Aggregated and optimized virtual power plant control

• US 10,103,550 B2
• Filed: 01/19/2016
• Issued: 10/16/2018
• Est. Priority Date: 01/19/2016
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Nakayama, Kiyoshi, Chen, Wei-Peng
• Primary Examiner(s): Lee, Thomas C
• Assistant Examiner(s): Nguyen, Tri T
• Application Number:
  US15/000,970
• Publication Number:
  US 20170207633A1
• Time in Patent Office: 1,001 Days
• CPC Class Codes: G05B 13/026 using a predictor
• CPC Class Codes: H02J 2300/20 The dispersed energy generation being of renewable origin
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 2300/28 The renewable source being wind energy wind motors F03D
• CPC Class Codes: H02J 2310/48 for electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: H02J 2310/54 according to a pre-established time schedule
• CPC Class Codes: H02J 2310/58 The condition being electrical
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 3/144 Demand-response operation of the power transmission or distribution network
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 3/466 Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02D 30/70 in wireless communication networks
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 10/76 Power conversion electric or electronic aspects
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving

Abstract

A method of aggregated virtual power plant (VPP) control includes receiving control variable values. The control variables are received for control variables related to energy production and loads of devices electrically coupled to an electrical grid and communicatively coupled to the VPP controller server. The method includes inputting the control variable values into an objective algorithm. The method may include executing the objective algorithm. Executing the objective algorithm includes adjusting energy loads and energy production of prosumers, adjusting an energy amount supplied from a supply side for multiple time intervals, and adjusting curtailment of the energy loads in the prosumers based thereon. The method includes generating a VPP DR event schedule and communicating it to VPP client servers. The VPP DR event schedule includes control signals that are configured to affect an operating condition of the devices that are controlled by the VPP client servers.

Claims

1. A method of aggregated virtual power plant (VPP) control, the method comprising:

receiving, at a VPP controller server of a VPP, one or more control variable values from a previous time interval for a plurality of control variables, the plurality of control variables being related to energy production and energy loads of devices that are electrically coupled to an electrical grid and communicatively coupled to the VPP controller server;

inputting, at the VPP controller server, the control variable values into an objective algorithm, the objective algorithm being configured to increase a contribution of renewable energy production to serve a demand and integration of energy source devices communicatively coupled to the VPP controller server and to reduce energy generation and integration of energy produced by a utility;

executing, by the VPP controller server, the objective algorithm, the executing the objective algorithm includes adjusting energy loads and energy production of one or more prosumers of the VPP, adjusting an energy amount supplied from a supply side of the VPP for one or more time intervals, and adjusting curtailment of the energy loads in the prosumers based on an adjusted energy supplied from the supply side of the VPP and adjusted energy loads and energy production of the one or more prosumers, the adjusting curtailment of the energy loads in the prosumers includes generating a set of curtailment amounts of loads for each of the prosumers and for each time interval (Al(t)), determining whether a total demand that is not covered by the renewable resource is smaller than a DR capacity, and in response to the total demand being smaller than the DR capacity, conducting a prosumer selection based on one or more or a combination of;

participation likelihood of each prosumer for past DR events, curtailment capacity and estimation, a number of available and occupied resources, and a benefits and costs analysis;

based on the objective function, generating, at the VPP controller server, a VPP demand response (DR) event schedule that includes a charge/discharge schedule of one or more energy source devices and a charge/discharge schedule for one or more energy load devices; and

communicating in real time, by the VPP controller server, the VPP DR event schedule to one or more VPP client servers, the VPP DR event schedule including control signals that are configured to affect an operating condition of one or more of the devices that are controlled by the VPP client servers.

2. The method of claim 1, further comprising communicating the control signals to the devices to affect an operating condition of the devices in accordance with the VPP DR event schedule.

3. The method of claim 1, wherein:

the control variable values include;

initial energy levels of electric vehicles (EV) of the one or more prosumers {e₁(0), e₂(0), . . . , e_M(0)},

initial energy levels of stationary batteries of the one or more prosumers (pro batteries) {s₁(0), s₂(0), . . . , s_M(0)},

forecasted photovoltaic (PV) production for a current time interval for each PV associated with each of the prosumers (pro PV) {p₁(t), p₂(t), . . . , p_M(t)}, and

forecasted loads for the current time interval for each of the prosumers {l₁(t), l₂(t), . . . , l_M(t)}; and

the adjusting the energy loads and the energy production of the one or more prosumers includes;

receiving the control variable values as inputs; and

generating for each of the prosumers at the current time interval an adjusted value for;

a curtailed amount of PV generation (Δ

p_i(t));

a discharge amount from a pro battery (u_i(t)),

a charge amount from a pro PV to a pro battery (v_i(t)),

a discharge amount from one or more EVs (x_i(t)),

a charge amount from a pro PV to a connected EV (y_i(t)),

an amount of energy sent from a pro PV directly to the load (z_i(t)),

discharge output from one or more pro batteries to the electrical grid (o_i^s(t)),

discharge output from one or more of the EVs associated with the prosumer to the electrical grid (o_i^e(t)), and

discharge output from one or more of the pro PVs to the electrical grid (o_i^p(t)),

in which;

 

t represents the current time interval,

 

M represents a number of prosumers, and

 

i is an indexing variable that ranges from 1 to M.

4. The method of claim 3, wherein the adjusting the energy loads and the energy production of the one or more prosumers further includes:

determining whether p_i(t)≥

l_i(t);

in response to p_i(t)≥

l_i(t);

setting;

z_i(t)=l_i(t),

u_i(t)=0, and

x_i(t)=0; and

determining whether s_i(t−

1)+(p_i(t)−

l_i(t))≤

s_i;

in response to s_i(t−

1)+(p_i(t)−

l_i(t))≤

s_i;

setting;

v_i(t)=p_i(t)−

l_i(t),

y_i(t)=0,

o_i^s(t)=0,

o_i^p(t)=0, and

Δ

p_i(t)=0;

in response to s_i(t−

1)+(p_i(t)−

l_i(t))≥

s_i;

setting v_i(t)=s_i−

s_i(t−

1), and

determining whether e_i(t−

1)+(p_i(t)−

l_i(t)−

(s_k−

s_i(t−

1)))≤

e_i;

and

in response to e_i(t−

1)+(p_i(t)−

l_i(t)−

(s_i−

s_i(t−

1)))≤

e_i, setting;

y_i(t)=p_i(t)−

l_i(t)−

(s₁−

s_i(t−

1)),

o_i^s(t)=0,

o_i^e(t)=0,

o_i^p(t)=0, and

Δ

p_i(t)=0,

in which;

v_i( ) represents a charge amount from a pro PV to a pro battery;

l_i( ) represents a load at one of the prosumers;

s_i( ) represents an energy level of a pro battery at t;

t−

1 represents a previous time interval;

x_i( ) represents a discharge amount from one or more EVs;

y_i( ) represents a charge amount from a pro PV of the prosumer to a connected EV;

p_i( ) represents a forecasted PV production;

^- represents a maximum capacity of a parameter;

o_i^s( ) represents discharge output from one or more pro batteries to the electrical grid;

o_i^p( ) represents discharge output from one or more of the pro PVs to the electrical grid;

o_i^e( ) represents a discharge output from one or more of the EVs associated with the prosumer to the electrical grid;

Δ

p_i( ) represents a curtailed amount of PV generation; and

e_i( ) represents energy levels of an EV.

5. The method of claim 4, wherein the adjusting the energy loads and the energy production of the one or more prosumers includes:

in response to

e_i(t−

1)+(p_i)−

l_i(t)−

(s_i−

s_i(t−

1)))>

e_i;

setting y_i(t)=e_i−

e_i(t−

1);

determining whether p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)≤

o_i^p;

in response to p(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)≤

o_i^p, setting;

Δ

p_i(t)=0,

o_i^s(t)=0,

o_i^e(t)=0,

o_i^p(t)=p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t);

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)>

o_i^p;

setting o_i^p(t)=o_i^p; and

determining whether

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p≤

o_i^s;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p≤

o_i^s, setting;

o_i^s(t)=p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p,

v_i(t)←

v_i(t)+o_i^s(t), and

o_i^s(t)=0,Δ

p_i(t)=0;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p>

o_i^s;

setting;

o_i^s(t)=o_i^s, and

v_i(t)←

v_i(t)+o_i^s; and

determining whether

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s≤

o_i^e;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s≤

o_i^e,

setting;

o_i^s(t)=

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s, and

y_i(t)←

y_i(t)+o_i^s(t),Δ

p_i(t)=0; and

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s≤

o_i^e,

setting;

o_i^s(t)=o_i^s,y_i(t)←

y_i(t)+o_i^s, and

Δ

p_i(t)

=p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s−

o_i^s.

6. The method of claim 5, wherein the adjusting the energy loads and the energy production of the one or more prosumers includes:

in response to p_i(t)<

l_i(t)

setting;

z_i(t)=p_i(t),

Δ

p_i(t)=0,

o_i^s(t)=0,

o_i^e(t)=0

o_i^p(t)=0,

v_i(t)=0, and

y_i(t)=0; and

determining whether l_i(t)−

p_i(t)≥

s_i(t−

1);

in response to l_i(t)−

p_i(t)<

s_i(t−

1), setting;

u_i(t)=l_i(t)−

p_i(t), and

x_i(t)=0;

in response to l_i(t)−

p_i(t)≥

s_i(t−

1),

setting u_i(t)=s_i(t−

1);

determining whether l_i(t)−

p_i(t)−

s_i(t−

1)≥

e_i(t−

1);

in response to l_i(t)−

p_i(t)−

s_i(t−

1)≥

e_i(t−

1), setting

x_i(t)=e_i(t−

1);

in response to

l_i(t)−

p_i(t)−

s_i(t−

1)<

e_i(t−

1), setting

x_i(t)=l_i(t)−

p_i(t)−

s_i(t−

1).

7. The method of claim 3, wherein:

the control variable values include;

initial charge levels of supply-side batteries of the supply side of the VPP {b₁(0), b₂ (0), . . . , b_j(0)};

forecasted renewable generation for photovoltaic cells of the supply side of the VPP (supply PVs) {r₁(t), r₂ (t), . . . , r_N(t)};

forecasted wind generation for wind turbines of the supply side of the VPP {w₁(t), w₂(t), . . . , w_H(t)}; and

forecasted loads for prosumers {l₁(t), l₂(t), . . . , l_M(t)}; and

an adjusted value for Δ

p_i(t), u_i(t), v_i(t), x_i(t), y_i(t), z_i(t), o_i^s(t), o_i^e(t), and o_i^p(t); and

adjusting energy supplied from the supply side of the VPP includes;

receiving the control variable values as inputs; and

generating adjusted values for;

a charge amount from a supply PV to a supply-side battery (q_i(t));

a curtailment amount of PV generation (Δ

r_g(t));

a charge amount from a wind turbine to a supply-side battery (w_k(t));

a curtailment amount of wind generation (Δ

w_k(t));

a discharge amount from a supply-side battery to loads (ƒ

_j(t)); and

energy sent from the electrical grid to a load at a prosumer (o_i^d(t)),

in which;

H represents the number of wind turbines in the supply side;

N represents the number of supply PVs in the supply side;

J represents the number of supply-side batteries;

k represents an indexing variable for the wind turbines with a range from 1 to H;

j represents an indexing variable for the supply-side batteries with a range from 1 to J;

i represents an indexing variable for the supply PVs with a range from 1 to N.

8. The method of claim 7, wherein adjusting energy supplied from the supply side of the VPP includes:

initializing ƒ

_j(t), g_i(t), and Δ

l_i(t) to be zero;

defining Δ

d_i(t)=l_i(t)−

u_i(t)−

x_i(t)−

z_i(t) and Δ

o_i=o_i^s(t)+o_i^e(t)+o_i^p(t), based on the results from the adjusting energy loads and energy production of one or more prosumers of the VPP;

determining whether Σ

_l=1^Nr_i(t)+Σ

_k=1^Hw_k(t)≥

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^M=Δ

o_i(t);

in response to Σ

_l=1^Nr_i(t)+Σ

_k=1^H=w_k(t)≥

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t);

setting;

F⁺(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^M=Δ

o_i(t),

o_i^d(t)=Δ

d_i, and

G(t)=0;

deciding ƒ

*_j(t) based on F⁺(t);

determining whether b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)−

ƒ

*_j(t)≤

b_j;

in response to b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)−

ƒ

*_j(t)≤

b_j;

setting q_s(t)=r_i(t), Δ

r_i(t)=0;

determining whether b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)≤

b_j;

in response to b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)≤

b_j, setting w_k(t)=w_k(t), Δ

w_k(t)=0;

in response to

b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>μ

j</sup>w_k(t)−

ƒ

*_j(t)>

b_j;

setting;

Σ

_k=1<sup>β

j</sup>ω

_k(t)=b_j−

b_j(t−

1)−

Σ

_i=1<sup>γ

j</sup>r_i(t)+ƒ

*_j(t), and

Σ

_k=1<sup>β

j</sup>Δ

w_k(t)=Σ

_k=1<sup>β

j</sup>w_k(t)−

(b_j−

b_j(t−

1)−

β

_i=1<sup>γ

j</sup>r_i(t)+

ƒ

*_j(t));

and

calculating ω

*_i(t) based on

Σ

_k=1<sup>β

j</sup>ω

_k(t)=b_j−

b_j(t−

1)−

Σ

_i=1<sup>γ

j</sup>r_i(t)+ƒ

*_j(t);

in response to

b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)>

b_j;

setting;

Σ

_i=1<sup>γ

j</sup>q_i(t)=b_j−

b_j(t−

1)+ƒ

*_j(t),

Σ

_i=1<sup>γ

j</sup>Δ

r_i(t)=Σ

_i=1<sup>γ

j</sup>r_i(t)−

(b_j−

b_j(t−

1)+ƒ

*_j(t)), and

ω

_k(t)=0,Δ

w_k(t)=w_k(t); and

calculating q*_i(t) based on Σ

_i=1<sup>γ

j</sup>q_i(t)=b_j−

b_j(t−

1)+ƒ

*_j(t).

9. The method of claim 8, wherein adjusting energy supplied from the supply side of the VPP includes:

in response to Σ

_l=1^Nr_l(t)+Σ

_k=1^Hw_k(t)≤

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t);

setting;

q_i(t)=r_i(t),

Δ

r_i(t)=0,

ω

_k(t)=w_k(t), and

Δ

w_k(t)=0;

determining whether

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)≥

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)×

Σ

_k=1<sup>β

j</sup>w_k(t)};

in response to Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_s(t)≥

Σ

_j=1^J{b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t)}, setting;

ƒ

_j(t)=b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t),

G(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)−

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t)},

and

o_i^d(t)=Δ

d_i(t)+Δ

l_i(t);

in response to

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)<

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r(t)+Σ

_k=1<sup>β

j</sup>w_k(t)},

setting;

F*(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t), and

o_i^d(t)=Δ

d_i(t),G(t)=0; and

deciding ƒ

*_j(t) based on F*(t).

10. The method of claim 1, wherein:

the control variable values include;

curtailment capacity of the prosumers nodes {l₁, l₂, . . . , l_M},

discharging rates of supply-side batteries for each time interval (t) ƒ

₁(t), ƒ

₂(t), . . . , ƒ

_l(t)), and

updated sets of demands that are based on adjusted energy loads and energy production of the one or more prosumers of the VPP and adjusted energy supplied from the supply side of the VPP {d₁(t), d₂ (t), . . . , d_M(t)}; and

the adjusting curtailment of the energy loads in the prosumers includes in response to the total demand being greater than the DR capacity, dispatching a DR event to all prosumers with a non-zero curtailment amount.

11. A non-transitory computer-readable medium having encoded therein programming code executable by a processor to perform or control performance of operations comprising:

receiving, at a virtual power plant (VPP) controller server of VPP, one or more control variable values from a previous time interval for a plurality of control variables, the plurality of control variables being related to energy production and energy loads of devices that are electrically coupled to the electrical grid and communicatively coupled to the VPP controller server;

inputting, at the VPP controller server, the control variable values into an objective algorithm, the objective algorithm being configured to increase a contribution of renewable energy production to serve a demand and integration of energy source devices communicatively coupled to the VPP controller server and to reduce energy generation and integration of energy produced by the utility;

executing, by the VPP controller server, the objective algorithm, wherein executing the objective algorithm includes adjusting energy loads and energy production of one or more prosumers of the VPP, adjusting an energy amount supplied from a supply side of the VPP for one or more time intervals, and adjusting curtailment of the energy loads in the prosumers based on an adjusted energy supplied from the supply side of the VPP and adjusted energy loads and energy production of the one or more prosumers, the adjusting curtailment of the energy loads in the prosumers includes generating a set of curtailment amounts of loads for each of the prosumers and for each time interval (A1(t)), determining whether a total demand that is not covered by the renewable resource is smaller than a DR capacity, and in response to the total demand being smaller than the DR capacity, conducting a prosumer selection based on one or more or a combination of;

participation likelihood of each prosumer for past DR events, curtailment capacity and estimation, a number of available and occupied resources, and a benefits and costs analysis;

based on the objective function, generating, at the VPP controller server, a VPP demand response (DR) event schedule that includes a charge/discharge schedule of one or more energy source devices and a charge/discharge schedule for one or more energy load devices; and

communicating in real time, by the VPP controller server, the VPP DR event schedule to one or more VPP client servers, the VPP DR event schedule including control signals that are configured to affect an operating condition of one or more of the devices that are controlled by the VPP client servers.

12. The non-transitory computer-readable medium of claim 11, wherein the operations further comprise communicating the control signals to the devices to affect an operating condition of the devices in accordance with the VPP DR event schedule.

13. The non-transitory computer-readable medium of claim 11, wherein:

the control variable values include;

initial energy levels of electric vehicles (EV) of the one or more prosumers {e₁(0), e₂(0), . . . , e_M(0)},

initial energy levels of stationary batteries of the one or more prosumers (pro batteries) (s₁(0), s₂(0), . . . , s_M(0)),

forecasted photovoltaic (PV) production for a current time interval for each PV associated with each of the prosumers (pro PV) {p₁(t), p₂(t), . . . , p_M(t)}, and

forecasted loads for the current time interval for each of the prosumers {l₁(t), l₂(t), . . . , l_M(t)}; and

the adjusting the energy loads and the energy production of the one or more prosumers includes;

receiving the control variable values as inputs; and

generating for each of the prosumers at the current time interval an adjusted value for;

a curtailed amount of PV generation (□

p_i(t));

a discharge amount from a pro battery (u_i(t)),

a charge amount from a pro PV to a pro battery (v_i(t)),

a discharge amount from one or more EVs (x_i(t)),

a charge amount from a pro PV to a connected EV (y_i(t)),

an amount of energy sent from a pro PV directly to the load (z_i(t)),

discharge output from one or more pro batteries to the electrical grid (o_i^s(t)),

discharge output from one or more of the EVs associated with the prosumer to the electrical grid (o_i^e((t)), and

discharge output from one or more of the pro PVs to the electrical grid (o_i^p(t)),

in which;

 

t represents the current time interval,

 

M represents a number of prosumers, and

 

i is an indexing variable that ranges from 1 to M.

14. The non-transitory computer-readable medium of claim 13, wherein the adjusting the energy loads and the energy production of the one or more prosumers further includes:

determining whether p_i(t)≥

l_i(t);

in response to p_i(t)≥

l_i(t);

setting;

z_i(t)=l_i(t),

u_i(t)=0, and

x_i(t)=0; and

determining whether s_i(t−

1)+(p_i(t)−

l_i(t))≤

s_i;

in response to s_i(t−

1)+(p_i(t)−

l_i(t))≤

s_i;

setting;

v_i(t)=p_i(t)−

l_i(t),

y_i(t)=0,

o_i^s(t)=0,

o_i^e(t)=0,

o_i^p(t)=0, and

Δ

p_i(t)=0;

in response to s_i(t−

1)+(p_i(t)−

l_i(t))>

s_i

setting v_i(t)=s_i−

s_i(t−

1), and

determining whether e_i(t−

1)+(p_i(t)−

l_i(t)−

(s_i−

s_i(t−

1)))≤

e_i; and

in response to e_i(t−

1)+(p_i(t)−

l_i(t)−

(s_i−

s_i(t−

1)))≤

e_i, setting;

y_i(t)=p_i(t)−

l_i(t)−

(s_i−

s_i(t−

1)),

o_i^s(t)=0,

o_i^e(t)=0,

o_i^p(t)=0, and

Δ

p_i(t)=0,

in which;

v_i( ) represents a charge amount from a pro PV to a pro battery;

l_i( ) represents a load at one of the prosumers;

s_i( ) represents an energy level of a pro battery at t;

t−

1 represents a previous time interval;

x_i( ) represents a discharge amount from one or more EVs;

y_i( ) represents a charge amount from a pro PV of the prosumer to a connected EV;

p_i( ) represents a forecasted PV production;

^- represents a maximum capacity of a parameter;

o_i^s( ) represents discharge output from one or more pro batteries to the electrical grid;

o_i^p( ) represents discharge output from one or more of the pro PVs to the electrical grid;

o_i^e( ) represents a discharge output from one or more of the EVs associated with the prosumer to the electrical grid;

Δ

p_i( ) represents a curtailed amount of PV generation; and

e_i( ) represents energy levels of an EV.

15. The non-transitory computer-readable medium of claim 14, wherein the adjusting the energy loads and the energy production of the one or more prosumers includes:

in response to e_i(t−

1)+(p_i(t)−

l_i(t)−

(s_i−

s_i(t−

1)))>

e_i

setting y_i(t)=e_i−

e_i(t−

1);

determining whether p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1)−

l_i (t)≤

o_i^p;

in response to p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)≤

o_i^p, setting;

Δ

p_i(t)=0,

o_i^s(t)=0,

o_i^e(t)=0, and

o_i^p(t)=p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1)−

l_i(t);

in response to p_i(t)−

(s_i−

s_i (t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)>

o_i^p;

setting o_i^p(t)=0; and

determining whether

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p≤

o_i^s;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p≤

o_i^s, setting;

o_i^s(t)=p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p,

v_i(t)←

v_i(t)+o_i^s(t), and

o_i^e(t)=0,Δ

p_i(t)=0;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p<

o_i^s;

setting;

o_i^s(t)=o_i^s, and

v_i(t)←

v_i(t)+o_i^s; and

determining whether

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s≤

o_i^e;

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s≤

o_i^e,

setting;

o_i^e(t)=

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s, and

y_i(t)←

y_i(t)+o_i^e(t),Δ

p_i(t)=0; and

in response to

p_i(t)−

(s_i−

s_i(t−

1))−

(e_i−

e_i(t−

1))−

l_i(t)−

o_i^p−

o_i^s>

o_i^e, and

setting;

o_i^e(t)=o_i^s,y_i(t)←

y_i(t)+o_i^e, and

Δ

p_i(t)=

p_i( )−

(s_i−

s_i(t−

1))−

(e_i−

e_i)(t−

1))−

l_i(t)−

o_i^p−

o_i^s−

o_i^e.

16. The non-transitory computer-readable medium of claim 15, wherein the adjusting the energy loads and the energy production of the one or more prosumers includes:

in response to p_i(t)<

l_i(t);

setting;

z_i(t)=p_i(t),

Δ

p_i(t)=0,

o_i^s(t)=0,

o_i^e(t)=0,

o_i^p(t)=0,

v_i(t)=0, and

y_i(t)=0; and

determining whether l_i(t)−

p_i(t)≥

s_i(t−

1);

in response to

l_i(t)−

p_i(t)<

s_i(t−

1), setting;

u_i(t)=l_i(t)−

p_i(t), and

x_i(t)=0;

in response to l_i(t)−

p_i(t)≥

s_i(t−

1),

setting u_i(t)=s_i(t−

1);

determining whether l_i(t)−

p_i(t)−

s_i(t−

1)≥

e_i(t−

1);

in response to l_i(t)−

p_i(t)−

s_i(t−

1)≥

e_i(t−

1), setting

x_i(t)=e_i(t−

1);

in response to

l_i(t)−

p_i(t)−

s_i(t−

1)<

e_i(t−

1), setting

x_i(t)=l_i(t)−

p_i(t)−

s_i(t−

1).

17. The non-transitory computer-readable medium of claim 13, wherein:

the control variable values include;

initial charge levels of supply-side batteries of the supply side of the VPP {b₁(0), b₂ (0), . . . , b_J(0)};

forecasted renewable generation for photovoltaic cells of the supply side of the VPP (supply PVs) {r₁(t), r₂ (t), . . . , r_N(t)};

forecasted wind generation for wind turbines of the supply side of the VPP {w₁(t), w₂(t), . . . , w_H(t)}; and

forecasted loads for prosumers {l₁(t), l2(t), . . . , l_M(t)}; and

an adjusted value for □

p_i(t), u_i(t), v_i(t), x_i(t), y_i(t), z_i(t), o_i^s(t), o_i^e(t), and o_i^p(t); and

adjusting energy supplied from the supply side of the VPP includes;

receiving the control variable values as inputs; and

generating adjusted values for;

a charge amount from a supply PV to a supply-side battery (q_i(t));

a curtailment amount of PV generation (Δ

r_g(t));

a charge amount from a wind turbine to a supply-side battery (ω

_k(t));

a curtailment amount of wind generation (Δ

w_k(t));

a discharge amount from a supply-side battery to loads (ƒ

_j(t)); and

energy sent from the electrical grid to a load at a prosumer (o_i^d(t)),

in which;

H represents the number of wind turbines in the supply side;

N represents the number of supply PVs in the supply side;

J represents the number of supply-side batteries;

k represents an indexing variable for the wind turbines with a range from 1 to H;

j represents an indexing variable for the supply-side batteries with a range from 1 to J;

i represents an indexing variable for the supply PVs with a range from 1 to N.

18. The non-transitory computer-readable medium of claim 17, wherein adjusting energy supplied from the supply side of the VPP includes:

initializing ƒ

_j(t), g_i(t), and Δ

l_i(t) to be zero;

defining Δ

d_i(t)=l_i(t)−

u₁(t)−

x_i(t)−

z_i(t) and Δ

o_i=o_i^s(t)+o_i^e(t)+o_i^p(t), based on the results from the adjusting energy loads and energy production of one or more prosumers of the VPP;

determining whether Σ

_l=1^Nr_i(t)+Σ

_k=1^Hw_k(t)≥

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t);

in response to Σ

_l=1^Nr_i(t)+Σ

_k=1^Hw_k(t)≥

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t);

setting;

F*(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t),

o_i^d(t)=Δ

d_i, and

G(t)=0;

deciding ƒ

*_j(t) based on F*(t);

determining whether b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)−

ƒ

*_j(t)≤

b_j;

in response to b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)−

ƒ

*_i(t)≤

b_j;

setting q_i(t)=r_i(t), Δ

r_i(t)=0;

determining whether b_j(t−

1)+Σ

_i=1<sup>β

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)≤

b_j;

in response to b_j(t−

1)+Σ

_i=1<sup>β

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)≤

b_j, setting

ω

_k(t)=w_k(t),Δ

w_k(t)=0;

in response to

b_j(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)>

b_j;

setting;

Σ

_k=1<sup>β

j</sup>ω

_k(t)=b_j−

b_j(t−

1)−

Σ

_i=1<sup>γ

j</sup>r_i(t)+ƒ

*_j(t), and

Σ

_k=1<sup>β

j</sup>Δ

w_k(t)=Σ

_k=1<sup>β

j</sup>w_k(t)−

b_j−

b_j(t−

1)−

Σ

_i=1<sup>γ

j</sup>r_i(t)+ƒ

*_j(t)); and

calculating ω

*_i(t) based on

Σ

_k=1<sup>β

j</sup>ω

_k(t)=b_j−

b_j(t−

1)−

Σ

_i=1<sup>γ

j</sup>r_i(t)+ƒ

*_j(t);

in response to

b_l(t−

1)+Σ

_i=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)−

ƒ

*_j(t)>

bdj;

setting;

ρ

_i=1<sup>γ

j</sup>q_i(t)=b_j−

b_j(t−

1)+ƒ

*_j(t),

Σ

_i=1<sup>γ

j</sup>Δ

r_i(t)=Σ

_i=1<sup>γ

j</sup>r_i(t)−

b_j−

b_j(t−

1)+ƒ

*_j(t)), and

ω

_k(t)=0,Δ

w_k(t)=w_k(t); and

calculating q*_i(t) based on Σ

_i=1<sup>γ

j</sup>q_i(t)=b_j−

b_j(t−

1)+ƒ

*_j(t).

19. The non-transitory computer-readable medium of claim 18, wherein adjusting energy supplied from the supply side of the VPP includes:

in response to Σ

_l=1r_i(t)+Σ

_k=1^Hw_k(t)≤

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t);

setting;

q_i(t)=r_i(t),

Δ

r_i(t)=0,

ω

_k(t)=w_k(t), and

Δ

w_k(t)=0;

determining whether

Σ

_i=1^MΔ

d_i(t)=Σ

_i=1^MΔ

o_i(t)≥

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)};

in response to Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)≥

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t)}, setting;

ƒ

_j(t)=b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t),

G(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)−

Σ

_i=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_i(t)+Σ

_k=1<sup>β

j</sup>w_k(t)},

and

o_i^d(t)=Δ

d_i(t)+Δ

l_i(t);

in response to

Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t)<

Σ

_j=1^J{b_j(t−

1)+Σ

_l=1<sup>γ

j</sup>r_l(t)+Σ

_k=1<sup>β

j</sup>w_k(t)},

setting;

F*(t)=Σ

_i=1^MΔ

d_i(t)−

Σ

_i=1^MΔ

o_i(t), and

o_i^d(t)=Δ

d_i(t),G(t)=0; and

deciding ƒ

*_j(t) based on F*(t).

20. The non-transitory computer-readable medium of claim 11, wherein:

the control variable values include;

curtailment capacity of the prosumers nodes {l₁, l₂, . . . , l_M},

discharging rates of supply-side batteries for each time interval (t) {ƒ

₁(t) ƒ

₂(t), . . . , ƒ

_J(t)}, and

updated sets of demands that are based on adjusted energy loads and energy production of the one or more prosumers of the VPP and adjusted energy supplied from the supply side of the VPP {d₁(t), d₂(t), . . . , d_M(t)}; and

the adjusting curtailment of the energy loads in the prosumers includes in response to the total demand being greater than the DR capacity, dispatching a DR event to all prosumers with a non-zero curtailment amount.