# Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage

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## Abstract

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## 1. Introduction

- The problem with solar and wind power plants is that the volume of electricity generation depends significantly on weather conditions. In cloudy weather or at night, energy generation at solar power plants is significantly reduced or completely absent. This can seriously affect the network’s overall operation.
- The inclusion of generating nodes with energy storage devices in the structure of microgrids improves the efficiency of the generated power, as well as improves the reliability of consumer supply.
- An isolated microgrid mainly relies on a diesel generator or battery energy storage system to store energy.
- Storage devices, such as batteries and flywheel generators, can play an important role in maintaining the stability of the overall operation of the microgrid system.
- Energy storage systems (pump-hydro) can play a key role. When the price of electricity is low, it pumps water from downstream to upstream.
- A pumped-hydro energy storage system makes a good alternative to batteries, by storing water (energy) to cope with the intermittent nature of renewable energy sources.

^{3}water tanks with 100 m height difference, 100 Ah battery bank, and 18 kW solar PV in a 13-floor building on a Greek island, has been implemented. If micro-pump hydro-energy storage is built with a natural reservoir or built near a river, the installation costs are significantly lower [22].

- To develop a detailed model of the microgrid system consisting of pump-hydro, photovoltaic, wind, and energy-storage systems as well as diesel generators.
- To design a MATLAB-based controller for the proposed system, using the Quasi-Newton optimization algorithm.
- To examine the technical performance of the proposed system, with and without an energy storage system, using realistic renewable resources data.
- To investigate whether it is suitable for storage applications of the renewable-based microgrid system, with the pump-type hydroelectric unit.

## 2. Modeling of the Isolated Microgrid System

#### 2.1. Solar PV System

^{2}), Ԑ denotes irradiation of solar (kW/m

^{2}) (shadings not included), n represents panel efficiency (%), and T denotes ambient temperature (°C). The power output of a PVG system mainly depends on the ambient temperature (T) and irradiation (Ԑ), which is why A and n are taken as constants. The value of T is taken into account at 25 °C in this study. The realistic variation data of the solar radiation (kw/m

^{2}) for simulations are shown in Figure 2. The reference of maximum generating capacity is (0.8 p.u) by the PV generator, and the system worked on the basis of the maximum power-point-tracking technique. In this study, the transfer function for the solar power model is considered as:

#### 2.2. Diesel Generator

^{3}/degree), R denotes the universal gas constant (R = 8.314 kJ/kmol K), S denotes the stroke length (m), L represents the length of connecting rod (m), V

_{disp}represents the displacement volume (m

^{3}), T denotes the instantaneous temperature (Kelvin) at any crank angle θ, and θ is the angular displacement with respect to bottom dead center. Referring to the synchronous generator of the conventional diesel engine generator model, the power output of the diesel generator is, directly, proportional to the inlet valve action, and the internal combustion engine action, consequently, a linearized transfer function is signified by the following, Equation (4):

#### 2.3. Battery Energy Storage

#### 2.4. Wind Turbine

^{2}/day, the annual average temperature is 11 °C, and the clearness index is between 0.46 and 0.63 for the selected location, as displayed in Figure 2. The power output of the wind turbine generator, using the real source data of the wind speed has some limitations.

_{rat}denotes the rated wind speed, V denotes the wind speed at the desired height, V

_{out}represents cut-out speed, and V

_{in}represents cut-in speeds. The relationship between wind speed and power for the wind turbine is shown in Figure 3. The horizontal axis is expressed in wind speed, measured in meters per second. The vertical axis is expressed in kilowatts.

#### 2.5. System Dynamics Modeling with Pump Micro Hydro

#### 2.6. Micro-Pumped-Hydro Storage System

^{3}/s, passes the volume of water W = Q t, m

^{3}. The total energy of the up and downstream reservoir flow in sections is calculated according to the Bernoulli equation. When using hydraulic reservoirs, energy production is carried out, as a result of the transition of the potential energy of water in the channel, into kinetic energy directly in the hydraulic converter. In this case, the power generated by the falling water will be:

## 3. Introduction to the Quasi-Newton Method

#### Objective Function Formulation to Design an Optimal Controller

## 4. Simulation Results and Analysis

#### 4.1. Non-Availability of Solar Power Full-Day

#### 4.2. Non-Availability of Wind Power Full-Day

#### 4.3. Random Load Fluctuations and Variable Power Generation throughout the Day

#### 4.4. Sudden Variation of a Load Change with Day-to-Day Operations

- The electrical energy produced by the renewable energy source varies according to seasonal conditions. For this reason, in order to ensure the energy continuity of the system in the island-mode microgrid, diesel generators and batteries are used for the worst-case scenarios, where there is no access to electrical energy. This shows that renewable energy sources make a limited contribution to energy production.
- Energy storage technologies, such as batteries and pump hydro, are a solution to these problems, as they are integrated into the microgrid, to ensure reliability and quality in the efficiency of the power system with different renewable energy sources.
- Electricity is stored with storage systems, when energy prices are low and renewable resources are plentiful, and it is used when energy prices are high, thereby reducing energy costs. It provides support to users to increase the reliability of the power supply in case of failures in microgrids and sudden load changes. It, also, improves the power quality, by protecting the frequencies and voltages of the microgrids.
- A basic descent direction Quasi-Newton-mehtod-based optimization technique was applied, simultaneously, for smooth constrained optimization of all PI controllers during different operating conditions of the microgrid system. The frequency fluctuations were minimized by means of a descent-direction Quasi-Newton-method-based optimization method, namely, the Broyden–Fletcher–Goldfarb–Shanno technique.
- Battery groups and diesel generators are in the group of controllable sources, as they can adjust the energy production according to the load demand. For microgrid applications, a diesel generator is used as a secondary energy source and ensures energy continuity.
- It is aimed to coordinate the load flow between the components of the microgrid, meet the energy demand, maximize the benefit obtained from the wind and PV power system, and consume minimum fuel from the diesel generator in the network system, with the pump-hydro system in this direction.

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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**Figure 4.**The pump-hydro unit is obtained via the following transfer function representation [60].

**Figure 8.**Frequency response of the microgrid with random load fluctuations and variable power generation.

Reference, Microgrid Type | Advantage | Disadvantage | Generating/ Storage Sources | Methodology |
---|---|---|---|---|

Centralized [38,39,40,41] | It is based on high-efficiency, low-cost, clean energy sources. It provides uninterrupted energy by being safely separated from the regional grid. It meets the instantaneously changing demand needs of the central grid. Losses in power lines are prevented. The risk is distributed; the central grid becomes stronger. After various disaster situations, the problem of line interruption disappears. | Complex and costly protection circuit design Sudden fluctuation and control/damping difficulties The necessity of establishing a microgrid modeling and control mechanism Renewable energy sources are affected by weather conditions Investment and maintenance cost of the energy storage unit | PV/Wind/ Hydropower/ Grid/Battery | Generalized backstepping method, Sequential quadratic programming, Muddy soil fish optimization algorithm, Active-set method, Interior point method |

Decentralized [42,43,44] | Diversified risk rather than concentrated risk, Enable and increase the sustainable use of renewable energy, Reduce the cost of energy for consumers. | Complex control method, Low resiliency, Difficult to establish a consensus for all players | PV/Wind/ Hydropower/ Grid/Battery | Bender’s decomposition algorithm, Differential evolution algorithm, Compound alternating direction method of multipliers, Chase algorithm |

Hybrid [45,46,47,48,49] | On-site generation, to reduce inter-regional transmission losses, To increase service quality by detecting faults instantly, To use resources efficiently by supporting demand management, Use more local resources, Have a more dynamic and durable network. | High dependency on communication networks, If a fault occurs in the central controller, All microgrids operate independently | PV/Wind/fuel cell/Micro-hydro/Biomass fueled combined heat and power unit/Aqua-electrolyser/Diesel generator/Biogas/Battery | Linear programming, Crow search algorithm, Marine Predator Algorithm, Shuffled Frog Leaping Algorithm, Sine cosine algorithm, Grey wolf optimizer, Metaheuristic algorithm, |

Nested [50,51,52] | High resiliency, Less operation cost, Strong privacy protection. | Very complex structure, Long calculation time | PV/Wind/ Hydropower/ Hydrogen/Battery | Linear programming, Nested algorithm, Distributed optimization |

Scenario | Power Units of the Working Model | Duration(s) | Values |
---|---|---|---|

Non-availability of solar power full-day | Wind turbine, pump micro-hydro, Battery groups, diesel generator | 24 h | no generation from the solar PV system |

Non-availability of wind power full-day | PV, pump micro-hydro, Battery groups, diesel generator | no generation from the wind farm | |

random load fluctuations and variable power generation throughout the day | Wind turbine, PV, pump micro-hydro, Battery groups, diesel generator | sudden load demands in consumption | |

sudden variation of a load change with day-to-day operations | Wind turbine, PV, pump micro-hydro, Battery groups, diesel generator | +18% load 07:00 a.m., +18% load 21:00 p.m. |

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**MDPI and ACS Style**

Coban, H.H.; Rehman, A.; Mousa, M.
Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage. *Water* **2022**, *14*, 1818.
https://doi.org/10.3390/w14111818

**AMA Style**

Coban HH, Rehman A, Mousa M.
Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage. *Water*. 2022; 14(11):1818.
https://doi.org/10.3390/w14111818

**Chicago/Turabian Style**

Coban, Hasan Huseyin, Aysha Rehman, and Mohamed Mousa.
2022. "Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage" *Water* 14, no. 11: 1818.
https://doi.org/10.3390/w14111818