S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/571
DYNAMIC LOAD MANAGEMENT FOR SMART HOME USING HOME ENERGY MANAGEMENT
ALGORITHM
1S.Rajalingam, 2R.Mahamari
1Assistant Professor, 2 Full Time M.E student
1,2 Department of Electrical and Electronics Engineering, K.L.N. College of Engineering Pottapalayam, sivagangai-Dst, Tamilnadu, India
1[email protected] 2[email protected] ABSTRACT— Generally power system has micro grids and
smart grid operations. Each consumer has different types of loads. The main objective of this paper is to reduce the energy demand and electricity cost. The electricity demand is increasing day by day and leads to increase in generation & transmission.
This is complex and it is reduced by incorporating renewable energy & prioritizing the load as per the wish. This methodology is implemented by considering the two cases such as half peak hour and peak hour. Assuming that the power from renewable energy source is utilized during half peak hour and the power from Electricity Board can be utilized at peak hour. During Peak hours when power from renewable energy is not able to supply, the Automatic power supply selector switches the next source of power (EB). Since power from renewable energy is chosen first, the cost & electricity demand may be reduced. This arrangement can be designed by using PLC (Programming Logic Controller).
A home energy management (HEM) is important by which smart grid and micro grid can manage residential customers. It manages household appliances according to their preset priority due to their power consumption below certain levels. The dynamic resources management methodology allows a better resources management in a demand event, mainly the ones of long duration, by changing the priorities of loads during the event.
Keywords—Smart appliance, Home energy management, Dynamic load priority, customer choice.
I. INTRODUCTION
Electric power systems have more frequent stress conditions due to ever-increasing electricity demand [1]. Transmission line outages have a common cause of system stress conditions, which are likely to occur during critical peak hours. Like that events will cause a supply-limit situation where cascading failures and large-area blackouts are possible. In the new electrical network operation paradigm, consumers will be seen as active resources with the capability to manage their energy consumption, power generation, and power storage
systems. To implement this insight several approaches have been proposed with the main focus on the smart grids and micro grids. To improve the performance of the house management system, it is necessary to include the ability to independent acquire knowledge on the user’s behavior alter the consumer’s priority during the management process, improving the global system performance, and the consumer preference [7]. This features will be very important to control of devices during a demand response event in order to decrease the electricity consumption without changing the comfort levels too much [8]. DR also plays an important role in load shifting that can help increase reliability and efficiency in operation. Many DR programs are widely implemented by commercial and industrial customers. In residential home have three types of DR automation levels are manual DR semi-automated DR and fully automated DR [5].
The fully automated DR is the most popular automation type that can be achieved by a home energy management System. An HEM system is used for monitoring and managing the operation of in home appliances, and providing load shedding and shifting according to a specified set of requirements. Different HEM hardware applications are discussed in [11],[12]. Several papers in the literature discussed on controlling low power consumption appliances, such as coffee makers, refrigerators, lighting, and other plug loads.
This paper presents the development of an HEM algorithm due to managing household power- intensive appliances. These are Air conditioner, water heaters, washing machine and electric Vehicles (EV). They range in size from 2KW for an
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/572 Air conditioner to 3.3–9.6 kW for an EV. The
proposed HEM algorithm is used to control the selected load devices and maintain the total household power consumption below a certain limit, while considering customer priority and allowing the customer more flexibility to operate their load appliances. An HEM system plays an important role in achieving automated Demand Response within a house, as most residential customers do not have time, either proactive enough to perform Demand Response manually. An effective HEM system should provide load shedding and shifting ability whenever required the least impact on customer life style during a Demand Response event.
II. ENERGY MANAGEMENT CONCEPT The increase of energy consumption of electricity and makes the effectiveness counteract actions essentials [12, 13]. To improve the residential sector, it is important to separate consumptions by floor, room, and device to evaluate the device's efficiency, as well as the expected consumption behavior [14, 15]. However, the energy consumption monitoring is important in large time periods in order to quantify the replacement advantages. In the following subsections, the home energy management systems will be discussed in detail, providing more information on intelligent applications, and for the management of demand response events from the house’s point of view.
A. MANAGEMENT OF DEMAND RESPONSE EVENTS IN HOME ENERGY
MANAGEMENT SYSTEMS
Demand response (DR) programs can be an important energy resource in the future power systems. Large consumers like industries are the main focus of the actual DR programs. However, small consumers like the domestic can provide more a flexible response to these events [25]. The management of DR events in the HEM is an important challenge for future HEM, in order to
take advantages from the participation in DR events. The future home energy management systems should be able to manage automatically demand response events, considering the consumer's point of view, regarding the consumption/prices offsets, and the loads priority [26]. Several types of demand response like Time- of-Use (TOU) programs the most popular. TOU is used to minimize the consumption of higher electricity price [27]. The participation in Demand Response programs can be managed by an aggregator entity, for sample by the curtailment service provider (CSP). The CSP can handle the participation in demand response events of more than one consumer, making some possible to the system operators, and providing services to the consumers. In [28] this paper is proposed that communication architecture is composed of different layers, considering a layer to implement the interface between the HEM, and the system operator energy management system. The load management was implemented in another layer using a mixed-integer programming in order to minimize the operation costs considering the demand response opportunities.
B. A DEMAND RESPONSE EVENT
A DR event is defined as a period during which the customer demand needs to be cut to reduce a system stress condition. Customers who participate in a Demand Response program can be defined of a DR event of an external signal from a utility by way their smart meters. For our study, we consider that the external signal received by the HEM system is in a form of a demand curtailment request (KW) and duration (hrs). Fig.2 illustrates the proposed HEM framework.
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/573
Fig.1. Diagram to identify the characteristics of the load in a manageable event.
Fig.2 illustrates the proposed HEM framework.
TABLE I
EXAMPLE OF LOAD PRIORITY AND PREFERENCE SETTINGS IN A HOUSE
Appliance Load Priority
Home owner preference Water heater 1 Water temperature: 110-
120°F Air conditioner 2 Room Temperature:
76°F (±2°F)
Clothes Dryer 3 Finish job by midnight Maximum OFF time:
30minsMinimum ON time: 30mins EV(24v single
phase)
4 Fully charged by 8AM Minimum charge
time:30mins
As the HEM receives the external signal, which includes demand curtailment request and duration, its algorithm is designed for the total household power consumption below the specified demand limit level (KW) during the specified duration (hrs).
This demand limit level can vary every 15 mins or every hour depending on system requirements.
High power consumption appliances to be controlled are Air conditioner, water heater, and Electric vehicle, Clothes dryer. Critical loads are to be served at all time. The proposed HEM algorithm allows the consumer to operate their appliances when needed as long the total household consumption below the specified limit during a DR event. At the same time, it takes into account load priority and customer comfort priority.
C. PROBLEM FORMULATION
The main objective of the optimization algorithm is to the power consumption limits
(PLimit) during the house management system
operation, considering different types of events like comfort levels, and the user’s interaction. All these details are reflected in the resources and loads priority factors (Load). The priority factors change between 0 and 10, factor 10 being used for lowest priority loads, and factor 0 for the higher priority loads. When the loads are not equipped with any uncontrollable or when the users do not want the automatic device control, the corresponding power is included in the parameter PFixed Loads, and any priority is considered. The fixed loads change every optimization process during the Demand Response event. The optimization problem can be formulated and Objective function to determine the load as follows
Load profile
Perm anent
Esse ntia l Non- priori ty
Time On
Time off
ID Load
Varia ble (0) Disc rete (1) Moto
r
Light
HVA C
TV
Was h
Kitch en
Cool er
AC WH EV CD Home Energy Management
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/574
MinF . m in. m in m ax. m ax
11
R R
P
nload
Load
Load
Load
Pr
oblem constrains
Eq (2) intends to determine the connected load
2m in
m ax
nLoad
Load load FixedLoads
Limit p p R R
p
3 .. Load Load LoadMax Load
Min
Load x P P x
P
λmin Regulation minimum priority λmax Regulation maximum priority Load Load index
NLoad Maximum number of loads Maximum load Consumption [W]
Min
pLoad Minimum load Consumption [W]
PFixedload Total Consumption of non-controlled
loads [W]
Plimit Power limit for the total Consumption[w]
Pload Power consumption of load[w]
Rmin Power regulation minimum[w]
Rmax Power regulation maximum[w]
Xload Load binary variable K Priority factor λ Load priority
D. LOAD
PRIORITY BASED CUSTOMER COMFORT PREFERENCE
The first step before the proposed HEM algorithm can operate is for a homeowner to set their load priority and comfort preference. The load priority and preference settings are shown in Table I.As shown in this house; the water heater is of the highest priority. This is followed by the Air conditioner unit, the clothes dryer, and the electric vehicle.
Comfort level settings can be defined for each appliance. For the water heater, the hot water temperature preference can be set, e.g., between 110-120°F.For the Air conditioner unit, the room temperature preference can be specified, e.g., between 74-78°F.For the clothes dryer, a homeowner can specify its complete time,
maximum heating coils are considered OFF time and minimum heating coils are considered ON time. For the EV, a homeowner can specify the EV full charge time.
III. HEM
CONTROL AUCTION BY APPLIANCE TYPE
The defined demand limit is the important factor to determine the status of devices in the algorithm. Any violation in the demand limit will result in turning OFF selected devices according to their priority.
Customer priority settings are allowed to be exceeding from the least important loads to the most important ones to the requested demand limit.
The operation of each device and its associated HEM control algorithm are discussed below.
1. ELECTRIC
WATER HEATER OPERATION:
A heat water temperature set point is specified with a temperature tolerance. When the heat water temperature drop below the minimum required temperature (TWH-Δ TWH), WH heating coils are ON. After the heat water temperature reaches the set point, WH heating coils are OFF. If the hot water temperature is within the preset comfort range, (TWH, S-Δ TWH≤ TWH, N≤ TWH, S) the heating coils will keep their previous status.
Where
TWH, S hot water temperature set point (°F);
Δ TWH temperature tolerance (°F);
TWH, N Hot water temperature in time interval(°F)
Sw,H,N WH Status in time interval (0=OFF;1=ON).
If the demand limit is force on this house and the water heater is ON, the HEM is allowed to turn OFF the water heater as required for the preset load priority. If the water heater has the highest priority, it will be the last one to be turned OFF.
Max
pLoad
0, TWH, N> TWH, S
SWH,N= 1, TWH, N< TWH, S − Δ TWH (1) SW, H, N-1, TWH, S − Δ TWH ≤ TWH, N ≤ TWH, S
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/575 2. AIR CONDITIONER OPERATION:
A room temperature set point is defined with a dead band. When the room temperature violate the maximum allowable temperature (TAC, S+𝜟TAC) the space cooling unit is ON and the room temperature will slowly decrease. When the room temperature is below TAC, S-𝜟TAC, the space cooling unit is OFF. If the room temperature is within the preset comfort range (TAC, S-Δ TAC ≤ TAC, N ≤ TAC, S+ Δ TAC), the space cooling unit will maintain its previous status.
0, TAC, N<TAC, S-Δ TAC
SAC,N= 1, TAC, N>TAC, S+Δ TAC (2) SAC, N-1, TAC, S − Δ TAC≤ TAC, N ≤ TAC, S+ΔTAC
Where
TAC, S room temperature set point (°F);
Δ TAC dead band (°F);
TAC, N room temperature in time interval n (°F);
SAC, N AC Status in time interval n(0=OFF;1=ON)
3. HEM Control Strategy for AC:
If the demand limit is force on this house and the Air conditioner unit is ON, the HEM is allowed to turn OFF the space cooling unit as required due to the preset load priority. If the comfort setting is exceed (i.e., room temperature exceeds the preset level), the air conditioner unit will be forced ON to maintain the room temperature within the comfort range, given that the total household consumption does not violated the limit.
4. CLOTHES DRYER OPERATION:
A clothes dryer have rotating tumbler and heating coils. The power consumption of the motor part is in the range of hundred watts (e.g. 200 watts), while that of the heating coils can be kilowatts (e.g. 3 kW). The clothes dryer will be turned ON as long the accumulated ON time is less than the required ON time to complete a clothes drying operation. When the accumulated ON time reaches the required ON time, the clothes dryer will be turned OFF.
0, CDN≥ CDMAX
SCD,N= 1, CDN< CDMAX (3)
Where:
CDN clothes dryer’s accumulated ON time(min)
CDMAX clothes dryer’s required ON time (min)
N
SCD,
clothes dryer status (0=OFF; 1=ON).
5. HEM CONTROL STRATEGY FOR CD:
HEM controls the clothes dryer by turning OFF its heating coils, while leaving the motor part running. This is to ensure that the clothes dryer can restart its operation without consumer involvements. If the demand limit is force on this house and the clothes dryer is ON, the HEM is allowed to control the clothes dryer as required for the preset load priority. The clothes dryer ON time limit, e.g.30 min, can be defined to ensure that the clothes dryer operates for certain duration before it can be controlled OFF. The heating coil OFF time limit can also be specified to prevent uncontrolled heat loss during the clothes dryer operation.
However, these comfort level settings are allowed to be violating if any loads of higher priority need to operate to maintain the preset comfort ranges.
6. ELECTRIC VEHICLE OPERATION:
Once plugged in, an EV will be charged until its battery’s state of charge (SOCN) reaches the maximum state of charge (SOCMAX).
0, SOCN ≥ SOCMAX
SEV,N= 1, SOCN <SOCMAX (4)
Where
SOCN battery state of charge in time interval (%)
SOCMAX maximum battery state of charge (%);
N
SEV, EV status in time interval
7. HEM CONTROL ALGORITHM FOR EV:
The EV is allowed to be partly charged as soon as it is plugged in regardless of its priority without violating the demand limit. This will allow the homeowner to have the privilege to use the Vehicle earlier if needed. In certain circumstances when other appliances of higher priority required operating, the EV charging maybe placed on hold.
However, if the HEM system predicts the EV
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/576 charging cannot be completed by the time specified
by the consumer, the EV will be allowed to start charging earlier than planed by changing its priority.
IV. HEM ALGORITHM
At every time interval, the HEM algorithm starts by gathering information, which includes the status and power consumption of all appliances, load priority and customer priority settings, water temperature and room temperatures, as well as the demand limit and its associated duration. Then the HEM algorithm checks for comfort level violations, which include water temperatures for WH, room temperatures for Air conditioner, the required ON time and maximum OFF time and the minimum ON time for the clothes dryer; and the full charge time and the minimum charge time requested for the EV.
See Fig. 4. If there is a comfort level violation, the HEM decides on the status of each appliance based on the requested demand limit level. After the decision is made, the HEM sends control signals to change the selected device status. The total household power consumption is compared with the requested demand limit. If the household consumption is lower than the demand limit, no action is taken if there is no comfort level violation.
However, with the comfort level violation of appliance the HEM will force the selected appliance ON to minimize the comfort level violation. If the household consumption is greater than the demand limit and there is no comfort level violation, the HEM will turn OFF the lowest priority loads, in this case starting with the EV, the clothes dryer and the space cooling unit, to keep the total power consumption below the demand limit. If the household power consumption is greater than the demand limit and there is a comfort level violation of the appliance app, then the HEM will compare the priority of all ON appliances with the priority of this appliance, starting from the lowest priority loads to the highest one. If the priority of the appliance of APP is greater than any other appliances that are ON, the HEM will shut OFF the
lower priority loads until the appliance APP can be turned ON and the total power consumption is below the demand limit.
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/577
Fig 3.HEM algorithm flowchart (PART-1) Note: SAPP is the status of appliance APP that has the comfort level violation
NO YES
OFF OFF OFF OFF ON ON ON ON
NO NO NO NO YES YES YES YES
DL: Demand limit
TP: Total power LP: Load priority
Fig.4 HEM Algorithm flowchart (Part II) Assuming the load priority is as follows WH>AC>CD>EV
1. from appliance monitoring & control units
2. Status& power consumption of all appliances
User inputs: Load priority & comfort level setting
From Temperature sensors: Water & Room
temperature
Utility Inputs:
Demand limit (KW)
&Duration (hrs)
For WH: Check water temperature
For AC: Check room temperature
For CD: Check water temperature, Check Min ON & Max OFF time
For EV: Check complete time Check Min ON time
Request change of status for APP
Decide appliance status SWH-SAC- SCD-SEV
Update appliance status
SWH-SAC-SCD-SEV
SAPP ON
LP<LP (APP)
SWH
OFF WH
LP<LP (APP)
SAC OFF CD AC
LP<LP (APP)
SCD OFF LP<LP
(APP)
SEV OFF
Request SAPP ON
Update Total power Update Total power
TP>DL
EV
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/578 A. PLC LOGIC
(PLC) is an industrial computer control system. It is continuously monitors the state of input devices and makes decisions based on a custom program to control the state of output devices. Almost any production line, machine function, or process can be greatly enhanced using this type of control system. However, the biggest benefit in using a PLC is the ability to change and replicate the operation or process while collecting and communicating vital information. There are four steps in the operation of all PLCs Input Scan Program Scan Output Scan and Housekeeping. This step continually takes place in a repeating loop. Another advantage of a PLC system is that it is modular.
In this project we are using Micrologix 1400 Allen Bradley PLC for the uninterruptible power supply.
In Micrologix 1400, it electronically controls your application. The controllers are available in either 32 I/O point (20 inputs and 12 outputs) in 5 electrical configurations. The I/O options and electrical configurations make them ideal for almost any application.
In Figure 5 PLC Ladder logic diagram we have a four types of limits for checking current limits it should be within 0-10A.If current should be within 0-3A it represent the Binary B4.If the Current limit is 3-5A it represent B1.If the Current limit is 5-7A it represent B2.If the current limit is 7-10A it represent as B3.Below figure it shows the binary lines are 0001, 0002, 0003, 0004.Then we have two input one is Solar(B1,B2,B4), and another EB(B3).Then the three outputs are Low load, Medium load, Heavy load and each load consists of 2Relays. When the current demand (7-10A) is highB3 (EB) it directly send power to High load. And similarly current demand (0-7A) is low (B1, B2,B4) it directly send power to Low and Medium load.
V. SIMULATION RESULTS
NO NO
YES YES YES YES
HEM Algorithm Using Dynamic Load Management
Fig.5 illustrates the performance of the Dynamic load managing high power consumption appliances and keeping the total power consumption according their current limit level(0-10A).Current level consists of four types such as 0-3A,3-5A,5-7A,7-10A.we have consider solar and EB power. Load have three types like low level(0-5A),Medium level(5-7A) and High level(7-10A).we have assume low and medium level load as half peak hours it consumes power from solar energy. Peak hour’s load consumes power from EB and its current limits 7-10A.
Start
Solar and EB Power
Check current value within
(0-10A)
Current value split in to four types
(0-3A),(3-5A),(5-7A),(7-10A)
From solar power to Low and Medium Level Load
(Half peak hours)
From EB power to High Level Load
(peak hours)
Stop If
0<I≤3 A
If 3<I≤5 A
If 3<I≤5 A
If 7<I≤1 0A
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/579
Fig 5.Dynamic load management using Allen Bradley 1400 PLC
VI. CONCLUSION
This paper presents an home energy management (HEM) algorithm used for demand response applications. Simulation results show
S.Rajalingam and R.Mahamari ijesird , Vol. II Issue VIII February 2016/580 that the proposed HEM algorithm using
Allenbradley 1400 PLC can proactively and effectively control and manage the appliance operation to maintain the total household consumption below a specified demand limit.
The proposed HEM algorithm takes both load priority and customer priority settings. The flowchart results indicate that at a low demand limit level, HEM is able to maintain the total household demand below the limit. Customers may compromise their comfort level to some extent. Also, it is possible that a Demand Response event should create a high off-peak demand due to load satisfaction. This paper presents this limit and demonstrates that DR potential is a function of customer comfort priority and the demand limit level that does not affect high load compensation after a DR event.
It is expected that the results of work is benefit in electric distribution utilities and DR aggregators in providing the limits of DR in residential markets.
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