An Intelligent Energy Management System Solution for Multiple Renewable Energy Sources

Abstract

This paper proposes an intelligent energy management system based on multiple renewable energy sources. The intelligent energy management system is defined as a flexible energy management system built by integrating multiple renewable energy sources and facilities for energy storage. The general objective of this paper is to propose a solution to increase the use of energy potential from renewable sources by embedding small-sized energy sources to behave as a higher-power energy source. The proposed system includes solar, wind, and hydro as renewable sources. As the system is not connected to the primary distribution grid, two alternatives for energy storage are also included: batteries and a water basin used for hydro energy. The system includes a diesel generator as a reserve. The system can be adjusted depending on the consumers it serves and the location where it is implemented (i.e., the potential of electricity, wind, and hydro). The main contribution of this paper is the use of an energy storage concept in the form of a “natural” battery system composed of a water storage basin into which water is pumped when we have a surplus of energy from renewable generators.

1. Introduction

The efficient use of energy resources was and is a significant interest of all decision-makers at the national, European, and international levels. The European Union (EU) and all member states have signed and ratified the Paris Agreement on reducing greenhouse gas emissions by up to 55% until 2030 compared to the 1990 level. In support of the efforts of the authorities, but also of private entities fighting to achieve these objectives, considerable research efforts are being carried out related to energy management systems [1,2] for the management of several renewable energy sources that could lead to a reduction in the use of energy from fossil fuels.

The primary renewable energy sources are [3,4,5,6]: bioenergy, direct solar energy, geothermal energy, hydropower, wind, and ocean energy (tide and wave). These sources can be included in micro-grids [7] that take care of consumers in remote areas or within a building.

The main energy management systems (EMS) [8] available on the market or presented in the literature are based on a single renewable energy source and a single energy storage possibility. This paper proposes an EMS that includes several renewable sources: solar, wind, and hydropower, and two storage possibilities: batteries and a basin for hydro energy production. As the system is not connected to the electricity distribution grid, the system includes a diesel generation group as a backup option.

In this paper, we propose and describe an intelligent management system for multiple renewable energy sources (photovoltaic, wind, hydro) combined with conventional energy generation sources (conventional generators). As a storage solution, the system uses batteries combined with an intelligent energy storage solution that uses reversible pumps and a water storage tank when we have a surplus of energy in the system. This system contains software that can run in:

• Simulation mode to obtain the optimal dimensioning ratio of all energy-generating/storage elements;
• Automatic mode to control all elements, such as start/stop valves and actuators, for coupling energy sources in the micro-grid and monitoring their parameters.

The proposal for the EMS began with the request of the Boulet Monastery (which is located in an isolated mountain in Cracaoani commune, Neamt county, Romania) to E-ON (the company that owns the medium and low voltage electrical grid, which is also the electricity provider in the Cracaoani commune and the entire territory of the county) to connect to the electrical grid. The answer was that the cost of the investment is EUR 100,000 for the establishment of the overhead power grid: installation of poles; electrical cables/wires, 20 Kv/230 V transformer; installations and works for supplementing the network energy; installation of communications and monitoring of the network and consumers; installation of electricity consumption metering systems; landscaping works, etc. It was also remarked that the underground network could not be built because it was challenging to carry out technically, but also very complicated and difficult to obtain the approval of the works: the entire area and the route, of approx. 5 km, is located in a protected natural area and takes place on a forest road, on the edge of a river, and at the edge of the forest. E-ON also stated that, apart from the investment, the consumers who will be connected to the network thus established will have to pay, subsequently, the counter value of the electricity consumption, but also maintenance or intervention costs in case of local defects [9].

The proposed system introduces an energy storage concept in the form of a “natural” battery system composed of a water storage basin into which water is pumped when we have a surplus of energy from renewable generators (wind and photovoltaic) with the help of reversible pumps that can be used both for pumping in the pool and for generating electricity when necessary. By using the simulator mode from the software, the production/storage capacity per element can be efficiently sized to have an autonomous system. The system is intelligent because it manages several energy sources and several energy storage systems (batteries and a water basin). With the help of the proposed system, it is first required to study and perfect the model implementation of an energy management system using an energy storage system in some water basins alongside classic storage sources (battery system) by making the system more efficient, and the priority use of cheap energies (wind, photovoltaic) when they are available to be stored in the battery system or water pumping in the upper basin, and use of this energy when necessary.

This paper is structured as follows: in Section 2, we present the context of a study and related works that highlight the advantages and benefits of EMSs, together with the proposed solutions for the EMS presented in the specialized literature; Section 3 presents the materials and methods considered; in Section 4, a solution of an intelligent energy system is proposed; the technical solution is presented in Section 5; the discussions related to the solution proposed in this article are presented in Section 6; limitations are presented in Section 7; and the conclusions are highlighted in Section 8.

2. Related Works

A review of the energy saving achieved by energy management systems is presented in [10]. This comprehensive survey investigates 276 papers related to EMSs in buildings, in the industrial environment, and for specific equipment. This study noted that the saving effects of using an EMS in the building increased from 11.39% to 16.22% annually. In the industrial environment, the saving effects decreased from 18.89% to 10.35 annually. With the use of the EMS for lighting systems, the saving effect increased by up to 39.5%.

In [11], the authors present an EMS based on smart metering for implementing energy management strategies. The system uses a photovoltaic energy system and batteries for storage. The proposed system achieves a better consumer energy gain by ensuring up to 28% of the total energy consumption. Simulation results, using one-year real measured data, show that the proposed EMS design achieves an 11.4% reduction in the maximum power absorbed from the grid.

A fuzzy-based energy management system is proposed in [12] that achieves an 11.4% reduction in the maximum power absorbed from the grid. The fuzzy logic control is used to predict the micro-grid behavior for the next 12 h based on the balance of energy generation and consumption forecast.

An energy management system for residential buildings with a photovoltaic generation system for renewable energy sources is presented in [13]. The proposed system has three stages: forecasting, day-ahead scheduling, and actual operation. The simulations have shown that the system can coordinate the day-ahead and actual operations of a smart home. The proposed system is then validated with a real dataset.

In paper [14], the authors proposed a hybrid platform energy management system consisting of wind and photovoltaic generators with a storage system based on fuzzy logic control. They demonstrated that by using fuzzy logic control, continuous voltage regulation is guaranteed, supply is ensured even with wind and radiation fluctuations or load changes, and they also kept the batteries at acceptable intervals. The authors concluded that if they used a combination of renewable sources of photovoltaic or wind energy, as well as batteries as a storage system, the load demand is satisfied at all times.

Paper [15] proposed a hierarchical energy management system with high solar photovoltaic (PV) penetration for smart homes. The authors performed the energy management in two stages, namely, to determine the device schedules on the first day, they established a stochastic programming model for the next day. In the next stage of actual operation, they used a mechanism for stochastic optimization of the running horizon to upgrade the operation of the Residential Battery Energy Storage System (RBESS).

In [16], by allowing for load demand variations on optimally integrating solar photovoltaic (PV) and wind turbines (WT), the authors solved the problem of energy management of a micro-grid (MG) connected to a primary energy system, considerably reducing the total cost and improving system performance. In applying this technique, the authors had to consider certain parameters such as wind speed, the market price in deterministic and probabilistic conditions, load demand variations, and solar radiation. The authors used an efficient algorithm called the equilibrium optimizer (EO), which is superior to both the cosine sine algorithm (SCA) and the whale optimization algorithm (WOA) to improve the voltage profile and voltage stability.

Most of the EMSs presented in the literature [10,17,18,19] focus on reducing energy consumption from the primary grid. The system proposed in this paper aims to be autonomous, without connection to the primary grid. Thus, the proposed system uses several renewable energy sources to satisfy consumer demands. These energy sources are activated according to needs, and the surplus is stored in conventional and “natural” batteries composed of a water storage basin into which the water is pumped.

HOMER (Hybrid Optimization of Multiple Energy Resources) software [20,21] is a solution to simulate and dimension an energy system. The Homer software uses only conventional energy generation and storage sources in the simulation. Our system introduces an energy storage concept in the form of a “natural” battery system composed of a water storage basin into which water is pumped when we have a surplus of energy from ecological generators (wind energy, photovoltaic) with the help of reversible pumps that can be used both for pumping in the pool and for generating electricity when necessary. By using the simulator in the software, the production/storage capacity per element can be efficiently sized to have an autonomous system.

3. Backgrounds

This article proposes an intelligent management system for renewable resources to support the efforts of the authorities in the development of the renewable energy supply and the companies that share this goal. The system could lead to a reduction in the use of energy generated from fossil fuels.

This paper proposes the use of renewable energy sources such as solar, wind, or hydro energy. We designed and developed an intelligent system that combines electrical energy from several sources to achieve maximum efficiency in the energy management system. The EMS will command the activation/deactivation of the actuator elements to redirect the energy flow from the energy-producing elements (photovoltaic panels/wind turbines/hydro generators) to the consumers or the energy storage elements. The system involves implementing elements with automatic adjustment according to energy consumption.

The constituent elements of the energy management system are the following:

• Solar energy generation source;
• Wind energy generation source;
• The hydro energy generation;
• Water storage;
• Battery-based energy storage system;
• Diesel generator group.

With the help of these energy sources and high-capacity batteries, we can produce and store energy at lower costs. When energy consumption rises above the production level, the system uses the stored resources to supplement the grid supply. Each power generation group can be scaled to fully utilize it.

The proposed system uses a basin to collect water from a nearby river, from which it pumps water into a basin positioned at a higher altitude, to produce energy later. The basin fill pump is turned on when there is a surplus of energy in the system and the basin is not filled to the total capacity. The primary source of energy production is the photovoltaic panels, which produce enough energy to supply the electrical network but also to store energy in batteries and to fill the basin. In addition to the photovoltaic panels, there are connected wind energy sources and a generator set that starts only when there is no other energy source in the system.

4. The Proposed Solution of the Intelligent Energy System

With the help of the proposed intelligent energy system, we first want to study and improve the implementation model of an energy management system by using an energy storage source in a water basin alongside the classic storage sources (battery system). Thereby, the system could be more efficient by prioritizing the use of cheap energy sources (wind, photovoltaic) and storing the available surplus in the battery system or water pumping in the upper basin for use when necessary.

The general operation scheme of the proposed intelligent energy system is presented in Figure 1. The constituent elements of the intelligent energy system are as follows:

• The catchment with diversion of a permanent natural water course (1 from Figure 1);
• An upper basin (3 from Figure 1) with a capacity of at least 800 m³—in which the water is transported to a level below the catchment level through a pipe;
• A lower basin (4 from Figure 1) with a capacity of at least 1500 m³—in which the water from the river is discharged at the level of the river in that area, but where it flows and passes through the high-capacity hydro power plant (MHC 1) (5 from Figure 1);
• Discharge facility (from the upper basin to the lower one) with a capacity of 0.04 m³/s, on the course of which will be installed a low-power micro-hydropower plant of approximately 30 kW (MHC 1) (5 from Figure 1);
• Adduction path (from the lower basin to the upper basin) in order to supplement the volume of water in the upper basin if necessary. The addition of volume will be achieved by slow pumping with the use of a pump (15c from Figure 1) driven by energy resulting from the production of solar, wind, hydraulic energy, etc. of small capacity;
• Low-power micro-hydropower plant (approx. 1 kW) directly on the permanent natural water course (MHC 2) (6 from Figure 1);
• Energy management system (7 from Figure 1, dispatcher type—see Figure 2);
• Solar and wind panels (9 and 10 from Figure 1);
• Elements for energy storage (11 from Figure 1);
• Distribution grid (11 from Figure 1);
• Emergency diesel generator unit (8 from Figure 1);
• Consumers (16 from Figure 1);
• Radio, GSM, telephony system (13 from Figure 1).

The characteristics of the intelligent energy system are:

• Able to integrate multiple sources of renewable energy:

  ✓

  The use of permanent natural watercourses with a low flow for the generation of electricity is the main priority;

  ✓

  The integration in the energy generation process of multiple sources of renewable energy: solar panels, micro-hydro plants, wind plants, etc., as a secondary priority.

• Energy conservation by ensuring a high degree of energy security at the level of the system.
• Is implemented to ensure the energy security of tropical areas that are characterized by:

  ✓

  Geographical isolation;

  ✓

  The lack of possibility of connection to the national energy system, or the very high cost that connection implies;

  ✓

  Favorable topography for system installation:

  ▪

  The existence of a source (course) of permanent natural water with a low flow, between 3 mc/s and 0.1 mc/s;

  ▪

  A level difference of max. 30–100 m along the watercourse route.

The energy flow of the proposed system is presented in Figure 2. Energy sources (photovoltaic, solar, batteries, hydropower, and diesel generator) and consumers (battery charging, water tank filling pump, and other consumers) can be observed. The EMS controls the energy flow through switches (which are also shown in Figure 3).

5. The Technical Solution

The whole system is controlled by an intelligent energy management system. This software module acquires data from the sensors installed in the field (flow rate, energy consumption, produced energy power, etc.) and controls the actuators from the field. The software solution graphically illustrates how the system works. In Figure 3, we can see the main components of the system:

• The energy generation component, composed of MHC1, MHC2, wind group, photovoltaic group and diesel generator group;
• Energy storage component, water collection basin and battery system;
• Consumers;
• Dispatcher made up of hardware and software components.

The order of use of energy sources in the system is as follows:

• Photovoltaic energy;
• Wind power;
• Energy stored in batteries;
• Hydro energy;
• Energy generated by the burning of fossil fuels (generator group).

Power Generation Component. The power generated in the system is generated from several sources. The MHC1 and MHC2 groups use hydropower to generate power when the system requires it. MHC1 has a minimum generation capacity of 5 kWh and can generate a maximum of 30 kWh. For the purpose of efficient resource management, this group will come into operation only when the energy requirement that cannot be provided from other sources is over 5 kWh. The MHC2 component has a capacity between 1 kWh and 5 kWh. The wind group has a maximum capacity of 0.4 kWh. Photovoltaic energy is the main energy-generating component in the system, with an installed capacity of 15 kWh. When the energy consumption of the system is reduced, the generated photovoltaic energy is stored in the batteries and by pumping water into the pool. The diesel generator group will be used as a backup system. It will come into operation only when there is no other type of energy in the system.

The energy storage component. For efficient resource management, a mixed energy storage system was created both in batteries and in a basin located at a high altitude. When using photovoltaic or wind energy, the dispatcher will proceed to charge the batteries and turn on the pool filling pump. The system dispatcher has the role of limiting the download of system components below the 30% limit.

Consumers. The system has been dimensioned for the efficient use of all components with a minimum energy of 2 kWh that must be ensured for the consumer. With the increase in the energy requirement for consumption, the dispatcher will manage the energy sources to ensure the required amount of energy is available.

The dispatcher. The dispatcher is made up of several software and hardware components that ensure efficient management of the energy in the system. It has the possibility of running in 2 modes of operation: automatic and manual. In manual mode, the human operator from the dispatcher’s frame will have the possibility to enable/disable some system components to ensure the energy requirement for the consumer. The automatic management mode involves the use of decision algorithms in the operation of the various components of the system. The automatic management mode considers the data acquired by the system hardware components to know what energy is available and required for consumption to turn on/off the various system components. The illustration of the operation algorithm can be seen when changing the energy value for the consumer and actuating the switch from the consumer.

In the automatic operating mode, the program will forecast the generation of photo-voltaic energy depending on the time. The system will forecast an illumination degree close to zero until 6 o’clock, after which we will have an illumination degree of approximately 1000 W/m² between 13–14 h. Following that, after these hours, the energy produced drops to zero. The distribution of the degree of illumination was implemented using several sources of information, which led us to define a formula that represents a Gauss distribution type distribution.

According to [22], in the city of Bucharest we have an average of 3.8 peak sun hours annually. The distribution of these hours per month of the year is shown in

Table 1. Distribution of peak sun hours.

Month	Peak Sun Hours
January	1.27
February	2.35
March	3.36
April	4.54
May	5.85
June	6.43
July	6.58
August	5.78
September	4.16
October	2.68
November	1.47
December	1.12

.

A detailed description of how solar peaking works can be found in [23]. The concept of peak hours can be exemplified in Figure 4.

We can observe in Figure 4 that, on average, July is the sunniest month with 291 h of sunshine. December has, on average, the lowest amount of sunshine with 63 h, and the average annual amount of sun is 2114 h.

The role of the energy management system shown in Figure 1 is:

• Monitoring and control of the volume in the basins (upper and lower);
• Monitoring and control of the required flow rate of the micro-hydropower plant in relation to the energy demand;
• Monitoring and control of flow compensations between basins in relation to the volume requirement of the upper basin;
• Monitoring of energy stocks from accumulators;
• Monitoring, distribution and compensation of energy production between the system’s energy sources: micro-hydropower plant, solar panels, wind turbine, etc.;
• Questioning consumers regarding the requested energy requirement;
• Ensuring safe operating conditions in case of non-existence of the required amount of energy.

6. Discussion

As we specified at the beginning, in this paper we have proposed to research, develop, and test an intelligent energy management system.

By intelligent energy management system, we mean a flexible energy management system created by integrating multiple sources of renewable energy allowing us to conserve energy.

Among the specific objectives of this article, we can list the following:

• The development of alternative ways of storing hydro energy;
• The development of an intelligent dispatcher-type energy system (please see Figure 1);
• The development of a leadership/management strategy for the intelligent energy system;
• The development of systems that integrate several types of electricity generators.

Primarily the system produces electricity by using water falling from the upper basin to the lower basin. The drop is controlled by a valve that allows a variable flow rate to be obtained. The electricity produced has a variable power (between 3 and 30 kW) in relation to the volume of water used to operate the micro hydropower plant. The amount of energy produced and the volume of water used vary in relation to the requirements of the final consumer (group of consumers).

If the flow of the upper basin falls below the minimum allowed level, and the water source that ensures its filling does not have a sufficient flow to satisfy the operating needs of the micro-hydropower plant, it is supplemented by pumping from the lower basin. Pumping is ensured by using renewable energies (solar, wind, hydraulic, etc.).

The system is equipped with an energy storage station and a charge distributor that makes the junction and manages the distribution between the energy sources included in the system: micro-hydro plants, solar panels, and micro-wind plants. Also, the system is provided with a diesel generation system in case of maximum emergency.

The control of the passage of water within the system is carried out with the help of electric valves, in a completely automatic way, in relation to the energy requirement at a given moment.

The advantages of the energy management system are:

• Very low impact on the environment (continuous use of renewable energy);
• Exploitation of the hydropower potential of permanent natural watercourses with the low flow;
• High quality of the electricity supplied;
• Storing electricity reduces the costs in the final bill;
• Autonomy with respect to the centralized energy system;
• Low maintenance and operation costs;
• Low amortization period;
• Very good yield/efficiency.

As we specified in the Introduction, this solution was implemented in a protected natural area. For this reason, we followed the necessary steps to gain approval from all the institutions/authorities involved: the Environment Administration; the Natural Park Administration; the Forestry Administration; the Authority for Lands and Pastures; the Town Hall; the county council; and we had discussions/debates with the citizens of the commune for information and to request their support.

Thus, in the development of solutions, we reached an initial cost price of EUR 35,000 by establishing a micro-grid using photovoltaic panels and an inverter with a capacity of 15 kW, storage batteries of 1200 Ah, wind turbines of 0.4 kW and, for reserve/emergency, a 5 kW generator, container-laboratory, data transmission system, cables, electrical panel, etc.

The initial condition was to be able to generate a minimum of 2 kWh, with the possibility of peak feeding for short periods, providing consumers with power of 25 kW. Thus, it was necessary to develop this intelligent system in the form of software that would manage the entire system to achieve the previously stated requirements. Through simulations, we noticed that the system works well, but the diesel generator often enters into operation mode. This was problematic because the intention was to have a complete RES (Renewable Energy Sources) system. Under these conditions, we developed an energy storage solution that was available in the network and unused in a hydropower battery. In this way, we developed the scheme as it is presented in Figure 1 and updated the software for the automatic operation of the system.

Through successive simulations, we established the dimensions described in this paper regarding the MHCs and the volume of the basins used. At the same time, we also obtained the desired green energy in our micro-grid. These new features generated an additional cost of EUR 55,000. In total, we arrived at an investment cost for our micro-grid of EUR 93,000 if we also consider a design cost of approx. EUR 3000. It can thus be observed that the investment value is below that offered by E-ON (EUR 100,000), but it is significant that the energy obtained is green, the diesel generator being very rarely used in emergency cases.

In addition, the energy obtained in our grid is free compared to that which could have been provided by E-ON or another supplier, which is over 250 EUR/1000 kWh, as you can see for European market in Figure 5 [24,25], and for Romanian market in [26].

Considering an average monthly production (and also consumption) of 4500 kWh, the result is a saving of 10,000 EUR/year and 100,000 EUR/10 years, a considerable amount, almost equal to the value of the investment, which also shows us the amortization period of the investment: 10 years. It should also be considered that the price of electricity is still unstable but always increasing.

In general, in economic calculations (e.g., cost–benefit calculations for financing projects), annual depreciation is considered alongside an indexation of approx. 5% of annual income as an effect of inflation. In our case, with such a system, a lifespan of 20 years for the entire system can be foreseen (with shorter replacement periods for some components, such as batteries, computers, automation, and controls that have a shorter lifespan of approx. ten years, but with other parts, such as constructions, hydrogen generators, etc., with a lifespan of over 30 years). In the 20 years, we can consider that at least EUR 200,000 is saved (not considering the inflation component or the perspective of price increases), clearly resulting in a replacement value of the system components and support for maintenance during the period of use.

If the efficiency principle were to be applied: investment cost/realized product value × 100%, initially we would say that the ratio, for one year, is inefficient at 0.1, but if we refer to a longer period, for example, 20 years, we can observe the evidence of high efficiency: the ratio is 2-super unit size, which in economic terms is a very high efficiency of 200%.

7. Limitations

This system has some limitations, in the sense that the scheme is economically valid for the production of a minimum quantity of over 5 kWh (the value of the investment is approximately the same for a lower production, but it can be observed, applying the above calculations/reasoning, that the investment cannot be amortized nor economically supported, the annual value being half at a lower limit). Technically this system is limited to a size/production capacity of less than 50 kWh due to the size of the equipment and the occupied land surfaces, but also due to the rising costs which begin to approach EUR 300,000, an amount that would be difficult to obtain even from banks. In this sense the solution presented by E-ON becomes more effective. We aimed to create a solution for small, isolated communities, such as a locality/community with less than ten families/30 inhabitants. To address these limitations, the system could be developed in the future by introducing new renewable energy sources, such as geothermal energy. In addition, it is expected that the cost of photovoltaic panels will decrease, and thus the system can overcome the limitations from an economic perspective.

8. Conclusions

This paper proposed an energy management system solution to reduce energy consumption from conventional energy sources. The proposed system includes renewable sources: solar, wind, and hydropower, and two storage possibilities: batteries and a basin for hydro energy production. As the system is not connected to the electricity distribution grid, as a backup solution it includes a diesel electricity generator to be activated in unforeseen situations or to support consumption peaks.

This paper’s main aim was to use an energy storage concept as a “natural” battery system composed of a water storage basin into which water is pumped when there is a surplus of energy from renewable generators.

It also aimed to suggest a solution to the need for an electricity supply to small communities that cannot be connected to the national energy system, can be connected to the national energy system but with high costs, or can be connected to the national energy system but the power quality is low.

From an economic point of view, this system no longer generates energy consumption costs from the primary grid but only the operating and maintenance costs of the system elements.