Mechanical Energy Storage Systems (MESS)

1.1 Kinetic Energy Storage Systems: Flywheel Energy Storage (FES)

   A flywheel is a device which is used to store rotational energy (kinetic energy) [Beacon Power, 2012]. This device was commonly used in combination with a motor/generator to supply emergency power in the case of an interruption of the primary source. The original disadvantages of flywheels were their high initial costs (increasing the running energy costs) and long and frequent periods of repair compared to static systems (such as batteries). However, technology developments have enabled the emergence of a new type of flywheels, such as the “Beacon Power Flywheel (BPF)”. The main principle of operation of the BPF is that it uses a vacuum chamber and magnetic bearing to house the rotors, minimising losses and wear as a consequence [DTI, 2006]; a motor/generator is mounted on the shaft of the rotors [Rounds and Peek, 2009; Beacon Power, 2012]. Fig. 1 shows a general topology of a FES system, however, the technology and diagram of BPF is a bit more complicated than that shown in Fig. 1; see [Beacon Power, 2012] for more detailed information.

Fig. 1: A general topology of a FES system (adapted from [Beacon Power, 2012]).

 

 The energy stored in a rotating flywheel can be calculated as follows [DTI, 2006]:

Where:

 Kinetic energy [Joules]

Moment of inertia of the rotor [ kg*(m^2)]

Rotational rotor speed [rad/s]

   Therefore, the storage capacity in a rotor can be increased by incrementing its inertia or its rotational speed. However, increasing the mass (in order to increase the inertia) might provide difficulties in the installation [DTI, 2006]. Therefore, the main objective of “Beacon Power”  focuses on taking full advantage of the rotational speed (i.e. increasing it).

    Referring to the Fig. 1, at the time of charging, the flywheel’s motor acts as a load drawing power from the system to increase the speed of the rotor (power in). At the time of discharging the motor is changed to a generator mode and the rotor kinetic energy is used to drive the generator; the electrical energy obtained is supplied back into the network (power out) [Rounds and Peek, 2009; Beacon Power, 2012].

   The Beacon Power Flywheels (BPF’s) are classified as high–speed flywheels. Currently, the “Beacon technology” allows the rotors to be operated at speeds between 8,000 and 16,000 rpm [Rounds and Peek, 2009] and the estimated life of these flywheels is around of 20 years [DTI, 2006]. The efficiency estimated for a flywheel system is about 90% [PIER, 2011].

 1.2 Pumped Hydro Storage (PHS)

   Fig.2 shows a general topology of a Pumped Hydro Storage (PHS) system. These types of storage system collect the water from creeks and/or rivers and store it in an upper reservoir (commonly under off–peak demand). Therefore, the energy is stored as potential energy. The potential energy is transformed back into electrical energy in the same way as is done in traditional hydro power plants: the water goes through a turbine which is connected to a generator. The energy stored is most commonly used to meet peak demands [Wagner and Mathur, 2011]. The 1,730 MW Dinorwig pumped hydro storage system in the UK is an example of a large scale application of this type of energy storage systems [DTI, 2006].

   This energy storage process implies some losses. Electrical power is needed to pump the water into the upper reservoir; therefore, losses due to electrical and mechanical equipment are present. When the water flows down, again losses are present as well. About the 20% of the energy used in the whole process is lost, and about the 80% of the energy is recovered [Wagner and Mathur, 2011]. Also, this type of energy storage system needs long construction times and high capital costs for both the plant and transmission lines (since it depends on specific geographic locations which are commonly far away from consumption centres) [PIER, 2011].

Fig. 2: A general topology of a PHS system (adapted from
[Wagner and Mathur, 2011]).

   However, PHS seems to be the best choice of energy storage since, similar to common hydro power stations, it has the ability for almost instantaneous starting and stopping. Therefore, this type of energy storage is a good choice to compensate peak demands. Also, its operation, generation cost and maintenance are lower than other type of energy storage. It also has a high efficiency (about 80%) [Wagner and Mathur, 2011] compared with other energy storage technology. To see a list of the largest PHS systems in the world, visit [Carmona Sanchez, 20015] or [Wagner and Mathur, 2011].

1.3 Compressed Air Energy Storage (CAES)

   The common way of working in this type of energy storage system is to store air during off–peak hours through the use of compressors. Then, during the peak hours, the compressed air is usually used in combination with a modified gas turbine to generate electricity [DTI, 2006]. Electrical power generated by Wind energy could also be used to compress the air when generation exceeds demand [DTI, 2006]. Due to the large amount of air required, CAES systems are commonly composed of an underground cavern or chamber. Such a cavern is used to store compressed air, see Fig. 3.

Fig. 3: A general topology of a CAES system (adapted from [PIER, 2011]). 

   CAES systems were first developed for combustion turbine systems [DTI, 2006]. This type of energy storage system has a low efficiency (about 50%) and also it requires specific geographic locations for large–scale storage since man–made tanks are only suitable for small–scale storage [PIER, 2011].

References:

[Beacon Power, 2012] Beacon Power, LLC: http://www.beaconpower.com/, accessed: 04/12/2012.

[Carmona Sanchez, 2015] J. Carmona Sanchez. “A Smart Adaptive Load for Power-Frequency Support Applications”. PhD Thesis, Power Conversion Group, The University of Manchester, UK, December 2015. Available at: https://www.escholar.manchester.ac.uk/uk-ac-man-scw:300748

[DTI, 2006] Department of Trade and Industry  (DTI). “Electrical Energy Storage Systems – A mission to the USA”. Report of a DTI GLOBAL WATCH MISSION, December 2006.

[PIER, 2011] Public Interest Energy Research (PIER) Program. “2020 Strategic Analysis of Energy Storage in California”. Final Project Report. California Institute for Energy and Environment – University of California: California Energy Commission. November 2011.

[Rounds and Peek, 2009] Robert Rounds and Georgianne H. Peek. “Design & Development of a 20–MW Flywheel–based Freqeuncy Regulation Power Plant: A Study for the DOE Energy Storage Program”. SANDIA REPORT SAND2008–8229, Unlimited Release, Printed January 2009.

[Wagner and Mathur, 2011] Herman–Josef Wagner and Jyotirmay Mathur. Introduction to Hydro Energy Systems: Basics, Technology and Operation. Springer–Verlag Berlin Heidelberg 2011.

SmartGrids

   Many countries around the world have started the modernisation, upgrade and renovation of electrical power networks with the use of renewable energy, advanced demand side management and distributed generation management, the installation of new meters (called smart–meters), microcontrollers and advanced control methods for the nonlinear loads. The resulting network, with a greater degree of flexibility, better control and more efficiency, is called a “Smart Grid” (others names used are Intelligrid, GridWise, FutureGrid, etc. [Li et al., 2010]). 

   A SmartGrid is composed of smart–networks (transmission and distribution), smart–substations, smart–loads, smart–meters, microgrids, etc. [Palensky and Dietrich, 2011; Lasseter, 2011]. A general SmartGrid topology is given in Fig. 1.

   There are two important parts in the development of SmartGrids, on one side the transmission system (on the other side the distribution system); this includes [Li et al., 2010]:

a) Smart Control Centres

b) Smart Transmission Networks

c) Smart Substations

   The actual development of Smart–Control Centres, Smart–Transmission Networks and Smart–Substations is built on existing infrastructure. The main reasons for developing a smart transmission system are that in many countries these systems are working near their operational limits and the available and suitable space for adding new transmission lines has been decreased considerably [Li et al, 2010] and consequently it is difficult to acquire additional rights of way [Hingorani and Gyugyi, 2000]. 

 Fig. 1: A general SmartGrid topology (with information from [Lasseter, 2002, 

Barnes et al., 2007; Li et al., 2010, OECD/IEA, 2010; Lasseter, 2011]).

References:

Main source: J. Carmona Sanchez. “A Smart Adaptive Load for Power-Frequency Support Applications”. PhD Thesis, Power Conversion Group, The University of Manchester, UK, December 2015. Available at: https://www.escholar.manchester.ac.uk/uk-ac-man-scw:300748

[Barnes et al., 2007] Mike Barnes, Junji Kondoh, Hiroshi Asano, Jose Oyarzabal, Giri Ventakaramanan, Robert Lasseter, Nikos Hatziargyriou and Tim Green. “Real–World MicroGrids–An Overview”. Proceedings of the IEEE AES International Conference on System of Systems Engineering (SoSE), Vol. w/o, No. w/o, pp. 1–8, San Antonio, Texas, USA, 16th–18th April 2007.

[Hingorani and Gyugyi, 2000] Narain G. Hingoranl and Laszlo Gyugyi. Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems. IEEE Press. IEEE Power Engineering Society, Sponsor. John Wiley & Sons, 2000.

[Li et al., 2010] Fangxing Li; Wei Qiao, Hongbin Sun, Hui Wan, Jianhui Wang, Yan Xia, Zhao Xu, and Pei Zhang. “Smart Transmission Grid: Vision and Framework”. IEEE Transactions on Smart Grid, Vol. 1, No. 2, pp. 168 – 177, September, 2010.

[Lasseter, 2002] Robert H. Lasseter. “MicroGrids”. Proceedings of the IEEE Power Engineering Society Winter Meeting, Vol. 1, No. w/o, pp. 305–308, New York, NY, USA, 27th – 31st January 2002.

[Lasseter, 2011] R.H. Lasseter. “Smart Distribution: Coupled Microgrids,” Proceedings of the IEEE, Vol. 99, No. 6, pp. 1074–1082, June, 2011.

[OECD/IEA, 2010] © OECD/IEA (Organisation for Economic Co–operation and Development)/( International Energy Agency). “Energy Technology Perspectives 2010: Scenarios and Strategies to 2050”. IEA Publications, July 2010.

[Palensky and Dietrich, 2011] Peter Palensky and Dietmar Dietrich. “Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads”. IEEE CS Transactions on Industrial Informatics, Vol. 7, No. 3, pp. 381–388, August 2011.

Air-Conditioning Principle of Operation

“In an air–conditioning system, heat is transferred mechanically from room air to the outdoor air to establish human comfort [Miller and Miller, 2006]”.

1.1 Heat and Pressure

    The state (solid, liquid or gas) of a substance depends on its amount of heat and pressure. The “heat content” of a substance is composed of “sensible heat” and “latent heat”. When sensible heat is added/subtracted to a substance, it affects its temperature without changing its state. The heat require to change the state of a substance, e.g. from solid to liquid, is called “latent heat”; this type of heat does not affect the temperature of the substance [Miller and Miller, 2006].

    Additionally, a change in pressure affects the solidification, liquefaction and vaporization points of a substance. For example, water vaporizes at 100°C at a pressure of 14.7 psi (pounds per square inch). However, at a pressure of 10.1 psi, water vaporises at 89.4 °C. Hence, if the water were at a temperature of 89.48°C and a pressure of 14.7 psi, it would remain liquid, however, if its pressure were dropped to 10.1 psi, then the water would vaporize at this temperature [Miller and Miller, 2006].

1.2 Air–Conditioning System

     Air–conditioning systems and refrigeration take advantage of the principles explained in previous section 1.1. As an example, imagine a substance which is liquid at a pressure of 100 psi, but vaporizes at sea level atmospheric pressure (14.7 psi). This substance (liquid) contained in a tank (Fig. 1A, see below), which is at 100 psi, is released into a long coil of tubing, via an expansion valve, to the atmosphere. According to the principle of thermal expansion, matter expands when heated. This implies an increase in its linear dimensions and volume. The opposite effect is obtained when heat is removed from a substance [Miller and Miller, 2006]. When the liquid enters the coil, its pressure is reduced, and consequently so is its vaporization point. Part of the liquid becomes gas by using its own heat; the remaining liquid takes heat from the coil and vaporizes as well. This implies reducing the temperature of the coil and consequently the temperature of the surrounding air. This process, of cooling the surrounding air, will continue as long as the tank releases the pressurised substance. In an air conditioning system, the cycle is closed by recovering the substance after it has done its job of cooling [Miller and Miller, 2006]. The full cycle in an air conditioning system is shown in Fig. 1B. A general control layout of an air–conditioning system is shown in Fig. 1C.

Fig. 1: Air–conditioning System and its Control by the use of AC drives. A) Principle of operation, B) Full Air-Conditioning Cycle and C) General Control Layout of an Air–conditioning System (A and B adapted from [Miller and Miller, 2006] and C adapted from [Mohan et al., 2003]).

References:

Main source: J. Carmona Sanchez. “A Smart Adaptive Load for Power-Frequency Support Applications”. PhD Thesis, Power Conversion Group, The University of Manchester, UK, December 2015. Available at: https://www.escholar.manchester.ac.uk/uk-ac-man-scw:300748

[Miller and Miller, 2006] Rex Miller and Mark R. Miller. “Air Conditioning and Refrigeration”. McGraw-Hill. 2006.

[Mohan et al., 2003] N. Mohan, T. M. Undeland and W. P. Robbins. “Power Electronics: Converters, Applications and Design”. Third Edition, John Wiley and Sons Inc., 2003.

On the Evolution of Electric Power Networks

Fig. 1.1: One–line diagram of a typical electric power network.

A typical Electric Power Network (EPN) can be divided into three main parts, namely: generation, transmission and distribution, Fig. 1.1. These have had many improvements since their emergence in 1880s (see Fig. 1.2). The first complete electric network (developed in 1882) was based on the DC theory. However, since electrical energy losses are dependent on the value of  R*(I^2) (the resistance times the square of the current), the voltage level has to be high to minimise losses. DC technology had not developed enough to transmit electric power over long distances at that time. The emergence of AC theory (mainly the AC transformer) allowed the transmission of electric energy over long distances, and as a consequence, the use of DC systems was gradually reduced, and for a long time more attention was paid to the developments of AC equipment [Kundur, 1994]. However, advances in power electronics and state solid technology gave the basis for the rise of DC equipment from the 1950’s onward, initially, for high power applications [Kundur, 1994; Li et al., 2010], Fig. 1.2.

Fig. 1.2: The electric power networks evolution (with information from [Moore, 1935; Burns, 1988; Kundur, 1994; Drury, 2009; Li et al, 2010; Lasseter, 2011; Siemens, 2011]).

The Present and Future of Electric Power Networks

At present, large parts of electric power networks are based on AC current and their infrastructure is largely based on the same principles as the first power systems constructed 120 years ago [Peretto, 2010; Palensky and Dietrich, 2011]. However, in Europe and North America, many power transmission systems are reaching their operational limits and older generation plant is nearing the end of its usable life and will need replacing, leaving room for the interconnection of renewable energy. In Asia, Africa, and Central and South America power networks are expanding rapidly [OECD/IEA, 2010].

Additionally, with the introduction of computer systems in the 80’s, loads requiring “Digital Quality” (critical computers systems, data systems, etc.) have increased as well [DTI, 2006]. It is expected that by 2030, electric energy consumption in the world could increase by about 50% [Peretto, 2010]. Other sources forecast that global electricity demand will rise by 65 % from 2014 to 2040. About 85% of the electricity rise will be due to developing economies. Fig. 1.3 outlines the worldwide forecast of electricity demand by sector and by region for 2040 [ExxonMobil, 2016].

Fig. 1.3: a) Worldwide forecast of electricity demand by sector and b) Forecast Electricity Demand by Region (Adapted from [ExxonMobil, 2016]).

References:

Main source: J. Carmona Sanchez. “A Smart Adaptive Load for Power-Frequency Support Applications”. PhD Thesis, Power Conversion Group, The University of Manchester, UK, December 2015. Available at: https://www.escholar.manchester.ac.uk/uk-ac-man-scw:300748

[Burns, 1988] R. W. Burns. “Book Reviews: An Early History of Electricity Supply — The Story of the Electric Light in Victorian Leeds”. Proceedings A of the IEE – Physical Science, Measurement and Instrumentation, Management and Education – Reviews, Vol. 135, No. 6, pp. 362, July 1988.

[DTI, 2006] Department of Trade and Industry  (DTI). “Electrical Energy Storage Systems – A mission to the USA”. Report of a DTI GLOBAL WATCH MISSION, December 2006.

[Drury, 2009] Bill Drury. “Control Techniques Drives and Controls Handbook”. 2nd Edition. Institution of Engineering and Technology (IET): Power and Energy Series 57, 2009.

[ExxonMobil, 2016] Exxon Mobil. "The Outlook for Energy: A View to 2040".  Exxon Mobil Corporation, 2016.

[Kundur, 1994] P. Kundur. “Power System Stability and Control”. First Edition, McGraw–Hill: EPRl Power System Engineering Series, 1994.

[Lasseter, 2011] R.H. Lasseter. “Smart Distribution: Coupled Microgrids,” Proceedings of the IEEE, Vol. 99, No. 6, pp. 1074–1082, June, 2011.

[Li et al., 2010] Fangxing Li; Wei Qiao, Hongbin Sun, Hui Wan, Jianhui Wang, Yan Xia, Zhao Xu, and Pei Zhang. “Smart Transmission Grid: Vision and Framework”. IEEE Transactions on Smart Grid, Vol. 1, No. 2, pp. 168 – 177, September, 2010.

[Moore, 1935] A. E. Moore. “The History and Development of the Integrating Electricity Meter”. Journals of the IEE, Vol. 77, No. 468, pp. 851–859, December 1935.

[OECD/IEA, 2010] © OECD/IEA (Organisation for Economic Co–operation and Development)/( International Energy Agency). “Energy Technology Perspectives 2010: Scenarios and Strategies to 2050”. IEA Publications, July 2010.

[Palensky and Dietrich, 2011] Peter Palensky and Dietmar Dietrich. “Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads”. IEEE CS Transactions on Industrial Informatics, Vol. 7, No. 3, pp. 381–388, August 2011.

[Peretto, 2010] Lorenzo Peretto. “The Role of Measurements in the Smart Grid Era”. IEEE IMS Instrumentation & Measurement Magazine, Vol. 13, No. 3, pp. 22–25, June 2010.

[Siemens, 2011] Siemens. "Siemens Debuts HVDC PLUS with San Francisco’s Trans Bay Cable". Living Energy, The Magazine for International Energy Leadership, Issue 5, July 2011.