Smart energy management for unlocking demand ... Smart energy management for unlocking demand response

  • View
    0

  • Download
    0

Embed Size (px)

Text of Smart energy management for unlocking demand ... Smart energy management for unlocking demand...

  • Smart energy management for unlocking demand response in residential applications

    Xiangping Chen, Kui Weng, Fanlin Meng, Monjur Mourshed BRE Trust centre for sustainable engineering, Cardiff University, B24 3AB , UK

  • Smart energy management for unlocking demand response in residential applications

    Abstract

    This paper presents a smart energy management system which is primarily

    designed for the residential applications in the UK. First of all, a 24-hour

    ahead demand profile is scheduled by shafting potential flexible load. And

    then both one-hour energy demand and supplying flow are estimated. The

    real-time electrical demand is satisfied by the combined renewable energy

    sources/grid electricity/batteries with minimal cost.

  • Utility information/

    Electricity & gas prices

    • Forecasted load consumption,

    • PV generation

    • Battery capacity (exchangeable energy amount)

    • Estimation on the controllable load

    • Forecasting weather data

    One-hour ahead PV generation information Battery charge/discharge schedule Electrical Appliance calculation

    Optimal scheme for whole day operation

    Comfort evaluation and temperature setpoint calculation

    Model predictive thermal control

    Electrical demands calculation

    Demand=

  • Smart energy management for unlocking demand response in residential applications

    Methodology:

    • First of all, we forecast weather and predict the overall energy consumption, state of energy

    storage, electricity price. The load are categorised into non-shiftable, time shiftable and

    power shiftable load groups afterwards. Therefore, day-ahead facility operation scheme is

    decided;

    • One-hour ahead supply estimation and comfort setting are defined to configure the energy

    consumption profile;

    • Dynamic programming framework is used to optimise the real-time operation where PV,

    battery and grid electricity are combined to configure optimal supplying flow to balance the

    real-time electrical demand under the objective proposed.

  • Smart energy management for unlocking demand response in residential applications

    Load

    Shiftable Non-shiftable

    Time shiftable Power

    shiftable

    Wash machine Dish washer Water pump Electrical vehicle

    cooker oven Refrigera

    tor

  • Smart energy management for unlocking demand response in residential applications

    0

    1

    2

    3

    4

    5

    1 8 1

    5 2

    2 2

    9 3

    6 4

    3 5

    0 5

    7 6

    4 7

    1 7

    8 8

    5 9

    2 9

    9 1

    0 6

    1 1

    3 1

    2 0

    1 2

    7 1

    3 4

    1 4

    1 1

    4 8

    1 5

    5 1

    6 2

    C O

    N SU

    M P

    TI O

    N (

    K W

    )

    TIME (HOUR)

    Electrical consumption profile (7 days)

    0

    1

    2

    3

    4

    5

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

    One-day ahead consumption forecasting

    0

    0.5

    1

    1.5

    2

    2.5

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

    C O

    N SU

    M P

    TI O

    N (

    K W

    )

    TIME (HOUR)

    Shiftable load

    0

    0.5

    1

    1.5

    2

    2.5

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

    C O

    N SU

    M P

    TI O

    N (

    K W

    )

    TIME(HOUR)

    Non-shiftable load

  • Smart energy management for unlocking demand response in residential applications

    Energy supply

    0

    500

    1000

    1500

    2000

    2500

    3000

    3500 1 6

    1 1

    1 6

    2 1

    2 6

    3 1

    3 6

    4 1

    4 6

    5 1

    5 6

    6 1

    6 6

    7 1

    7 6

    8 1

    8 6

    9 1

    9 6

    1 0

    1

    1 0

    6

    1 1

    1

    1 1

    6

    1 2

    1

    1 2

    6

    1 3

    1

    1 3

    6

    1 4

    1

    1 4

    6

    1 5

    1

    1 5

    6

    1 6

    1

    1 6

    6

    P O

    W ER

    ( W

    )

    TIME (HOUR)

    Solar power

    Grid electricity price

    Time (hour)

    £

  • Smart energy management for unlocking demand response in residential applications

    • By re-scheduling the usage of shiftable appliances, the energy

    cost can be reduced to some extent. However, it could

    deteriorate the users’ conform. Furthermore, the high

    electrical demand takes place between 17’oclock and

    21’oclock when grid price gradually increase to its peaks.

    • There is a need to adopt better adjustable method to satisfy

    both comfort and economic requirement for the domestic

    users.

  • Smart energy management for unlocking demand response in residential applications

    • Energy storage systems, such as batteries are the good option

    for domestic electricity demand shifting/shedding/peak

    reduction. They can be regarded as either time

    shiftable/power shiftable loads or power supply resource.

    • In this study, batteries are used for adjustment method to

    balance demand and supply which in turn minimize both the

    discomfort and the cost.

  • Smart energy management for unlocking demand response in residential applications

    • Real-time operation

    0 < 𝑤𝑝𝑣 < 𝑤𝑚𝑎𝑥

    𝑆𝑂𝐶𝑚𝑎𝑥 < 𝑆𝑂𝐶 < 𝑆𝑂𝐶𝑚𝑖𝑛

    ൯𝑤𝑙𝑜𝑎𝑑 = 𝑤𝑔𝑟𝑖𝑑 𝑡 + 𝑤𝑝𝑣 𝑡 + 𝑤𝑏𝑎𝑡𝑡𝑒𝑟𝑦(𝑡

    𝐶𝑔𝑟𝑖𝑑𝑚𝑖𝑛 < 𝐶1 < 𝐶𝑔𝑟𝑖𝑑𝑚𝑎𝑥

    S.t.

    𝐽 = 𝑚𝑖𝑛 σ(𝐶1 ∙ (𝑤𝑔𝑟𝑖𝑑(t)) ∙ ℎ1(𝑡) + 𝛼 ∙ (𝑤𝑏𝑎𝑡𝑡𝑒𝑟𝑖𝑒𝑠 𝑡 ∙ ℎ2 𝑡 + 𝛽 ∙ (𝑤𝑃𝑉 𝑡 ) ∙ ℎ3 𝑡 )

  • Smart energy management for unlocking demand response in residential applications

    • Case Study

    The optimal strategy is validated via the energy system in a detached 3-

    bedroom house. The house is located in London with 101.25 m2 space.

    Simulation is executed within 168 hours in a summer week. A daily energy

    consumption and supplies are evaluated as follows,

  • Smart energy management for unlocking demand response in residential applications

    Case Study

    A daily demand and supplies (a) without optimisation (b)with optimisation

    -2000

    -1000

    0

    1000

    2000

    3000

    4000

    5000

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

    P o

    w e

    r (W

    )

    Time (hour) Scheduled demand solar power batteries power grid power

    -1000

    0

    1000

    2000

    3000

    4000

    5000

    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

    P o

    w e

    r (W

    )

    Time (hour)

    Electrical demands(W) PV power (W) Grid electricity (W)

  • Smart energy management for unlocking demand response in residential applications

    Case Study

    without optimisation with optimisation

    Demand(kWh) 43.59 43.59

    Electricity bought(kWh) 21.49 19.18

    Electricity sold(kWh) 2.71 0.4

    PV energy(kWh) 24.81 24.81

    Peak demand (kW) 4.21 2.84

    Electricity cost(£) 2.98 1.95

  • Smart energy management for unlocking demand response in residential applications

    Conclusion:

    This study developed an optimal operation scheme for a energy system in

    a domestic house. The highlights are summarised as follows:

    1. Load shifting/load shedding are realised through a day-ahead

    scheming;

    2. Energy storage assistants the realisation of peak shafting;

    3. The costs for buying electricity are reduced;

    4. CO2 emission will be considered in the future research.

  • Smart energy management for unlocking demand response in residential applications

    Thanks