Sizing a BESS device too small may. â reduce its operating life through over use, such as exceeding maximum depth of discharge too frequently. â Long term ...
THE INTEGRATION AND CONTROL OF MULTIFUNCTIONAL STATIONARY PV-BATTERY SYSTEMS IN SMART DISTRIBUTION GRID
Mohammad Rezwan Khan
Objective Usage of battery system for defer upgrades needed in case of large penetration of • electric vehicle (EV), • electrified heat pump (HP) • photovoltaic (PV) panel • Approach Techno economic optimal sizing
• Consider season-based diurnal dynamics
Intended functions PrimaryThe counterbalance of overloading of transformer SecondaryArbitrage (buy low, sell high)
Find the optimal storage for satisfying daily energy dynamics.
Challenges • Consideration o Geographic location of the BESS system around the globe, o Power demand profiles, o Electricity pricing policies. • BESS Have investment and operating cost. • Different Technologies Pb-Ac battery Li-ion battery
Sizing a BESS device too small may reduce its operating life through over use, such as exceeding maximum depth of discharge too frequently Long term costs in addition to finite life time or render it ineffective for the required function (in the paper peak shaving). Sizing a device too large will result increased capital costs bigger cost of supplying energy.
Input • A given load profile encompassing of EV, HP and household data, PV generation power profile and tariff systems • Extrapolate data into Transformer load -No power loss while transmission.
• Market Profile: Time varying dynamic market price Low when demand is low High when demand is high
Attributes
Cycle life Charge efficiency,𝜂𝑐 Discharge efficiency,𝜂𝑑 Nominal Energy Specific cost of the battery system,𝐶𝐸𝑏𝑎𝑡 Battery peripheral lifetime Shelf life Allowable DoD
Li ion systems 1500 90%
Pb Acid systems 500 80%
98%
98%
1000€/kWh
400€/kWh
10 year
10 year
25 year 80%
10 year 50%
Input
Load profile of Household
Probabilistic Load profile of Household
Work flow
Market Model
Cumulative load profile in a transformer
In summer No overloading In a sunny day lot of Energy but less to consume
In midseason(spring/ Fall) -Less sun -Moderate load
In winter -Not adequate sun -More loads are operating Load profile of Transformer
Find an optimal size that would provide best output ensuring lifetime.
Approach Linear Programming • The first stage sets limits the In a linear programming exercise, options for storage size all the participating information and stemming from different corresponding constrains of a specific allowable transformer loading time period is available level. the algorithm is able to optimise the power flow of the battery given that • The second stage optimises the price profile and load profile is for BESS operation within given beforehand. technical and economic limits considering daily dynamics.
a single method can incorporate the technical constraints of a real system and the correlations between input data sets while producing a lowest cost solution.
Governing Equations Market Model _ BPX
𝑚𝑖 = (0.44 + 0.56𝑚𝑖
_ BPX
) ∗ 0.18
𝑚𝑘 = (0.14 + 0.86𝑚𝑘
) ∗ 0.18…City €c/kWh
London 13
Berlin 19
Antwerp 18
Battery State of Energy Model 𝛦𝑚𝑖𝑛 ⩽ 𝛦0 + Δt 1,2, … . 𝑡
Cautions and Shortcomings • There is only limited knowledge of the future’s weather and the electricity demand. • The influence of demand side management is not taken into account in this work. • Results are sensitive to the energy tariff system, battery system price and performance of local controller.
