# Demand-Side Flexibility Impact on Prosumer Energy System Planning

^{*}

## Abstract

**:**

## 1. Introduction

- (a)
- The planning/dimensioning problem, which represents an optimal rated power split of different renewable sources and storage capacities within prosumer systems, resulting from a multicriteria decision making process against complex objectives combining maximization of economic performance, environmental neutrality, and independence from the power grid.
- (b)
- The operation problem, which focuses on optimal energy management strategy for a given prosumer and its energy assets. Moreover, it considers optimization of prosumer’s energy imports and exports as well as internal power flows between multiple renewable/conventional energy sources and storages against multiple technological, economic, and environmental criteria.

## 2. Proposed Planning Methodology

**1st.**The overall HRES planning process considers simultaneously both electric and thermal energy demand, while current approaches typically consider electric or thermal domain, exclusively, with the methods for such optimizations previously discussed in [19]. Employed methodologies therein are focused on balancing the selected demand type with available energy sources, conversion elements, and storages. However, increased utilization of devices like heat pumps, which satisfy the thermal demand while contributing to electricity demand, requires a holistic assessment approach. The differences between the traditional approach and the one proposed by this paper is illustrated in Figure 1.

**2nd.**The most utilized approach to consider isolated (island) HRES deployment scenarios is extended towards consideration of grid-tied deployment, which brings a more dynamic context where varying import and export energy prices are applied and unlimited energy exchange with power grid is enabled.

**3rd.**The increasing application of DSM programs and, more specifically, DR schemes in day-to-day operation is considered on an appliance level and corresponding implications on the planning of HRES and dimensioning of individual components are evaluated.

**4th.**MCDMA is employed to rank feasible HRES topologies with capabilities of simultaneously evaluating a wide range of technical, economic, environmental, and societal design criteria.

- Renewable energy sources (RES) harvesting potential (solar irradiation data, wind data, ambient temperature, ground temperatures);
- Building characteristics and space availability constraints (indoor area (basement), outdoor area, roof, wall facades, surrounding area);
- Energy demand requirements and flexibility (electricity demand, heating/cooling demand, hot water demand);
- Dynamic energy pricing (dynamic import/export energy prices, feed-in tariffs);
- Financing conditions (budget/loan, cost of capital, governmental incentives, inflation, increase of energy prices);
- RET equipment characteristics (photovoltaic panel, wind turbine, solar collector, geothermal heat pump, auxiliaries (DC/DC, DC/AC), battery storage, boiler);
- RET installation parameters (wind turbine installation height, azimuth and elevation of photovoltaic panels, etc.)

#### 2.1. Operation Optimization

#### 2.2. Sizing Optimization

- Technical criteria: Loss of Power Supply Probability (LPSP), Wasted energy
- Financial criteria: Capital Expenditure (CAPEX), Operational Expenditure (OPEX), Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PP)
- Environmental criteria: greenhouse gas emissions (CO${}_{2}$, NOx, SOx)
- Social/Economic/Political criteria: Fuel Reserve Years, Job creation, Inter-country energy dependence etc.

## 3. Mathematical Model

#### 3.1. Operation Optimization

#### 3.1.1. Energy Balance

#### 3.1.2. DSM and Load Variables

#### 3.1.3. Auxiliary Constraints

#### 3.1.4. Variable Bounds

#### 3.2. Objective Function

#### 3.2.1. Cost Minimization

#### 3.2.2. Dispersion Minimization

#### 3.3. Sizing Optimization

#### 3.3.1. Total Cost (EMI)

#### 3.3.2. Net-Zero Energy Building Rating

#### 3.3.3. CO_{2} Emissions

## 4. Use Case

#### 4.1. Energy Hub Model

#### 4.2. Tariff Information

#### 4.3. Baseline Consumption

#### 4.4. Renewable Technologies

#### 4.5. Objective Function Parameters

#### 4.6. Available Configurations

## 5. Results

#### 5.1. Total Cost as the Only Criterion

#### 5.2. Total Cost as the Primary Criterion

#### 5.3. NZEB Rating as the Primary Criterion

#### 5.4. CO_{2} Emissions as the Primary Criterion

#### 5.5. Use Case without Incentives

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Appendix A. Modeling Renewable Technologies

#### Appendix A.1. Wind Turbine

#### Appendix A.2. Photovoltaic Panels

#### Appendix A.3. Solar Thermal Collector

#### Appendix A.4. Ground Source Heat Pump

Coefficients | Cooling | Heating | |
---|---|---|---|

COP | ${k}_{0}$ | $1.5311\times {10}^{0}$ | $1.0000\times {10}^{0}$ |

${k}_{1}$ | $-2.2961\times {10}^{-2}$ | $1.5598\times {10}^{-2}$ | |

${k}_{2}$ | $6.8744\times {10}^{-5}$ | $-1.5931\times {10}^{-4}$ | |

Capacity | ${\lambda}_{0}$ | $1.4119\times {10}^{0}$ | $6.6787\times {10}^{-1}$ |

${\lambda}_{1}$ | $-2.5620\times {10}^{-3}$ | $2.7989\times {10}^{-2}$ | |

${\lambda}_{2}$ | $-7.2482\times {10}^{-5}$ | $-1.0636\times {10}^{-4}$ |

## Appendix B. Nomenclature

#### Appendix B.1. Proposed Planning Methodology

${a}_{i}$ | i-th alternative in the MCDMA |

${c}_{k}\left({a}_{i}\right)$ | k-th criterion out of q for ${a}_{k}$ |

${d}_{k}({a}_{i},{a}_{j})$ | pair-wise comparison value for criterion ${c}_{k}$ |

${\pi}_{k}\left(({a}_{i},{a}_{j})\right)$ | preference degree function |

${P}_{k}({a}_{i},{a}_{j})$ | preference function |

${p}_{k}$, ${q}_{k}$ | lower and upper preference boundaries |

${w}_{k}$ | weight associated with criterion ${c}_{k}$ |

${\varphi}^{+}$, ${\varphi}^{-}$, $\varphi $ | positive, negative and net preference flow |

$\mathrm{WT}$ | wind turbine |

${P}_{\mathrm{WT}}^{\mathrm{test}}\left({v}_{\mathrm{v}}\right)$ | nominal power-wind speed WT power curve |

${Y}_{\mathrm{WT}}$ | rated power (power capacity) of the WT system |

${P}_{\mathrm{WT}}\left({v}_{\mathrm{v}}\right)$ | capacity and air density adjusted power-wind speed WT power curve |

$\rho $, ${\rho}_{0}$ | air density at site and at test conditions |

B | laps rate |

${T}_{0}$ | standard temperature |

g | gravitational acceleration |

R | universal gas constant divided by the molar mass of air |

${z}_{\mathrm{hub}}^{\mathrm{abs}}$ | WT hub height above sea level |

${z}_{\mathrm{anem}/\mathrm{hub}}$ | anemometer and WT hub height above ground |

${v}_{\mathrm{anem}/\mathrm{hub}}$ | wind speed at anemometer and WT hub height |

${z}_{0}$ | surface roughness level |

$PV$ | photovoltaic |

${P}_{\mathrm{PV}}$ | instantaneous power generated by the PV system |

${Y}_{\mathrm{PV}}$ | rated power (power capacity) of the PV system |

${f}_{\mathrm{PV}}$ | derating factor of the PV system |

${\overline{G}}_{T}$ | solar irradiance incident on the PV array averaged at the current timestamp |

${a}_{P}$ | temperature coefficient of power |

${T}_{\mathrm{c}}$ | PV cell temperature |

$\mathrm{STC}$ | (at) standard test conditions |

${\overline{G}}_{\mathrm{d}/\mathrm{b}}$, G | diffuse, beam and global horizontal irradiation |

${A}_{\mathrm{i}}$ | anisotropy index |

${R}_{\mathrm{b}}$ | ratio between beam radiation on a tilted and horizontal surface |

f | horizontal brightening factor |

$\beta $ | PV surface slope |

${\rho}_{\mathrm{g}}$ | ground reflectance (albedo) |

${T}_{\mathrm{a}}$ | ambient temperature |

$\mathrm{NOCT}$ | (at) nominal operating cell temperature |

${\eta}_{\mathrm{mp}}$ | maximum power point efficiency |

${A}_{\mathrm{PV}}$ | surface area of the PV array |

a | solar absorbance of the PV array cover |

$\tau $ | solar transmittance of the PV array cover |

$STC$ | solat thermal collector |

${Q}_{\mathrm{tank}/\mathrm{loss}}$ | available amount of heat in the tank and lost amount of heat |

${T}_{\mathrm{tank}/\mathrm{amb}}$ | water temperature in the tank and ambient temperature |

m | mass of water in the tank |

c | specific heat capacity of water |

${\eta}_{\mathrm{l}}$ | storage heat loss coefficient per unit of volume |

${T}_{\mathrm{s}}$ | sample rate |

${Q}_{\mathrm{prod}/\mathrm{avail}}$ | produced amount of heat and available amount of heat in the tank |

$\mathrm{GSHP}$ | ground source heat pump |

${T}_{\mathrm{g}}$ | ground temperature |

${\overline{T}}_{g}$ | mean annual soil temperature |

${A}_{\mathrm{s}}$ | annual surface temperature amplitude |

${X}_{\mathrm{s}}$ | soil depth |

$\alpha $ | soil thermal diffusivity |

k | soil thermal conductivity |

$\rho $ | soil density |

${c}_{p}$ | soil specific heat |

t | day of the year |

${T}_{\mathrm{ewt}}$ | entering water temperature |

${T}_{\mathrm{d}}$ | cooling/heating averaged design temperature |

${T}_{\mathrm{bin}}$ | binned ambient temperature |

$\chi $ | capacity multiplier |

${q}_{\mathrm{c}}/\mathrm{d}$ | cooling/heating demand |

$\eta $, ${\eta}_{\mathrm{base}}$ | instantaneous coefficient of performance (COP) and at baseline |

${P}_{\mathrm{max}}$ | maximum design power |

${E}_{\mathrm{elec},\mathrm{GSHP}}$ | electric energy consumed by GSHP |

#### Appendix B.2. Mathematical model

${P}_{\mathrm{in}}$ | input (imported) power |

${P}_{\mathrm{cin}/\mathrm{cout}}$ | input and output power to and from the converters |

${Q}_{\mathrm{in}/\mathrm{out}}$ | power flow to/from the storage at the input and output stage |

L | loads |

${P}_{\mathrm{out}}$ | output power to loads |

${P}_{\mathrm{exp}}$ | exported power |

${q}_{\mathrm{in}/\mathrm{out}}$ | charge/discharge rate for storage at the input and output stages |

${E}_{\mathrm{in}/\mathrm{out}}$ | available energy (state of charge, SOC) for storage at the input and output stages |

y, z | device on/off and device start indicators |

${d}^{+/-}$ | positive and negative power deviations |

$I\left({d}^{+/-}\right)$ | indicators for positive and negative power deviations |

${S}_{\mathrm{in}/\mathrm{qin}}$ | input stage energy storage conversion matrices |

${F}_{\mathrm{in}/\mathrm{qin}}$ | input and output transformation matrices |

C | energy conversion matrix |

${D}_{\mathrm{exp}}$, ${R}_{\mathrm{exp}}$ | export energy restriction matrices |

${S}_{\mathrm{out}/\mathrm{qout}}$ | output stage energy storage conversion matrices |

${P}_{i}$, ${P}_{i}^{\mathrm{nom}}$ | i-th appliance’s instantaneous and nominal power draw |

${w}_{i}^{\mathrm{nom}},\Delta {t}_{i}^{\mathrm{nom}}$ | i-th appliance’s n-th activation window indicator and length |

${P}_{\mathrm{dev}+/{-}_{i}}^{\mathrm{max}}$ | maximum absolute positive and negative power deviations |

${P}_{\mathrm{renew}}$ | power produced from renewable sources |

$SO{C}_{\mathrm{in}/\mathrm{out}}^{\mathrm{min}/\mathrm{max}}$ | SOC capaciti limits at input and output stages |

${J}_{\mathrm{c}/\mathrm{d}/\mathrm{cd}}$ | cost, dispersion and mixed criterion |

$\alpha $, $\beta $, $\sigma $ | energy import and export prices and standing charge |

${\zeta}_{i}$ | i-th appliance dispersion penalization factor |

${X}_{i}^{\mathrm{EMI}/\mathrm{maint}}$ | equated monthly installments and maintenance costs |

${\gamma}_{i}$ | estimated lifetime in years for i-th device |

$\delta $ | monthly discount rate |

${B}_{i}$ | initial acquisition cost for i-th device |

${C}_{\mathrm{C}/\mathrm{NZEB}/{\mathrm{CO}}_{2}}$ | cost, net-zero energy building (NZEB) and CO_{2} emission criterion |

${f}_{\mathrm{WT}/\mathrm{PV}/\mathrm{grid}}^{C}$ | carbon footprint values for WT, PV and grid imported energy |

#### Appendix B.3. Use Case

${Q}_{\mathrm{heat}/\mathrm{DHW}}$ | baseline thermal energy requirements for heating and domestic hot water (DHW) |

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**Figure 4.**Considered building and corresponding installations. (

**a**) Property. (

**b**) STC and PV installations.

**Figure 6.**Normalized thermal and electricity usage profiles. (

**a**) Thermal usage. (

**b**) Electricity usage.

**Figure 9.**Single appliance and total load optimization examples. (

**a**) Example appliance (EV). (

**b**) Total load.

Appliance | ${\mathit{P}}_{\mathit{i}}^{\mathbf{nom}}$ [kW] | Nominal Usage | Shifting Windows |
---|---|---|---|

20:00–22:00 TUE | 18:00 TUE–16:00 WED | ||

Washing machine | 800 | 20:00–22:00 THU | 18:00 THU–16:00 FRI |

19:00–22:00 SAT | 18:00 SAT–16:00 SUN | ||

22:00–24:00 TUE | 20:00 TUE–18:00 WED | ||

Clothes dryer | 3000 | 22:00–24:00 THU | 20:00 THU–18:00 FRI |

20:00–24:00 SAT | 20:00 SAT–18:00 SUN | ||

08:00–09:00 WED | 08:00–16:00 WED | ||

Electric iron | 1200 | 08:00–09:00 FRI | 08:00–16:00 FRI |

19:00–21:00 SUN | 10:00–22:00 SUN | ||

Stove/oven | 1500 | 10:00–11:00, 18:00–19:00 workdays | 10:00–12:00, 17:00–19:00 workdays |

10:00–11:00, 16:00–18:00 weekends | 09:00–12:00, 15:00–19:00 weekends | ||

Dishwasher | 1000 | 20:00–22:00 every day | 19:00–16:00 (next day) every day |

Vacuum cleaner | 1200 | 11:00–12:00 TUE | 09:00–16:00 TUE |

11:00–13:00 SUN | 09:00–16:00 SUN | ||

Electric vehicle | 4800 | 18:00–02:00 (next day) every day | 18:00–08:00 (next day) every day |

Label | Value | Label | Value | Label | Value | Label | Value |
---|---|---|---|---|---|---|---|

B | $0.0065\mathrm{K}/\mathrm{m}$ | ${z}_{\mathrm{hub}}^{\mathrm{abs}}$ | $113\mathrm{m}$ | ${f}_{\mathrm{PV}}$ | 80% | ${G}_{\mathrm{T},\mathrm{STC}}$ | $1\mathrm{kW}/{\mathrm{m}}^{2}$ |

${T}_{0}$ | $288.16\mathrm{K}$ | ${z}_{\mathrm{anem}}$ | $10\mathrm{m}$ | ${a}_{P}$ | −0.45%/${}^{\circ}$C | ${G}_{\mathrm{T},\mathrm{NOCT}}$ | $0.8\mathrm{kW}/{\mathrm{m}}^{2}$ |

g | $9.81\mathrm{m}/{\mathrm{s}}^{2}$ | ${z}_{\mathrm{hub}}$ | $15\mathrm{m}$ | ${T}_{\mathrm{c},\mathrm{STC}}$ | $25{}^{\circ}\mathrm{C}$ | ${A}_{\mathrm{PV}}$ | $1.63{\mathrm{m}}^{2}$ |

R | $287J/(\mathrm{kg}\xb7\mathrm{K})$ | ${z}_{0}$ | $0.01\mathrm{m}$ | ${T}_{\mathrm{a},\mathrm{NOCT}}$ | $20{}^{\circ}\mathrm{C}$ | $\beta $ | $\mathrm{\xdf}/4$ |

a | $9$ | $\tau $ | $0.1$ | ||||

${\rho}_{g}$ | $0.2$ | ||||||

k | $1.2\mathrm{W}/(\mathrm{m}\xb7\mathrm{K})$ | ${\eta}_{\mathrm{base}}$ | $4$ | m | $182\mathrm{kg}$ | A | $5.32{\mathrm{m}}^{2}$ |

$\rho $ | $1.45\mathrm{g}/\mathrm{c}{\mathrm{m}}^{3}$ | ${T}_{\mathrm{g}}$ | $10{}^{\circ}\mathrm{C}$ | ${\eta}_{l}$ | $1.698\mathrm{J}/{\mathrm{K}}^{2}$ | ${T}_{\mathrm{base}}$ | $10{}^{\circ}\mathrm{C}$ |

${T}_{\mathrm{d},\mathrm{cool}}$ | $-7{}^{\circ}\mathrm{C}$ | ${X}_{\mathrm{S}}$ | $100\mathrm{m}$ | ||||

${T}_{\mathrm{d},\mathrm{heat}}$ | $37{}^{\circ}\mathrm{C}$ | ${c}_{p}$ | $1\mathrm{kJ}/(\mathrm{kg}\xb7\mathrm{K})$ | ||||

${A}_{\mathrm{s}}$ | $15{\mathrm{m}}^{2}$ | ${P}_{\mathrm{nom}}$ | $13\mathrm{kW}$ |

${\mathit{Y}}_{\mathbf{WT}}$ [kW] | B [kEUR] | $\mathit{\gamma}$ [a] | ${\mathit{Y}}_{\mathbf{PV}}$ [kW] | B [kEUR] | $\mathit{\gamma}$ [a] | ${\mathit{SOC}}_{\mathbf{out}}^{\mathbf{max}}$ [kWh] | ${\mathit{Q}}_{\mathbf{out}}^{\mathbf{max}}$ [kW] | B [kEUR] | $\mathit{\gamma}$ [a] |
---|---|---|---|---|---|---|---|---|---|

0.0 | 0.0 | 20 | 0 | 0.00 | 20 | 0 | 0.0 | 0.000 | 10 |

2.5 | 11.4 | 20 | 2 | 3.88 | 20 | 2 | 3.0 | 3.615 | 10 |

5.0 | 22.3 | 20 | 4 | 6.35 | 20 | 4 | 4.2 | 4.910 | 10 |

7.5 | 33.2 | 20 | 6 | 9.53 | 20 | 6 | 5.0 | 5.870 | 10 |

10.0 | 44.1 | 20 | 8 | 12.70 | 20 |

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. |
---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | Base. [%] |

0 | 0 | 2.5 | 4407.6 | 14,198.2 | 5612.2 | 2.70 |

0 | 0 | 5.0 | 4430.2 | 7637.0 | 5187.8 | 2.20 |

0 | 0 | 7.5 | 4544.8 | 1075.7 | 4909.3 | $-0.33$ |

0 | 0 | 0 | 4587.3 | 20,759.4 | 6435.4 | $-1.26$ |

0 | 2 | 2.5 | 4682.2 | 12,972.9 | 5548.5 | $-3.36$ |

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. | Savings vs. |
---|---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | DSM off [%] | Base. [%] |

0 | 0 | 5.0 | 3987.5 | 7634.0 | 4486.6 | 9.99 | 11.98 |

0 | 0 | 7.5 | 4021.5 | 1072.7 | 4080.4 | 11.51 | 11.23 |

0 | 0 | 2.5 | 4144.2 | 14,195.2 | 5194.9 | 5.98 | 8.52 |

0 | 0 | 10.0 | 4210.7 | $-5488.5$ | 3920.0 | 11.47 | 7.04 |

0 | 2 | 5.0 | 4227.6 | 6408.7 | 4368.3 | 10.42 | 6.68 |

3 | 0 | 5.0 | 4235.8 | 7633.2 | 4036.5 | 11.25 | 6.50 |

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. | Savings vs. |
---|---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | DSM off [%] | Base. [%] |

0 | 0 | 7.5 | 4021.5 | 1072.7 | 4080.4 | 11.51 | 11.23 |

0 | 0 | 10.0 | 4210.7 | $-5488.5$ | 3920.0 | 11.47 | 7.04 |

0 | 0 | 5.0 | 3987.5 | 7634.0 | 4486.6 | 9.99 | 11.98 |

3 | 0 | 7.5 | 4021.5 | 1072.7 | 4080.4 | 11.51 | 11.23 |

0 | 2 | 7.5 | 4281.2 | $-152.5$ | 3993.1 | 11.55 | 5.49 |

**Table 7.**List of five best configurations when primarily focusing on NZEB rating with DSM turned on.

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. | Savings vs. |
---|---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | DSM off [%] | Base. [%] |

0 | 4 | 10.0 | 4623.8 | $-7939.0$ | 3803.4 | 11.43 | $-2.13$ |

0 | 6 | 10.0 | 4850.9 | $-9164.3$ | 3769.6 | 11.30 | $-7.08$ |

0 | 8 | 10.0 | 5079.6 | $-10,389.6$ | 3744.9 | 11.13 | $-12.13$ |

0 | 0 | 10.0 | 4210.7 | $-5488.5$ | 3920.0 | 11.47 | 7.05 |

0 | 2 | 10.0 | 4482.6 | $-6713.8$ | 3852.0 | 11.33 | 1.04 |

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. | Savings vs. |
---|---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | DSM off [%] | Base. [%] |

9 | 0 | 7.5 | 4490.8 | 1072.0 | 3454.3 | 9.18 | 0.87 |

6 | 0 | 7.5 | 4409.4 | 1072.0 | 3549.3 | 10.54 | 2.66 |

9 | 4 | 7.5 | 4814.0 | $-1379.6$ | 3190.5 | 9.85 | $-6.27$ |

9 | 0 | 10.0 | 4723.1 | $-5489.3$ | 3362.2 | 8.67 | $-4.26$ |

3 | 0 | 7.5 | 4296.9 | 1072.0 | 3673.2 | 12.03 | 5.14 |

**Table 9.**List of five best configurations when optimizing solely for costs without any incentives and with DSM turned on.

BESS | PV | WT | Total Cost | NZEB Rat. | CO${}_{2}$ | Savings vs. | Savings vs. |
---|---|---|---|---|---|---|---|

[kWh] | [kW] | [kW] | [EUR] | [kWh] | Emiss. [kg] | DSM off [%] | Base. [%] |

0 | 0 | 2.5 | 6130.7 | 14,166.2 | 5189.7 | 4.06 | $-35.33$ |

0 | 4 | 2.5 | 6422.4 | 11,715.7 | 4878.5 | 5.78 | $-41.77$ |

0 | 4 | 5.0 | 6589.2 | 7605.0 | 4478.3 | 6.25 | $-45.46$ |

9 | 0 | 2.5 | 6747.8 | 14,165.7 | 4795.0 | 2.36 | $-48.96$ |

9 | 4 | 2.5 | 6896.8 | 11,715.2 | 4256.2 | 4.09 | $-52.25$ |

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**MDPI and ACS Style**

Jelić, M.; Batić, M.; Tomašević, N. Demand-Side Flexibility Impact on Prosumer Energy System Planning. *Energies* **2021**, *14*, 7076.
https://doi.org/10.3390/en14217076

**AMA Style**

Jelić M, Batić M, Tomašević N. Demand-Side Flexibility Impact on Prosumer Energy System Planning. *Energies*. 2021; 14(21):7076.
https://doi.org/10.3390/en14217076

**Chicago/Turabian Style**

Jelić, Marko, Marko Batić, and Nikola Tomašević. 2021. "Demand-Side Flexibility Impact on Prosumer Energy System Planning" *Energies* 14, no. 21: 7076.
https://doi.org/10.3390/en14217076