Sizing of a Hybrid Microgrid with Storage for a Remote Village in Angola - Xikola Yetu

Sizing of a Hybrid Microgrid with Storage for a

Remote Village in Angola

Cludio A. C. Cambambi

Federal University of Itajuba, UNIFEI Itajub´a, MG, Brazil

adrianocambambi91@gmail.com

Abstract—In the growing countries, the energy sector is weak-ened, with electrical grids not being able to provide power to all areas, especially regions farthest from urban centers. This is the situation of Angola on which the present study is concerned. It is estimated that in Angola only about 33% of the population has access to electricity, where most of this energy is supplied to urban centers, the interior regions being virtually without access to electricity. Rural electrification is a strategic policy measure in social inclusion, which serves to promote human development and is a determining factor for the harmonious development of the national territory. Therefore, the present work had the objective of sizing and simulating an autonomous system using wind / solar generation, together with an energy storage system, to feed the public lighting network, a hospital and schools in the rural community of Rivungo / Angola. The simulation of the project was carried out through the software HOMER, which is an open source computer tool specialized in microgrid analysis. The solar system is responsible for 95.6% of the energy generated, with the wind system providing 4.39%.

Index Terms—Angola, microgrid, sizing, HOMER

I. INTRODUCTION

We are living in a time when access to energy is a basic human right. Despite this, according to Angolan Ministry of Energy and Waters (MINEA), energy consumption in Angola is mostly urban, thus corroborating with the International Energy Agency (IEA) that about 84% of people without electricity live in rural areas where the population is disperse and energy demand is very low [1, 2]. For most cases it is not profitable for both the government and public utilities to extend the national distribution network because of the low rate of electricity consumption added to the high cost of installation [3].

The present study covers the rural village of Rivungo, located in the province of Cuando-Cubango is a sandy land with a lack of roads, which makes it difficult to circulate between the village of Rivungo and other communes. As a consequence, in Angola the implementation of new medium voltage lines (MT) for villages with these characteristics is not practical for the following reasons:

• Lack of roads suitable for access to the village;

• Small population density in the village makes the exten-sion of the network unprofitable.

The authors thank to Brazilian research agencies: CNPq, FAPEMIG, INERGE, and CAPES (Coordenac¸˜ao de Aperfeic¸oamento de Pessoal de N´ıvel Superior - Brasil - Finance Code 001) for the partial support on this work.

Village located in long-distance location, extension finds technical problems such as transmission line capacity, power outage and voltage [3].

Maintenance of transmission lines would be a problem due to lack of roads asphalted. As a consequence, if the classical model is followed, rural areas are not likely to be connected to the national grid in the near future. Therefore local micro-grids are expected to play an important role in electrification strategies of Angola and beyond [5]-[7].

This work aims to propose the implementation of an au-tonomous hybrid system to feed the public lighting network, a hospital and schools.

II. EVOLUTION OFDEMAND

Between 2008 and 2014, electricity consumption in Angola recorded an average annual growth rate of 15.5%. In fact, the consumption of electricity for production, without taking into account the repressed demand and the demand supplied through generators for self-consumption, reached 9.48 TWh in [8].

The strong growth in electricity consumption in recent years is associated with: (i) the high level of electrification efforts being undertaken by the Government of Angola; (ii) improving the living conditions of the population, resulting in increased electricity consumption, and (iii) increasing available production capacity [8]-[9].

III. THEROLE OFSMARTGRIDS IN THEANGOLAN

ELECTRICITYSECTOR

These smart grid technologies can make an important contri-bution to universal access to electricity in Angola. Developing countries have the potential to overcome traditional energy systems in terms of technology and regulation. The following reasons make it increasingly clear the need for investment and implementation of smart grids in the country [11].

Price and tariffs: Angola’s electricity sector currently has some of the lowest tariff levels in Southern Africa and East Africa. To aggravate this reality the sector has a high rate of transport and distribution losses and a productivity of the lowest in the region. So smart grid technologies are expected to help minimize transmission losses, for example, facilitat-ing more effective power compensation and reactive voltage

control. Distribution losses can be solved through adaptation voltage control at substations [7].

Reliable supply: A high-quality and functional electricity industry is a fundamental requirement for the successful implementation of the executive’s broader economic policy in order to ensure sustained economic development of the country.

Data management: In times of water scarcity and high prices, energy distributors seek solutions to generate, transmit and measure the product more effectively, identifying where it is possible to economize. The majority of electricity statistics in Angola are incomplete and / or outdated, which can lead to its misinterpretation and consequently to financial losses [2].

IV. SOFTWAREHOMER

The system under study includes the combination of wind turbines, photovoltaic cells and an energy storage system. The choice of such components depends very much on the size of the project, i.e., technical and economic issues.

The choice of software is to scale and minimize both implementation as well as operational costs, maximizing re-liability as well as offering availability. To achieve such op-timum results several software or algorithms have been used, these include linear and nonlinear programming optimization methods among others. In the present article we used the software HOMER (hybrid optimization model for multiple energy resources) to reach the desired criteria.

In Fig. 1, ”G3” represents the wind turbine; ”Electric Load” refers to the load of the community; ”Converter” symbolizes the inverter; ”PV” represents the photovoltaic panel; and, finally, ”1 kWh LA” is the battery representation.

Fig. 1. Architecture of the hybrid system created by the HOMER software.

A. Input Variables for the HOMER Software

In this section we provide the input variables for the micro-simulation, which are the solar irradiance data and monthly average wind speed of the region under study, the load demand, the costs associated to the micro-redo including initial investment costs, the equipment replacement cost and operating costs, as well as maintenance (O&M) costs. Load profile and demand parameters can be seen in Fig. 2

TABLE I

DEMANDPARAMETERS TO BEMET BY THEHYBRIDSYSTEM

Metric Baseline Scaled Average (kWh/day) 165.59 165.59 Average (kW) 6.9 6.9 Peak (kW) 23.31 23.31 Load Factor 0.3 23.31

B. Dimensioning of the Wind System

Figure 3 shows the average monthly wind speed for the Rivungo / Angola community at a height of 50 meters, with the purpose of guaranteeing energy for all months. HOMER simulates the system with the average speed of 12 months.

The wind turbine chosen for system design is Whisper brand. The choice was based on the initial low wind speed required for it to come on stream, resulting in increased production and lower risks of power outages.

C. Sizing of the Photovoltaic System

The photovoltaic module used in the design is the SunPower brand, model SPR-440NE-WHT-D. As can be seen in Fig. 4, the month of May presented the lowest recorded value of solar irradiance when compared to other months, being approximately 4.70 kW h/m2_{/day. Therefore, there is about}

4.70 hours of full sun for the most critical month of the year. Subsequently, the simulation is performed in order to verify if the demand needed to meet the load is reached. If this condition is met, costs and energy production are evaluated, and the most cost-effective system is chosen. Otherwise, the components used are resized and the simulation process starts again.

V. RESULTS

Fig. 5 shows the ideal solution for the proposed system. On the software, two wind turbines should be used. However, 405 batteries (1 kW h LA) should be used for the system to have a micro-relay self-sufficiency of approximately 35.2 hours. The converter has a power of 25.2 kW , because this is the maximum value that the designed system can withstand.

Fig. 6 shows the monthly average electric production of the two sources used to satisfy the demand. The orange column represents the solar system power generation, while the green column represents wind power generation. Tables II and III present energy production, demand as well as specific parameters related to the microgrid.

As can be seen in Tables II and III below, the average cost of energy generated (COE) is $ 0.613 / kW h and the system can provide up to 100,212 kW h/year.

From Fig. 7, it can be verified that the PV system is responsible for 95.6% of the generated energy, with the wind system providing 4.39%. This result was already expected, since according to MINEA in its plan for the electrification of Angola, the Rivungo region is the only one that presented the potential for a 100% solar system to be implemented.

Fig. 2. Load profile created by software Homer, with the demand to be met by the hybrid system

Fig. 3. Average wind speed of the region under study.

TABLE II

MICROGRIDENERGYPRODUCTION ANDCONSUMPTION

Production kWh/yr % Generic flat plate PV 100,212 95.6 Generic 3 kW 4,601 4.39

Total 104,813 100

Consumption kWh/yr % AC Primary Load 60,405 100

Fig. 7 makes it clear that the system is excellent, producing a surplus of 32.5% annually, which leads us to conclude that in addition to the system supplying the local demand, the residents of the region can inject the surplus in the local network, which can later be used as credit.

According to data presented in Fig. 7 and Table IV, it can

Fig. 4. Solar irradiation of the study region

Fig. 5. Ideal solution calculated by the Homer software.

TABLE III

SPECIFICSYSTEMPARAMETERS

Quantity kWh/yr %

Excess Elecricity 34,022 32.5 Unmet Electric Load 37.1 0.0614 Capacity Shortage 60.0 0.0993 Renewable Fraction – 100 Max. Renewable Penetration – 2,269

be seen that the photovoltaic system has a maximum capacity of 53.2 kW , providing daily energy of 275 kW h/day and 100,212 kW h/year, corresponding to 95.6% of the energy generated by the system. It produces energy for 4337 hours per year, corresponding to 12 hours of generation per day.

The wind system has an installed power of 3 kW , which is also the maximum electrical power that the system can produce. Each wind turbine has a power of 3 kW as already mentioned, however each one produces 0.525 kW . Low pro-duction is due to the low resources (low wind speed) in that area. This system works 7051 hours / year, which corresponds to 19 hours / day, as seen in Fig. 8 and Table V.

The inverter operates all year round. During this time it

TABLE IV SOLARSYSTEMPARAMETERS

Quantity Value Units Quantity Value Units Rated Capacity 55.1 kW Minimun Output 0 kW Mean Output 11.4 kW Maximum Output 53.2 kW Mean Output 275 kWh/day PV Penetration 166 % Capacity Factor 20.8 % Hours of Operation 4,337 hrs/yr Total Production 100,212 kWh/yr Levelized Cost 0.133 $/kWh

Fig. 6. Monthly solar and wind energy production in the study region.

Fig. 7. Performance of the solar system.

receives an energy of about 59 M W h and delivers 95 % of this energy to the load. The energy passing through the inverter is the energy equivalent to the consumption plus 2938 kW h per year, this one representing the 4 % losses of the inverter, as show in Fig. 9.

For this type of generation, it is extremely important to use an energy storage system, such as a battery bank, due to the intermittency of these sources (wind and solar). Although they often complement each other, there are cases in which generation is not sufficient to meet demand. In such cases, the storage system is used to provide power, thus increasing the reliability of the system, the autonomy of the system is directly proportional to the number of batteries.

The results in Fig. 10 and Table VII. show that the energy received by the battery was 37,637 kW h/year and that supplied to the load was 30,190 kW h/year, resulting in

TABLE V

WINDSYSTEMPERFORMANCE

Quantity Value Units Quantity Value Units Rated Capacity 3.0 kW Wind Penetration 7.61 % Mean Output 0.525 kW Hours of Operation 7,051 hrs/yr Maximum Output 3.0 kW Levelized Cost 0.348 $/kWh Capacity Factor 17.5 % Total Production 4,601 kWh/yr

Fig. 8. Performance of the wind system.

TABLE VI

INVERTER ANDRECTIFIERPERFORMANCE

Quantity Inverter Rectifier Units Hours of Operation 8,691 53 hrs/yr Energy Out 55,830 24.8 kWh/yr Energy In 58,769 26.1 kWh/yr

Losses 2,938 1.31 kWh/yr

losses of 7,447%. The battery can run for about 35.2 hours of discharge.

TABLE VII

PARAMETERS OF THEBATTERYENERGYSTORAGESYSTEM

Quantity Value Units Quantity Value Units Batteries 405 qty. Energy In 37,637 kWh/yr Autonomy 35.2 hr Energy Out 30,190 kWh/yr Nominal Capacity 405 kWh Losses 7,537 kWh/yr

During the year, the battery was mostly over 60 % of the load and in about half of this time it was 80 % load, only in January and November it was about 40 %, but in all months it was always above 30 % of its rated capacity.

When there is no solar irradiance, the photovoltaic system stops supplying energy to the load. At this time, the battery bank that supplies power to the load because the wind system does not have enough production. The solar resource ceases to exist from 6 p.m., but demand increases from 4 p.m. to 6 p.m. and in this period the batteries supply some of their energy to help satisfy the consumption, delivering power between 10 and 20 kW .

Since at 6 p.m. there is no solar resource, the batteries increase the power supplied to near its maximum until 20 p.m., and from this time and beyond the consumption drops again. From 6 a.m. to 12 p.m. there is plenty of solar power and low demand, so the battery bank practically does not supply energy in this period.

VI. CONCLUSIONS

The results indicated a surplus in energy production of 32.2% annually, which leads us to conclude that in addition to the system supplying the local demand, the residents of the region can inject the surplus in the local network, that later can be used as credit. Thus, the use of renewable resources should serve as strategy to improve energy supply in rural areas.

Fig. 9. Inverter power output during the year

Fig. 10. Battery performance

Therefore, it can be concluded that the analyzed system can be considered effective, since it is possible to supply the electric energy demand necessary to serve the community.

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