Consideración de Nuevas Inversiones

1.1 Energy in buildings and districts

Sustainable development is the ability to fulfill the requirements of current generation without disturbing the future generations to sustain theirs [1]. Most traditional forms of energy such as coal, petroleum and natural gas are non-renewable sources of energy and will be depleted in the near future [2, 3]. Use of renewable energy and an increase in energy efficiency are two essential solutions to address the current energy crisis [4].

In the recent years, substantial energy is spent in building sector where 46% of the total worldwide energy demand can be attributed to heating and cooling [5]. In addition to the availability of nonrenewable energy forms, environmental impacts associated with power production from these nonrenewable energies stresses the development of more efficient and sustainable heating/cooling and energy distribution strategies. District heating systems (DHSs) are found to be a promising technology to address sustainability in building-related energy production and distribution [6].

1.2 Necessity of energy storage

As energy systems become more complex (in both supply and demand), mechanisms are being sought by which greater control for variability and unpredictability can be adopted. At the district level, where heating and/or cooling networks can exist, energy storage can provide such control. Such districts vary in size, from tens of buildings connected to a small gas engine in London, UK [7], through hundreds of properties in Lieni, Italy [8] and Southern Austria [9], to a 974 km district network within Vienna, Austria [10] or even a 1,300 km district heating network connecting 19 energy centers in Berlin, Germany [11]. New thermal energy storage (TES) vessels are often the focus, but innovative methods are also considered for storing thermal energy, using the existing building stock thermal mass [12] and district heating pipework [10]. This section discusses the necessity of energy storage within building and district energy systems.

1.2.1 Profile smoothing

Renewable energy is becoming globally more prevalent as a source of heat and electricity; however, it is also inherently intermittent with time and space. To smoothen this varying supply, it is possible to use energy storage as a buffer. Electrical or thermal storage can be used indirectly, by using peaks in renewable supply to operate electric heaters/chillers [13] or by operating combined heat and power (CHP) plants in renewable supply troughs without wasting the resultant heat output [14, 15]. Solar thermal systems also tend to be optimized with storage in mind, either at high temperature preceding use through a Rankine engine (as is the case for concentrated solar power [16]) or at low temperature for direct use in a heating network [17].

Less intermittent than renewables (but equally variable) is the demand for electricity, heating, and cooling. Supply technologies are conventionally designed to meet the peak demand,

but could be sized smaller with the installment of storage [18-20]. By operating the supply to meet average demand, excess energy can be stored for use during peak demands, reducing the pressure on supply.

1.2.2 Time of use tariffs

Profile smoothing is beneficial to allow for intermittency and to reduce capacity requirements of the supply technologies. However, the same capability provided by storage to decouple supply from demand can be used purely for operational economic gain. Given a large enough swing in electricity wholesale price, significant economic gain can be achieved from operating CHP plants at the right time of day and selling the produced electricity to the grid [7, 21-24]. In fact, some argue that thermal storage in a district system is only beneficial with sufficient variation in wholesale electricity price [7, 22, 25]. Conversely, electricity can be purchased at off- peak times to operate chillers, reducing operating costs [18].

1.2.3 Efficiency improvements

Off-peak electricity wholesale pricing hours tend to be overnight, when the temperatures are lower. By operating cooling systems at this time, not only the electricity purchasing is cheaper, but also enhancement in efficiency can be realized directly in the technologies and via the cooling towers [26]. Thermal storage is then utilized to meet cooling demands when temperature increases during the day and buildings are occupied.

Loading of a given technology also affects its efficiency, with certain cooling technologies operating more efficiently at partial load rates, which can be maintained if supply is decoupled from demand by use of storage [27]. Avoiding excessive cycling (to meet varying demands) can also have the added benefit of extending technology lifetime and reducing maintenance requirements [28].

1.2.4 Seasonal variations

Short-term storage is widely found in actual and modeled systems; however, seasonal storage could also be used. Cooling in summer can be matched to heating in winter for potentially greater economic gain than considering the systems separately in the short-term [29].

1.3 Content organization

Energy storage technologies can be generally classified in two major categories of thermal and electrical energy storage. These technologies and their mechanisms are covered in Chapter 2, introducing storage systems.

To support the optimum integration of TES into future building energy systems, benefits of TES should be quantified during decision making processes at policy, strategy, concept design and detailed design stages. Modeling has a key role in providing this quantification and underpinning future standards, regulations, guidance and design methods for effective TES integration. In general, modeling can be viewed as supporting three different domains with different requirements on modeling outputs (see Table 1.1):

(1) Policy, scoping and concept design, regulation compliance (2) Detailed system design

(3) System automation design and operation.

Table 1.1: Modeling requirements for different levels and domains

Scale Component Building District Regional Policy, scoping/concept design, regulatory compliance ✓ ✓ ✓ ✓

Detailed system design ✓ ✓ ✓

System automation design and operation ✓ ✓ ✓

The integration of TES primarily requires that materials, components, and local interactions are characterized, and their behavior are captured in models which allow these to represent TES systems in the design process. Thereafter, these TES system characteristics must be appropriately integrated within constructions or plant models for their behavior to be correctly comprehended within building or district models in the higher-level design processes. In turn, the TES characteristics at building level should be comprehended in district or regional level models. Therefore, energy storage applications in buildings (including component level) are discussed in Chapter 3, while Chapter 4 is devoted to the district level. These chapters cover the fundamentals of energy storage, introduce available tools, provide state-of-the-art examples, etc. Note that this publication is not focused on the regional or national level.

Once a system is modeled, optimization can be carried out based on several criteria. This is the subject of Chapter 5 with a focus on energy storage. First, common optimization methods and algorithms are explained. Then, common objective functions and decision parameters for energy storage are presented. Existing tools for optimization at building and district levels are elaborated. Thereafter, due to the complicated nature of district level optimization, some computational time deduction methods are covered. Further, examples based on some recent studies are provided to illustrate how optimization can be applied to energy storage in buildings and districts.

In order to evaluate the effectiveness of energy storage technologies in building/district applications, key performance indicators (KPIs) are important for analyzing the interactions among economic, human activity, energy consumption and GHG emissions [30]. Therefore, Chapter 6 first reviews the existing KPIs and then introduces ten KPIs in detail which are later used at the end of Chapter 6 to evaluate Annex 31 case studies. The chapter also introduces some other advanced KPIs.

Finally, Chapter 7 concludes the publication by explaining the achievements of Annex 31 as well as providing recommendations for the future work.