20th Electrical Power Distribution Conference, 28-29 April 2015, Zahedan, Iran
Optimal Battery Planning in Grid Connected Distributed Generation Systems Considering Different Technologies Majid Daghi
Mahdi Sedghi
Masoud Aliakbar-Golkar
Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran, Iran
[email protected]
Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran, Iran
[email protected]
Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran, Iran
[email protected]
Abstract— The battery energy storage units bring many benefits to the distribution networks. However, they may result in a high cost, if they are not used in optimal manner. Optimal sizing as well as the optimal typing of batteries is very important from both technical and economic points of view. In this paper, the optimal planning of the batteries in a grid connected distributed energy system is presented considering the most famous technologies of the batteries. As there is not specified value for the economic and technical parameters of the batteries, the expected values are used in case studies. This study determines which technology is the most suitable one to be used in the grid connected distributed generation systems. The numerical results show that selecting the optimal technology of the batteries affects the cost of energy considerably, and it should not be neglected in optimal planning. The sensitivity analyses represent the impact of wind energy, peak load and the price factor on optimal typing of the batteries.
4) The storage can be used for peak shaving and improving load factor. As a result, the expansion of generation and transmission system is postponed. This is valuable from economic point of view. 5) In addition to the deferral expansion, the distributed storage reduces the cost of purchased power by distribution utilities in deregulated environmental. 6) Because of the rapid response of power electronic interfaces, the storage units are ideal components for load following. 7) Storage, as a support, allows the DG units such as microturbines and fuel cells to be operated at constant output at its highest efficiency, reducing fuel use and emissions. 8) The energy storage can be used to damp the frequency oscillations thanks to the rapid change of their active and reactive power. Hence, the system stability increases. Despite of the above mentioned advantages, the energy storage units are usually expensive technologies [5]. Therefore they should be integrated optimally from both technical and economic points of view. Several types of electrical energy storage used in power system are as follows: 1) Batteries 2) Fuel cells 3) Flywheels 4) Superconducting magnetic energy storage (SMES) 5) Super capacitors 6) Compressed air energy storage (CAES) 7) Pumped hydro Among various types of distribution grid scale storage, the batteries are widely considered and studied in literature [6-13]. Optimal scheduling of batteries using dynamic programming is presented in [6]. The dynamic programming is used as well in [7] to maximize fuel-cost savings and optimize battery size. Optimal sizing of battery is considered in [8] where the genetic algorithm is employed for optimization. The impact of wind speed variability and load uncertainty on battery sizing is investigated in [9], and similar studies are presented in [10], [11]. Optimal placement and sizing of batteries is shown in
Keywords- Energy storage, Batteries, Distributed generation, Wind energy.
I. INTRODUCTION Distributed generation (DG) sources bring many advantages to the modern electrical distribution systems called active distribution networks (ADNs) [1]. Among all, renewable and sustainable energy sources such as solar and wind energy are more suitable for DG systems considering air pollution, environmental concerns and global warming phenomena as well as the limitation of fossil fuel resources [2]. However, the renewable energies are inherently intermittent which is problematic for electrical power systems [3]. In order to solve the problems arising from uncertain renewable DGs, the storage units can be used in such systems. The advantages of using energy storage units are as follow [4]: 1) They can reduce fluctuations in wind and photovoltaic (PV) output, and allow sale of renewable energy at highvalue times. 2) They allow loads to operate through outages. 3) The storage units can be used for voltage regulation, reactive power control and power factor correction.
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20th Electrical Power Distribution Conference, 28-29 April 2015, Zahedan, Iran [12], [13]. In [12], the Zn/Br batteries and DG units are used to minimize the investment, operation and reliability cost of distribution system, while the NaS technology is considered in [13] in order to optimize only the reliability index. However, in these references, only one type of battery is investigated. In the current work, several types of batteries are considered for optimization in a grid connected distributed generation system which supplies a residential LV load. The impact of wind generation on optimal typing and sizing is also considered. In addition, several sensitivity analyses are provided to address different conditions. The expected value of battery properties as well as the real data of load and wind in Iran is used in numerical studies that are developed in HOMER. This study determines that which technology of battery is the most suitable one to be used in wind-based DG systems which are connected to the distribution network, from both technical and economic points of view.
since 2003 in Fairbanks, Alaska (USA), with power rating of 27 MW (15 min discharge time) capable to boost to 40MW (7min). C. Lithium–ion (Li-ion) The first commercial Li-ion batteries were produced in early 1990s. They were first targeted for portable applications but were employed in grid-scale, stationary applications as well. High energy density (200 Wh/kg) and relatively high efficiency (85–90%) have offered sufficient motives for the development of these batteries. The largest Li-ion EES serves at the Laurel Mountain Wind Farm, in Moraine, Ohio supplied by AES Energy Storage. D. Vanadium–Redox Flow Battery (VRFB) The flow batteries store energy in the electrolyte solutions, opposite to the conventional BES in which the electrodes are responsible for this task. Hence, the ratings of power and energy can be designed independently: energy capacity is determined by the quantity of electrolyte stored in external tanks while power rating is designed based on the active area of the cell compartment. It makes flow batteries favorable for both energy and power related storage applications, maintaining a high rate of discharge time up to 10 (h). With relatively low energy density (i.e. 10–75 Wh/kg), limited operating temperature range (i.e. 10–35 °C), and high capital costs, VRFB are yet to be commercialized for grid-scale applications. However, their flexibility in discharge time, power rating and energy capacity motivates further research for developing VRFBs. The largest reported VRFB is a 3 MW (16 min discharge time) unit at Sumitomo's Densetsu Office, in Osaka, Japan, targeted for peak shaving.
II. BATTERY ENERGY STORAGE TECHNOLOGIES Rechargeable battery energy storage (BES) comprises a wide range of technologies based on the material used in electrodes and electrolytes, and the functioning system. The most important parameters of a BES used in optimization are the investment cost of capacity (in $/kWh), the investment cost of power rating (in $/kW), replacement cost (in $/kWh), operation and maintenance cost (in $/kW-year), the efficiency (in percent), depth of discharge (DoD) (in percent) and the lifetime (in number of charge/discharge cycles). In this paper, the following types of BES are considered for planning: 1) Sodium–Sulfur (NaS) 2) Nickel–Cadmium (Ni-Cd) 3) Lithium–ion (Li-ion) 4) Vanadium–Redox Flow Battery (VRFB) 5) Zinc–Bromine (Zn-Br) In this section these batteries are briefly reviewed, however, more details can be found in [5].
E. Zinc–Bromine (Zn-Br) The Zn-Br technology is also categorized in flow batteries. Despite having relatively low efficiency (i.e. 60–65 %), Zn–Br batteries offer higher DoD, approximately fully discharged. For Zn–Br batteries the recent estimations show the cost of power rating in the range of 151–595 €/kW, with the average of 444 €/kW. The storage cost and replacement costs (after 15 yr) are approximately 195 €/kWh, for bulk energy storage and transmission and distribution applications with 365–500 cycles per year. One of the challenges in storage planning is that there is not specified value for economic and technical parameters such as the capital cost ($/kWh) and efficiency of the batteries in literature. For example, the box plots of battery capacity cost are shown in Fig. 1, which is based on several references of [5]. It is assumed that 1 (€) is approximately equal to 1.22 ($). Here, the expected values of all the uncertain parameters are used in case studies. The expected value of uncertain parameters of different technologies is shown in Table 1.
A. Sodium–Sulfur (NaS) NaS batteries have been developed by NGK Insulators and Tokyo Electric Power since 1987. The batteries are one of the most proven electrochemical storage technologies in MW scale, with projected total installations of 606 MW by 2012. NaS batteries have shown capabilities in power quality applications and power time shift, with relatively high overall efficiency (75–85%), 2500–4500 life cycles, expected lifetime of 15 yr, and discharge time up to 7 h. The largest project of NaS with 70 MW power has been developed in Italy, 2014. B.
Nickel–Cadmium (Ni-Cd) Ni-Cd batteries are among the oldest BES technologies that are further developed since 1990s. They offer relatively high energy density (55–75 Wh/kg), low maintenance need, and life cycles between 2000 and 2500. The life cycle is highly depended on DoD. Ni-Cd batteries have served in different applications from power quality and emergency reserve to telecommunication and portable services. The world's largest Ni-Cd battery, and the US largest BES, has been in operation
III.
PARAMETERS OF THE SYSTEM UNDER STUDY
The typical system which is connected to the distribution grid, supplies a residential load. The AC bus is connected to
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20th Electrical Power Distribution Conference, 28-29 April 2015, Zahedan, Iran
Type of battery NaS Ni-Cd Li-ion VRFB Zn-Br
Capacity cost ($/kWh) 363 951 970 569 238
TABLE I. EXPECTED VALUE OF BATTERY PROPERTIES [5] Power rating cost Replacement cost O&M Cost ($/kW) ($/kWh) ($/kW-year) 446 219 4.4 291 640 13.4 564 450 8.4 597 158 10.3 541 238 5.2
Efficiency (%) 83 67 90 75 65
Lifetime (Cycles no.) 2920 3650 2162 2920 5475
Fig. 1. Box plots of storage capacity cost as uncertain parameter [5]
the DC bus using AC/DC converter. The battery and wind turbine are linked to the DC bus according to Fig. 2.
Fig. 3. Load profiles of the system in 12 months
Fig. 2. Configuration of the system under study
A. Load demand and energy price The load profiles, within 12 months of a year, are shown in Fig. 3 which is based on the real data of a distribution network in Azarbaijan, Iran. In the base case, the average demand is 4065 (kwh/d) with the peak load of 300 (kW). The price of electrical energy is based on the three-level price in Iran. It is different considerably in two sections of a year, as shown in Fig. 4. The energy price in peak load is twice greater than that in normal load, and the price in normal load is twice more than that in light load. In other words, the relation among the peak price, normal price and light price is 2. This coefficient, which is shown here by PF, may vary in different conditions.
Fig. 4. Electrical energy price in two sections of a year
higher in winter, while the least wind power is provided in summer. In addition, a typical wind turbine, shown in [14], is considered to be used in numerical studies. The maximum wind power penetration is 15 (%) in this study. C. Btteries The parameters of the batteries are according to Table I. D. Convertor cost The investment cost of convertor is assumed to be 560 ($/kW), and the O&M cost is 35 ($/year). E. Distribution grid It is assumed that the power from the grid is unlimited with the price shown in Fig. 4. This assumption let us discover that
B. Wind data The wind speed is based on the real data of wind in Ganjeh, Iran, as shown in Fig. 5. It can be seen that the wind speed is
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20th Electrical Power Distribution Conference, 28-29 April 2015, Zahedan, Iran under which conditions the batteries would be economically comparable with the power from the grid.
than 310 (kW), the optimal capacity of various BES technologies is different. Among all, the Li-ion battery has the least capacity, and the maximum capacity belongs to the ZnBr and Ni-Cd technologies. The reason is that the Li-ion has the most efficiency, while the efficiency of the Zn-Br and NiCd batteries is the lowest. On the other hand, the optimal capacity of all the batteries is zero, if the peak load becomes less than 300 (kW). As a result, using BES technology is not economical for the systems having the peak load less than 300 (kW). Although using the Li-ion BES results in the lowest battery capacity, it is not the most economic battery, because of higher investment cost. In order to discover the most economical BES, the index of COE (cost of energy) should be investigated, as shown in Fig. 7.
F. The other parameters The annual real interest rate is assumed to be 6 (%), and the lifetime of the project is 25 (years).
(a)
Fig. 7. Cost of energy versus the peak load for different technologies
As can be seen, the most economical batteries are Zn-Br and VRFB, while the Ni-Cd technology results in the highest cost. According to the results in Fig. 6 and Fig. 7, it is not critical to select which type of technology, when the peak load is less than 310 (kW); however, the difference is considerable for the peak loads greater than 310 (kW).
(b) Fig. 5. The average value of wind speed in 12 months in Ganjeh: a) box plots, b) time series
IV.
NUMERICAL RESULTS
In this section, the numerical results are presented through some scenarios.
B. Scenario 2 In this scenario, the impact of PF coefficient (i.e. the price factor defined in Section III.A) on optimal typing of BES is addressed. Here, the wind energy is neglected to investigate the optimal BES typing in energy systems without renewable resources. The results are presented in Fig. 8. It shows the COE increases as the PF increases; however, the best choice is the Zn-Br technology in all values of PF.
A. Scenario 1 As the first scenario, the optimal capacity of the batteries are obtained for different values of peak load. The result of optimal sizing is shown in Fig. 6.
Fig. 6. Optimal capacity of batteries versus peak load of the system Fig. 8. The effect of PF on optimal typing of BES without wind power
According to this figure, the optimal capacity increases as the peak load raises. However, when the peak load is greater
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20th Electrical Power Distribution Conference, 28-29 April 2015, Zahedan, Iran [2]
C. Scenario 3 The impact of wind energy on optimal BES typing is considered in this scenario. Fig. 9 displays the COE of the system versus the PF, in presence of wind energy. It reveals that the Zn-Br is the best technology in the base case i.e. at PF 2 . However, the NaS technology is better than Zn-Br when the PF is equal to 2.2 and 2.5. As a result, the NaS technology may be an alternative when the wind power is considered in grid connected distributed energy systems.
[3]
[4]
[5]
[6]
[7]
[8]
[9] Fig. 9. The effect of PF on optimal typing of BES considering wind power [10]
V. CONCLUSIONS [11]
In this paper, the simultaneous optimal sizing and typing of battery energy storage in a grid connected DG system was presented. The most famous technologies i.e. NaS, Ni-Cd, Liion, VRFB and Zn-Br were considered to determine which technology is the best choice, from both technical and economic points of view. The literature review showed there is not specified values for the parameters of the batteries, so, the expected value of parameters were used in case studies. The average parameters represent that the most expensive technologies e.g. Li-ion, have a great efficiency, while the efficiency of the cheapest ones e.g. Zn-Br, is poor. Among all, the parameters of NaS technology are in the most moderate situation i.e. they are not very high or low. Hence, without the exact case studies, it is not clear which technology is the most suitable in different conditions. The numerical results, in this paper, showed that the high efficiency results in the low capacity; however, it does not bring economic advantages. As a result, the Zn-Br is the most suitable technology generally, while the VRFB and NaS technologies can be used as alternatives in some special conditions. It is notable that these results are based on the grid connected systems, and may not be valid for other cases such as stand alone systems. However, the sensitivity analyses, shown in this paper, generalize the conclusions for different conditions in the grid connected systems.
[12]
[13]
[14]
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