (ANSWER: Active Network Systems With Energy Resources), DRAS, smart meters, HEMS, and smart home appliances. This system supports standardized communication protocols, including OpenADR 2.0b, SEP 2.0, and ECHONET Lite. More specifically, DRAS communicates with smart meters and HEMS with OpenADR 2.0b for sending DR events and HEMS communicate with smart home appliances communicate using SEP 2.0 or ECHONET Lite for sending DR events and control signals.
Demand Response Events and Test Cases
In this experiment, we assumed 4 types of DR events: TOU pricing, CPP, PTR, and LC. Also, by considering some combinations of the timing of DR events and the number of events per day, we tested total 6 DR events as shown in Table 3.
In the systems, we employ multiple communication protocols for exchanging DR events and thus we need to define how to convert a DR event information from a communication protocol to another protocol. Table 4 shows the mapping of DR event information between OpenADR 2.0b, SEP2.0, and ECHONET Lite. Due to lack of a class in ECHONET Lite corresponding to Pricing Function Set in SEP2.0 used for TOU event information, we added and implemented Electricity Price Class into ECHONET Lite solely for this experiment. This class allows us to convert TOU event messages from OpenADR 2.0b to ECHONET Lite.
The lists of test cases for our evaluation are shown in Table 5. We evaluated the developed systems for various test cases by considering various combinations of communication protocols (SEP 2.0 or ECHONET Lite), types of energy control (distributed control or coordinated control), DR events, users' preferences for DR events, and user's behavior on PEV charging (the time when PHV is plugged-in and the expected time when charging is completed).
Figure 7 shows experimental results of smart charging systems using OpenADR 2.0b, SEP 2.0, and SAE standards. Due to space limitation, we only show the results of the test cases SEP-A4 and SEP B-4. In this figure, we show the total power consumption (Total), the power generated by the photovoltaic (PV), the powers consumed by the air conditioner (A/C), the heat pump water heater (H/P), and PHV, respectively. From the figure, we can see that PHV complied with the DR events and thus the charging power was successfully reduced in an automated manner during the DR events. Also, PHV was charged during the cheapest TOU periods and charging was completed by the expected charging completion time.
Figure 8 shows experimental results of smart charging systems using OpenADR 2.0b, ECHONET Lite, and ISO/TEC 15118. Due to space limitation, we only show the results of the test cases EL-A4 and EL B-3. In this figure, the power consumed by PHV for charging and the power discharged by PHV for V2H are shown as PHV and V2H, respectively. In Figure 8 (a), charging was successfully stopped in an automated manner during the CPP events as in Figure 7 (a). Therefore, we confirmed that the system based on ECHONET Lite and ISO/IEC 15118 can successfully perform ADR as the system based on SEP 2.0 and SAE standards can do in Figure 7. In Figure 8 (b). V2H was performed during the TOU peak period, while PHV was charged during the TOU off-peak periods and charging was completed by the expected charging completion time. In the TOU peak period, we can see that the total power consumption was significantly reduced by virtue of V2H and thus successful peak shift was achieved.
In this paper, we proposed smart PEV charging and V2H systems coordinated with HEMS that are able to support different levels of HEMS coordination and react to DR events in an automated manner. We implemented the proposed systems by employing two sets of standardized communication protocols: one using OpenADR 2.0b, SEP 2.0 and SAE standards and the other using OpenADR 2.0b, ECHONET Lite and ISO/IEC 15118. We demonstrated the feasibility of the proposed systems through experiments in the EMS Shinjuku Demonstration Center and showed that the developed systems enable ADR and peak shift by automatically reacting to DR events.
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The authors would like to thank the partner companies: DENSO Corporation, Sumitomo Electric Industries, Ltd., Sumitomo Electric Networks Inc., Autonetworks Technologies, Ltd., and Toyota Industries Corporation, for their generous support.
A/C - Air Conditioner
ADR - Automated Demand Response
DR - Demand Response
DRLC - Demand Response and Load Control
DRAS - Demand Response Automation Server
CPP - Critical Peak Pricing
EMS - Energy Management System
EVSE - Electric Vehicle Supply Equipment
HEMS - Home Energy Management System
HGW - Home Gateway
H/P - Heat Pump
HP-GP - HomePlug GreenPHY
LC - Load Control
PEV - Plug-in Electric Vehicle
PHV - Plug-in Hybrid Vehicle
PTR - Peak Time Rebate
PV - Photovoltaic
SoC - State of Charge
TOU - Time-of-Use
V2G - Vehicle-to-Grid
V2H - Vehicle-to-Home
Toyota Info Technology Center USA
Toyota Motor Corporation
Toyota Motor Corporation
Table 1. Comparison of SEP 2.0 and ECHONET Lite. Item SEP 2.0 ECHONET Lite Concept Each device manages its own HEMS controls devices by energy management by using using device objects multiple function sets defined for each device type Control Control by events (time, Realtime control command) (command) OSI Layers Layers 5-7 Command GET, PUT, POST, DELETE GET, SET, ANNOUNCE Format Binary XML/EXI Organization ZigBee Alliance, ECHONET Consortium HomePlug Alliance Recommendation Adopted by NIST in USA for Recommended by METI in smart grid applications Japan for smart home applications Table 2. The added and extended classes in ECHONET Lite and corresponding function set in SEP 2.0. Function Added/Extended Corresponding Class in ECHONET Function Set in Life SEP 2.0 Charging/Discharging Energy Schedule Energy Flow Reservation Schedule Notification Property in Electric Function Set Vehicle Charger /Discharger Class Direct Load Control Energy Limit Set DRLC Function Set Property in Electric Vehicle Charger /Discharger Class Price Information Electricity Price Pricing Function Set Class Table 4. The mapping of DR event information between different protocols. DR Event OpenADR2.0b SEP 2.0 TOU ELECTRICITY_PRICE Pricing Function Set (marketContext: TOU) CPP ELECTRICITY_PRICE Pricing Function Set (marketContext: CPP) PTR ELECTRICITY_PRICE N/A (marketContext: PTR) LC SIMPLE DRLC Function Set (marketContext: LC) DR Event ECHONET Life TOU Electricity Price Class (added for the experiment) CPP CPP in DR Object PTR PTR in DR Object LC LC in DR Object Table 5. The list of test cases. a. Test cases for SEP 2.0-based distributed energy control system Exam ID DR Events OpenADR2.0b Signal SEP2.0 Signal DR Preference SEP-A1 TOU TOU(Peak Shift) Price DR SEP-A2 TOU TOU(Peak Shift) Price DR SEP-A3 CPP-1 TOU(Flat) + CPP Price DR SEP-A4 CPP-1 TOU(Flat) + CPP Price DR SEP-A5 CPP-2 TOU(Flat) + CPP Price DR SEP-A6 CPP-2 TOU(Flat) + CPP Price Charging SEP-A7 LC TOU(Peak Shift) + Price + DRLC DR Simple (Level 1) (Offset: 50) SEP-A8 LC TOU(Peak Shift) + Pnce + DRLC DR Simple (Level 2) (Offset 100) Exam ID Time of PHV Expected Charging Cable Connected Completion Time SEP-A1 10:00 19:00 SEP-A2 12:00 19:00 SEP-A3 10:00 19:00 SEP-A4 12:00 19:00 SEP-A5 10:00 19:00 SEP-A6 10:00 13:00 SEP-A7 10:00 19:00 SEP-A8 10:00 19:00 b. Test cases for SEP 2.0-based coordinated energy control system Exam ID DR OpenADR2.0b SEP2.0 Signal DR Events Signal Preference SEP-B1 TOU TOU (Peak Price DR Shift) SEP-B2 TOU TOU (Peak Price DR Shift) SEP-B3 CPP-1 TOU (Flat) + Price DR CPP SEP-B4 CPP-1 TOU (Flat) + Price + DRLC DR GPP (12:00-14:00) SEP-B5 CPP-2 TOU (Flat) + Price DR GPP SEP-B6 LC TOU (Peak Price + DELC DR Shift) + Simple-Level Exam ID Time of PHV Expected Charging Cable Connected Completion Time SEP-B1 10:00 19:00 SEP-B2 12:00 19:00 SEP-B3 10:00 19:00 SEP-B4 11:00 19:00 SEP-B5 10:00 19:00 SEP-B6 10:00 17:00 c. Test cases for ECHONET-Lite-based distributed energy control system Exam ID DR Event OpenADR2.0b ECHONET Lite DR Preference Signal Signal EL-A1 TOU TOU(Peak Shift) Price DR (w/o V2H) EL-A2 TOU TOU(Peak Price DR (w/o V2H) Shift) EL-A3 CPP-1 TOU(Flat) + Price + DR-CPP DR (w/o V2H) CPP EL-A4 CPP-1 TOU(Flat) + Price + DR-CPP DR (w/o V2H) CPP EL-A5 CPP-2 TOU(Flat) + Price + DR-CPP DR (w/o V2H) CPP EL-A6 CPP-2 TOU(Flat) + Price + DR-CPP Charging CPP EL-A7 PTR-l TOU(Peak Price + DR-PTR Charging Shift) + PTR EL-A8 PTR-2 TOU(Peak Price + DR-PTR DR (w/o V2H) Shift) + PTR EL-A9 LC TOU(Peak Price + DR-LC DR (w/o V2H) Shift) + Simple-Level Exam ID Time of PHV Expected Charging Cable Connected Completion Time EL-A1 10:00 19:00 EL-A2 12:00 19:00 EL-A3 10:00 19:00 EL-A4 12:00 19:00 EL-A5 10:00 19:00 EL-A6 10:00 13:00 EL-A7 12:00 13:00 EL-A8 10:00 13:00 EL-A9 10:00 19:00 d. Test cases for ECHONET-Lite-based coordinated energy control system Exam ID DR Event OpenADR2.0b ECHONET Lite Signal DR Preference Signal EL-B1 TOU TOU(Peak Price DR (w/o Shift) V2H) EL-B2 TOU TOU(Peak Price DR (w/o Shift) V2H) EL-B3 TOU TOU(Peak Price DR (w/o Shift) V2H) EL-B4 CPP-1 TOU(Flat) + Price + DR-CPP DR (w/o CPP V2H) EL-B5 CPP-1 TOU(Flat) + Price + DR-CPP Charging CPP + DLC (12:00-14:00) EL-B6 CPP-2 TOU(Flat) + Price + DR-CPP DR (w/o CPP V2H) EL-B7 CPP-2 TOU(Flat) + Price + DR-CPP DR (w/o CPP + DLC (12:00-14:00) V2H) EL-B8 PTR-1 TOU(Peak Price + DR-PTR Charging Shift) + PTR EL-B9 PTR-2 TOU(Peak Price + DR-CPP DR (w/o Shift) + PTR + DLC (12:00-16:00) V2H) EL-B10 PTR-2 TOU(Peak Price + DR-CPP DR (w/o Shift) + PTR + DLC (12:00-15:00) V2H) EL-B11 LC TOU(Peak Price + DR-LC DR (w/o Shift) + V2H) Simple-Level EL-B12 LC TOU(Peak Price + DR-LC DR (w/o Shift) + V2H) Simple-Level Exam ID Time of PHV Expected Charging Cable Connected Completion Time EL-B1 10:00 19:00 EL-B2 12:00 19:00 EL-B3 12:00 19:00 EL-B4 10:00 19:00 EL-B5 11:00 19:00 EL-B6 10:00 19:00 EL-B7 10:00 19:00 EL-B8 12:00 13:00 EL-B9 10:00 17:00 EL-B10 10:00 17:00 EL-B11 10:00 17:00 EL-B12 10:00 17:00
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|Author:||Shimizu, Takayuki; Ono, Tomoya; Hirohashi, Wataru; Kumita, Kunihiko; Hayashi, Yasuhiro|
|Publication:||SAE International Journal of Passenger Cars - Electronic and Electrical Systems|
|Date:||Aug 1, 2016|
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