Cloud Energy Storage for Residential and Small Commercial Consumers : A business Case Study

Cloud Energy Storage for
Residential and Small
Commercial Consumers :
A business Case Study
Shubham Kumar
MT/EE/10013/19
Power System

Contents:
Shubham Kumar Cloud Energy Storage : A business Case Study
TOPICS TO BE
COVERED
INTRODUCTION CONCEPT AND
BUSINESS MODEL
ECONOMIC
ANALYSIS
CASE STUDY CONCLUSION REFERENCES

Topics to
be
covered:
Energy storage is extensively recognized as a significant potential resource
for balancing generation and load in future power systems.
This presentation proposes a new type of DES-cloud energy storage (CES)-
that can provide energy storage services at a substantially lower cost.
This grid-based storage service enables ubiquitous and on-demand access to
a shared pool of grid-scale energy storage resources.
It provides users the ability to store and withdraw electrical energy to and
from centralized batteries.
This presentation describes the concept of CES and the control and
communication technologies that are required for its implementation and
its operating mechanism, as well as its business model.
Simulation results that are based on actual power system operating data
demonstrate the feasibility and economic benefit of CES.

Introduction
Transition from fossil fuels to renewable energy sources, with variable renewable energy (VRE)
sources, such as wind and photovoltaic (PV), increasing from 181.57 GW of worldwide installed
capacity in 2009 to 549.24 GW in 2014 , and generating 2.7% of the electrical energy consumed
globally. By 2050, wind power and PV are estimated to provide more than half of the electricity
demand in China and more than 40% of the electricity demand in the U.S
Maintaining the stability of the power system requires real-time balancing of the energy that is
consumed and produced.
The integration of VRE replaces controllable power-generating plants with an uncertain and
intermittent energy source that always complicates the task of satisfying the demand.
Energy storage can significantly facilitate VRE integration because it can store electrical energy
when VRE sources produce more power than can be used and release this energy when needed.
Notation:
VRE:Variable Renewable Energy

Introduction
Energy storage can smooth the intermittency ofVRE sources to better
follow the variation of the load demand.
Several energy storage technologies are in various stages of
development: pumped hydro, compressed air (CAES), super capacitor,
flywheel, and various types of flow batteries or solid batteries.
Although the cost of these energy storage technologies remains high
compared with the price of electricity, recent advances in battery
technologies, especially in lithium-ion chemistries, suggest that their
cost may be substantially declining.
In parallel, electricity markets are evolving toward a model in which a
larger number of consumers will be exposed to real-time prices.

Introduction
Consumers who have installed solar panels may also want to use this
storage to reduce their dependence on electricity from the grid.
These factors lead to the development and deployment of
distributed energy storage (DES).
In this case study, an alternative technique is considered i.e.: cloud
energy storage (CES).This technique supports both the needs of
residential DES and the optimal operation of storage resources.
The CES concept is inspired by cloud services and the sharing
economy.
As locating shared computing resources in ‘‘the cloud” enhances
their utilization and cost-effectiveness, CES is dependent on the
power grid to optimize the use of energy storage resources.

Case
Study lies
in three
aspects:
Proposing
Proposing the
concept of Cloud
Energy Storage
which would
utilize centralized
energy storage
facilities to
provide
distributed
storage services
for residential and
small commercial
users.
Describing
Describing the
architecture and
enabling
technologies,
operation
mechanism that
facilitate CES.
Designing
Designing the
business model of
CES and
demonstrating its
profitability using
real-life residential
load and
electricity data.

Concept and Business Model
CONCEPT OF CLOUD
ENERGY STORAGE
ARCHITECTUREAND
ENABLING
TECHNOLOGIES
OPERATION
MECHANISM
BUSINESS MODEL

Concept of cloud energy storage
• The demand for DES has very similar characteristics
to the demand for distributed computing services.
1) Uniformity 2)Transportability
• CES can be defined as a grid-based storage service
that enables ubiquitous and on-demand access to a
shared pool of grid-scale energy storage resources.
• CES provides users the ability to store and withdraw
electrical energy to and from centralized batteries.

• The structure of CES, which
consists of three main parts:
1) CES users
2) Energy storage facilities
3) CES operator
• Fig.1 also illustrates the flows of
information, energy and money
among the various participants.
• The CES operator bidirectionally
communicates with the CES
users and the energy storage
facilities.
• CES users send their requests for
charging and discharging to the
CES operator, who can give
advice to CES users regarding
their use of storage.
• The energy storage facilities are
fully controlled and monitored
by the CES operator
Fig. 1. Framework of cloud energy storage (CAES: compressed air
energy storage).

Architecture and enabling
technologies
• Fig.2 shows a CES system involves several
functional modules and relies on state-of-
the-art technologies, such as data analytics,
optimization and communication.
• The communication module of the CES
enables the exchange of information among
the CES operator and the users, the energy
management module and the power grid.
• Standard industrial network protocols such
as Modbus and Profibus can be used to
guarantee the security and reliability of
these communications. The communication
module of the CES also gathers information
about electricity prices to support the
scheduling of the batteries.
• CES operator also needs to forecast users’
charging and discharging demand, which
may require techniques that substantially
differ from traditional load forecasting.
Fig. 2. Architecture of the cloud energy storage system.

Architecture
and enabling
technologies
• schedule optimization module makes optimal operation
decisions for the energy storage facility based on the
forecasted and real charge and discharge demand and
electricity prices, as well as the state of charge of the
batteries.
• The optimization of the energy storage facility is
essentially a linear programming (LP) problem that can
be efficiently solved using commercial software.
Moreover different algorithm can also be used
(Advanced Stochastic, Robust Optimization,
Decomposition and Coordination approaches).
• The battery management system controls the charge
and discharge of each battery based on the optimized
schedule and monitors the state of charge and the state
of health of the batteries.
• This system is also responsible for the protection of the
battery cells and communication with the CES operator.

Operation
mechanism
• Fig. 3 shows, the users of the CES purchase
services from the CES operator for both the
electric power capacity and the energy capacity.
• To CES users, this virtual storage is like actual
batteries, with the exception that they are
operated by centralized operators.
• The CES operator gathers information about the
CES users and forecasts their charging and
discharging behaviors to determine their total
charging and discharging profiles for the next
day.
• The CES operator simultaneously forecasts
electricity prices for the next day and collects
information about the SOC of each energy
storage facility.
• In each single storage facility, the battery
management system receives the schedule from
the CES operator and optimally controls the
charge and discharge of different batteries to
maximize their life span.
Fig. 3. Operation mechanism of cloud energy storage

Business Model
• The business model of CES is similar to that of other
cloud-based businesses, such as cloud computing.
• CES users purchase or rent virtual energy storage capacity
from the cloud.The power and energy capacity can be
customized according to the needs of users.
• CES provides four types of social benefits.They are
1) Leverages the diversity in the users’ demand for
storage
2) Able to better schedule the battery
3) It can achieve an economy of scale that reduces the
unit investment cost
4) It can coordinate with multiple storage
technologies
• CES uses centralized energy storage facilities, which are
owned by CES operator, to provide decentralized energy
storage services, which makes the service provider easier
to take charge of energy storage facilities and to take
advantages of the economies of scale

Economic Analysis
FLOW OFTHE
ECONOMIC
ANALYSIS MODEL
USER SIDE MODEL SOCIAL COST AND
CES MODEL
BENEFIT AND
PROFITABILITY
INDICES

Flow of the economic
analysis model
• Fig.4 shows the flow of the model that is used to
evaluate the benefits and profitability of CES.
• First, the load profile of each user is assessed to
determine whether it could benefit from DES,
using the storage investment and operation
model for each user.
• Second, the storage investment and operation
model of CES is run considering the charging
and discharging behaviors of each user.
• Last, the total benefit is calculated by
comparing the social benefit for all users
between the use of DES (the DES case) and the
use of CES (the CES case).
Fig. 4. Flow chart of the economic analysis
model

User Side Model
• In the original case, when no storage is used, the annual cost to each user Ci
original
is defined as the annual electricity bill that each user pays to purchase power from
the grid
Ci
original
= 𝒕∈𝑻 𝝀 𝒕 𝒅 𝒕 𝚫𝒕 (1)
• If the user is equipped with DES, its annual cost Ci
DES is the annual equivalent
investment of DES and its annual electricity bill
Ci
DES = Ii
DES + Oi
User
=
𝒓
𝟏 − 𝟏+𝒓
−Y ( CP,DES Pi
Cap + CE,DES Ei
Cap ) + 𝒕∈𝑻[ 𝝀 𝒕(𝐏𝐢
Cap – Pd
i,t +
di,t)+ +𝜽𝒕 (Pc
i,t – Pd
i,t + di,t)- ] 𝚫𝒕 (2)

• The optimal power capacity and energy capacity of DES are optimized based on
the load of each user and the electricity prices.The optimal capacity model also
schedules the charge and discharge schedule at each time interval:
[Pi
Cap, Ei
Cap, Pc
i,t , Pd
i,t ] = arg Pi
Cap, Ei
Cap, Pc
i,t , Pd
i,t min(Ci
DES) (3)
• In the CES case, the charge and discharge schedule is assumed to be identical
to the DES case. Users purchase the power and energy storage capacity from
CES.The user’s annual cost in the CES case,
Ci
CES, User = Ai
CES + Oi
User
= (aP,CES Pi
Cap + aE,CES Ei
Cap ) + 𝒕∈𝑻[ 𝝀 𝒕(𝐏𝐢
Cap– Pd
i,t +
i,t – Pd
i,t + di,t)- ] 𝚫𝒕 (4)
• A comparison between (2) and (4) shows that the precondition for users to
participate in CES rather than buying DES is that the annual service fee for CES
is less than the annualized investment cost of an energy storage device

Social Cost and CES Model
• the total social cost of all users in the set of CDES, Social is the sum of the cost for all
users in the DES case:
CDES, Social = 𝒊∈𝑺 𝑪𝑬𝑺 Ci
DES (𝟓)
• In the CES case, the social cost is the sum of the investment in the entire storage
facility and the electricity bills for all users
CDES,Social = ICES + OCES,Social
=
𝒓
𝟏 − 𝟏+𝒓
−Y ( CP,CES PCap + CE,CES ECap ) + 𝒕∈𝑻[ 𝝀 𝒕(𝐏𝐭
C – PD
t +
t – PD
t + 𝒊∈𝑺 𝑪𝑬𝑺 di,t )- ] 𝒕 (6)
• The total cost for the CES operator is
CDES,Operator = ICES + OCES,Operator
=
𝒓
𝟏 − 𝟏+𝒓
−Y ( CP,CES PCap + CE,CES ECap ) + 𝒕∈𝑻[ 𝝀 𝒕(𝐏𝐭
C – PD
t +
𝐢∈𝐒 𝑪𝑬𝑺 𝑷 𝑫
𝒊, 𝒕)+ +𝜽𝒕 (Pc
t – PD
t + 𝐢∈𝐒 𝑪𝑬𝑺 𝑷 𝑫
𝒊, 𝒕)- ] 𝒕 - 𝒕∈𝑻 𝐢∈𝑺 𝑪𝑬𝑺 𝝀 𝒕 Pc
i,t t
(7)

Benefit and profitability indices
• The revenue of CES RCES consists of the income from the users’ annual service
fees
RCES = 𝐢∈𝑺 𝑪𝑬𝑺 𝑨𝒊
𝑪𝑬𝑺 (𝟖)
• The maximum rate of return on investment of CES is defined as the ratio of the
maximum profit over the investment in CES:
η =
𝑪 𝑫𝑬𝑺
,
𝑺𝒐𝒄𝒊𝒂𝒍
−
𝑪𝑪𝑬 𝑺
,
𝑺𝒐𝒄𝒊𝒂𝒍
𝒓
𝟏 − 𝟏+𝒓
−
Y (𝑪𝑷
,
𝑪𝑬𝑺
𝑷 𝑪𝒂𝒑
+𝑪𝑬
,
𝑪𝑬𝑺
𝑬 𝑪𝒂𝒑
)
(9)
• The profit margin of CES is defined as the ratio of the CES profit and revenue:
k =
𝐦𝐚𝐱 𝑹 𝑪𝑬𝑺
−
𝑪𝑪 𝑬𝑺
,
𝑶𝒑𝒆𝒓𝒂𝒕𝒐𝒓
𝐦𝐚𝐱 𝑹 𝑪𝑬𝑺 (10)
where the 𝐦𝐚𝐱 𝑹 𝑪𝑬𝑺 −
𝑪𝑪 𝑬𝑺, 𝑶𝒑𝒆𝒓𝒂𝒕𝒐𝒓 denotes the maximum annual profit of CES.

Case Study
• Basic data setting
• Simulation results
• Cost analysis
• Sensitivity analysis
• Discussion

Basic data
setting
testing is based on actual load profiles from 400 Irish residential consumers
in 2009 with a time interval of 30 min.
The evaluation is performed using both peak/off-peak prices and real-time
prices for Ireland in 2009.
Assume that each residential consumer is equipped with a DES with optimal
capacity and calculate its optimal daily charge and discharge schedule for
the entire year using peak/off-peak prices and real-time prices.
Calculate the optimal investment and operation of CES that satisfies the
aggregated charge and discharge profiles for all consumers.
Evaluate the profitability of CES based on this social benefit.

Simulation results
• It compares the aggregated charge and discharge
power of all consumers and CES for a typical day
using both peak/off-peak prices and real-time prices.
• Negative values in the time series indicate that the
storage is discharging.
• It also shows electricity prices change over the course
of this particular day.
• The peak value of the CES charging profile is
significantly less than the peak value of the
aggregated DES charging profile.
• The optimal schedule of CES usually charges less
electricity than the optimal schedule of DES.
• It reduces the total cost over a longer time horizon.
Fig. 5. Comparison between the
operation of CES and the aggregated
operation of individual DES

Cost analysis
• Figure 6 illustrates the improvement in CES
model in social welfare.
• The DES unit prices are set as 180
USD/kWh and 60 USD/kW (60% of the base
unit prices).
• The unit cost of investments for CES is
assumed to be 20% less than the unit cost
of investments for DES in Fig. 6
• The CES income is equivalent to the sum of
the CES investment cost, the CES
operating cost and the CES model total
benefit.
Fig. 6. Breakdown of annual cost and income of CES.

Sensitivity Analysis
• To calculate the annual rate of return on CES investment
based on the calculated profit for operation using both
peak/off-peak prices and real-time prices.
• Optimal investment and operation of CES is simulated for
investment costs for CES and DES, which range from 20%
of the current price to 100%.
• Fig. 8 shows that CES is profitable in all cases, with the
exception when the investment cost is 100% or 80%
using peak/off-peak prices.
• The return on investment of CES increases if the unit cost
of energy storage decreases.
• The economies of scale also improves the profitability of
CES and justify its business model

Discussion
• Case study demonstrates the economic
feasibility of CES.
• Under the peak/off-peak prices, 100% and 80%
of base energy storage unit price are still
prohibitively high, while when energy storage
unit price is no more than 60%, users will want
to use energy storage and CES would be
profitable.
• Under the real-time prices, CES will be feasible
when the energy storage unit price is 20–100%
of base value.
• The trends of rate of return on investment show
that the economies of scale will help enhance
the profitability of CES significantly and that the
changes of storage unit price have smaller
influences on the rate of return on investment
compared with the economies of scale.
Shubham Kumar

Discussion
• The future development of CES service is
driven by two main factors.
1)The need of energy storage
2)The cost of storage
• It shows that the rate of return will increase
by 45% if the unit cost of energy storage
decreases by 30%.
• The CES business risks include policy risks
and public acceptance risks.
• The public recognition of energy storage as a
part of the energy consumption habituation
is needed, which is true for both DES and
CES
Shubham Kumar

Conclusion
• With the Cloud Energy Storage, we can provide
the same services to these users at a lower social
cost.
• The structure of CES consists of three main parts:
1)The CES user 2)Energy Storage facilities
3)The CES operator
• CES users can use their cloud batteries just like real
energy storage devices, while the CES operator
will invest and operate centralized energy storage
facilities to provide storage services to these users.
Shubham Kumar

Conclusion
• CES is also demonstrated to be able to gain social
benefits through a case study based on actual
residential load data and electricity prices.
• The result indicates that:
1) CES is easier to profit under real-time prices than
under peak/off-peak prices
2)The energy storage unit price decreases brought
by technology advance would not have a big
influences on the percentages of social welfare
improved by CES.
3) Economies of scale has a significant influence on
the economy of CES.

Future Work
• In the future, CES may not only employ a
centralized storage facility but also gather
fragments of energy storage resources,
such as electric vehicles, UPSs, or even
residential distributed batteries.
• The business model of CES will be available
to various players in the power system.
Both retailers and aggregators can invest in
CES to improve their profits and reduce
their costs of buying electricity.
• The business model of CES could also be
merged into some current business models
as value-added services.

References
• IRENA. Renewable energy integration in power
grids
• IRENA, Renewable energy prospects: China
• MaiT, Sandor D,Wiser R, SchneiderT. Renewable
electricity futures study. Executive summary. No.
NREL/TP-6A20-52409-ES. National Renewable
Energy Laboratory (NREL), Golden, CO., 2012.T
Mai, D Sandor, RWiser,T Schneider.
• IEA.The power of transformation - wind, sun and
the economics of flexible power systems
• Neubauer, Jeremy, M. Simpson. Deployment of
behind-the-meter energy storage for demand
charge reduction.Technical report: NREL/TP-
5400-63162, 2015.

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