# Energy Storage Benefits Assessment Using Multiple-Choice Criteria: The Case of Drini River Cascade, Albania

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## Abstract

**:**

## 1. Introduction

## 2. Study Case

^{3}. The total head (H) of the HPP varies from 115.5 m up to 161.5 m. The specific water consumption (m

^{3}/kWh) generates 1 kWh of electricity, resulting in the range of 4.07 (Fierzë), 4.2 (Koman), and 8.59 (Vau Dejës). Based on 2010 water discharge rates of (i.e., 11,287 million m

^{3}) and specific water consumption, the potential of saving reaches around 0.8 up to 2.08 TWh of electricity, accounting for 30% of total annual electricity demand in Albania. As shown in Figure 2, considering an electricity export rate of EUR 50/MWh up to EUR 70/MWh (i.e., off-peak energy or excess), it can bring a considerable monetary benefit to KESH. Hence, electricity storage can be used to avoid congestion-related costs and charges, especially if the costs become onerous due to significant transmission system congestion. In this application service, storage systems would be installed at locations electrically downstream from the congested portion of the transmission system. Energy would be stored when there is no transmission congestion. It would be released (i.e., during on-peak demand periods) to reduce peak transmission capacity requirements.

## 3. Methodology

_{1}, S

_{2}, and S

_{3}represent the average feasibility scores and “n” is their number. The main difference between the two methods is that lower numbers have a higher impact on reducing the geometric mean than the arithmetic mean. For example, a single “zero” result may lower the arithmetic mean slightly, but the geometric mean leads to zero. When a storage option calculates zero points for any of the feasibility criteria, then this means that the ESS cannot provide the list of services; therefore, it may not be an acceptable technical solution, and this shortcoming should be reflected in the combined feasibility score. As a result, the geometric mean is preferred for combining multiple feasibility results. ES-Select uses the following geometric mean Equation, Equation (3) [7].

_{1}, b is the weight of the result S

_{2}, and c is the weight of the result S

_{3}.

#### Economic Analysis

**Cost-benefit analysis:**A period is chosen, and the sum of all costs and benefits is determined. The net benefit is determined by subtracting total benefits and total costs, as shown in Equation (4).

**Benefit to cost ratio (BCR):**A period is chosen then the sum of all costs and benefits in that period is determined. The ratio of benefit to cost gives the benefit to cost ratio, as shown in Equation (5).

**Simple payback period (SPB):**This indicator represents one of the most common ways of finding the economic value of an energy project. Payback considers the initial investment costs and the resulting annual cash flow. The payback period represents the time needed to recoup the initial investment, as shown in Equation (6).

**Initial rate of return:**This is the opposite of a simple payback period, as shown in Equation (7).

**Levelized cost of energy (LCOE):**All the costs are added during a selected period divided by units of energy. Firstly, a net present value (NPV) analysis is performed. For the value of the chosen LCOE, the project’s NPV becomes zero. This means that the LCOE is the minimum price for energy to be sold for an energy project to break even, as shown in Equation (8).

**Cash flow analysis:**One of the most flexible and powerful ways to analyze an energy investment is cash-flow analysis. This technique easily complicates fuel escalation, tax-deductible interest, depreciation, periodic maintenance costs, and disposal or value of the equipment’s salvage at the end of its lifetime. The results of a cash flow analysis are computed numerically using a spreadsheet rather than increasingly complex formulas to characterize these factors, as shown in Equation (9).

**Discounted cash flow (DCF**): DCF considers future free cash flow projections and discounts them to reach a present value, then evaluates investment feasibility. Suppose the value obtained through DCF analysis is higher than the current investment cost. In that case, the opportunity may be a good one. DCF analysis aims to estimate the money one would receive from an investment and adjust for money’s time value, as shown in Equation (10).

^{n}. The value chosen for r shows that it “weights” the decision towards one option, so the basis for choosing the discount rate value must be carefully evaluated. The discount rate depends on the cost of capital, including the balance between debt-financing and equity financing. An assessment of the financial risk must be applied.

**Net present value (NPV):**NPV compares the value of, e.g., a dollar today to the value of that same dollar in the future, considering the inflation and returns into account. If the NPV of a prospective project is positive, then that project’s investment is considered feasible. In contrast, if NPV is negative, the project should be rejected because cash flows will also be negative. To calculate NPV, the project period and the sum of all the discounted cash flows should be chosen. The net present value is computed by taking the first annual payment and dividing it by (1 + r). The next payment is then divided by (1 + r)

^{2}, the third payment by (1 + r)

^{3}, and the n

^{th}payment by (1 + r)

^{n}, as given in Equation (11).

_{1}, P

_{2}, P

_{3}… P

_{n}represents net cash inflow–outflows during a single period n, r—represents the discount rate of return made on another investment, and n—represents the number of years or a given period.

## 4. Results

## 5. Discussion

## 6. Conclusions

## Supplementary Materials

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Abbreviations

ALCM | Application, Location, Cost and Maturity |

ESS | Energy Storage System |

CAES | Compressed Air Energy System |

PHES | Pump Hydro Energy Storage |

RES | Renewable Energy Storage |

T&D | Transmission & Distribution |

MES | Multi-Energy Systems |

DMG | Distributed Multi-Generation |

VPP | Virtual Power Plants |

PV | Photovoltaic |

HPP | Hydro Power Plant |

CAES-c | Compressed Air Energy System of Cavern |

LMP | Locational Marginal Pricing |

KESH | Korporata Electro Energjitike Shqiptare |

LCOE | Levelized Cost of Energy |

NPV | Net Present Value |

DCF | Discounted Cash Flow |

SPP | Simple Payback Period |

dod | Depth of Discharge |

IRENA | International Renewable Energy Agency |

IEA | International Energy Agency |

App | Application |

TCR | Transmission Congestion Relief |

ETSH | Energy Time Shift |

TUD | Transmission Upgrade Deferral |

SES | Solar Energy Smoothing |

SESTSH | Solar Energy Time Shift |

WETSH | Wind Energy Time Shift |

H. E | Heat Exchangers |

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**Figure 2.**Level of potential financial losses (EUR/year) in the Drin River cascade, during 2002–2018.

**Figure 3.**Overview of ES-Select™ design and functionalities adapted after KEMA [7].

**Figure 4.**Computation process for the total feasibility score of each storage option after KEMA [7].

**Figure 5.**Analysis of the feasibility scores (%) of different ESSs applicable at central or bulk storage for a weight factor of 1, considering the four categories of the chosen criteria (ALCM) and total installation cost (USD/kW) or (USD/kWh).

**Figure 6.**Analysis of total scores meeting only application requirements from different ESS applicable at central or bulk storage for a weight factor of 1.

**Figure 7.**Analysis of overall feasibility scores for different ESS applied at central or bulk generation level (%) meeting application requirement, ALCM criteria, and total installation cost (USD/kW or USD/kWh) for a weight factor of 1.0.

**Figure 8.**Energy efficiency (%) of different ESSs as a function of installation cost (USD/kW) at the selected location.

**Figure 9.**Lifetime throughput Energy at 80% dod (MWh/kW) as a function of efficiency (%) for different types of ESSs.

**Figure 10.**Lifetime throughput Energy at 10% dod (MWh/kW) as a function of energy efficiency (%) for different ESS.

**Figure 11.**Annual maintenance costs or warranty for various ESSs (USD/kW) or (USD/year/kW) as a function of total installation cost (USD/kW) at the selected location.

**Figure 12.**Net Present Value (USD/kW) as a function of the AC equipment cost (USD/kW) for the selected applications list.

**Figure 15.**The total market potential benefit in 10 years (USD billion) as a function of the application list (App1–App6) and a discount rate of 5% up to11%.

**Figure 16.**Net Present Value (USD/kW) at a range of electricity purchasing prices (USD 30–50/MWh) and a discount rate of 11%.

Grid Application | Services |
---|---|

Application#1 | Transmission and Congestion Relief |

Application#2 | Transmission Upgrade Deferral at 10% |

Application#3 | Energy Time Shift (Arbitrage) |

Application#4 | Solar Energy Time Shift |

Application#5 | Wind Energy Time Shift |

Application#6 | Solar Energy Smoothing |

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**MDPI and ACS Style**

Malka, L.; Daci, A.; Kuriqi, A.; Bartocci, P.; Rrapaj, E.
Energy Storage Benefits Assessment Using Multiple-Choice Criteria: The Case of Drini River Cascade, Albania. *Energies* **2022**, *15*, 4032.
https://doi.org/10.3390/en15114032

**AMA Style**

Malka L, Daci A, Kuriqi A, Bartocci P, Rrapaj E.
Energy Storage Benefits Assessment Using Multiple-Choice Criteria: The Case of Drini River Cascade, Albania. *Energies*. 2022; 15(11):4032.
https://doi.org/10.3390/en15114032

**Chicago/Turabian Style**

Malka, Lorenc, Alfred Daci, Alban Kuriqi, Pietro Bartocci, and Ermonela Rrapaj.
2022. "Energy Storage Benefits Assessment Using Multiple-Choice Criteria: The Case of Drini River Cascade, Albania" *Energies* 15, no. 11: 4032.
https://doi.org/10.3390/en15114032