METHOD IN ASSOCIATION THERETO

Field Of Invention

The present disclosure generally relates to a renewable energy-based system, and a method of control (i.e., a control method) in association with the renewable energy- based system. The present disclosure, further, generally relates to an apparatus in association with one or both of the renewable energy-based system and the control method.

Background

A system such as a heating system or a cooling system can be driven by manner of renewable energy. Such a system can generally be referred to as a renewable energy-based system.

Renewable energy can generally be derived based on renewable sources such as solar (i.e., sunlight), wind, rain, geothermal heat and/or waves etc.

For example, a heating system can be operationally powered via a renewable energy source (e.g., solar).

The present disclosure contemplates that a renewable energy-based system may be subject to various inefficiencies and/or reliability issues. Therefore, the present disclosure contemplates that there is a need to improve the manner in which a renewable energy-based system can be operated.

Summary of the Invention

In accordance with an aspect of the disclosure, a control method is provided. The control method can correspond to a method of control in association with a renewable energy-based system. The control method can include obtaining real-time data and obtaining historic data. The control method can further include processing the historic data in a manner so as to obtain projection data. The control method can yet further include processing the real-time data and the projection data to generate at least one control signal. The control signal(s) can be communicated to the renewable energy-based system. Moreover, the control signal(s) can include at least one control parameter for controlling at least one portion of the renewable energy-based system.

In accordance with another aspect of the disclosure, an apparatus is provided.

The apparatus can include a receiving module, a processing module and a transmission module. The receiving module can be coupled to the processing module. The processing module can be coupled to the transmission module. The receiving module can be configured to receive real-time data and projection data. Additionally, the processing module can be configured to process the real-time data and the projection data in a manner so as to generate at least one control signal. Moreover, the transmission module can be configured to transmit at least one control signal.

The control signal can be communicated to a renewable-energy based system for controlling at least a portion of the renewable-energy based system.

In accordance with yet another aspect of the disclosure, there is provided a renewable energy-based system.

The renewable-energy based system can include an operational portion suitable for heating water. The renewable-energy based system can further include a harvesting portion which can be configured to harvest renewable energy and convert the harvested renewable energy into supply for powering the operational portion so as to facilitate the heating of water. The renewable-energy based system can yet further include a processing portion which can be configured to receive and process real time data and projection data in a manner so as to generate at least one control signal. Moreover, the renewable-energy based system can include a control portion which can be configured to receive the control signal, and based on the control signal, configured to optimize operation of the operational portion. Brief Description of the Drawings

Embodiments of the disclosure are described hereinafter with reference to the following drawings, in which:

Fig. 1 shows a renewable energy-based system, according to an embodiment of the disclosure;

Fig, 2a shows a control method in association with the renewable energy-based system of Fig. 1 , according to an embodiment of the disclosure; Fig. 2b shows an apparatus in association with one or both of the renewable energy- based system of Fig. 1 and the control method of Fig. 2a, according to an embodiment of the disclosure;

Fig. 3a shows an example implementation of the renewable energy-based system of Fig. 1 wherein the renewable energy-based system can correspond to a Solar Thermal Water bleating (STWH) system, according to an embodiment of the disclosure;

Fig. 3b shows an energy management framework associated with the STWH system of Fig. 3a, according to an embodiment of the disclosure;

Fig. 3c shows the example implementation of Fig. 3a in further detail, according to an embodiment of the disclosure; and Fig. 4 and Fig. 5 show a set of graphs and a set of tables, respectively, in connection with a simulation based validation of the energy management framework of Fig. 3b, according to an embodiment of the disclosure. Detailed Description

The present disclosure contemplates that a control method (e.g., an energy management framework which can include one or more control strategies) in association with a renewable energy-based system (e.g., a solar thermal water heating system), and can be applicable in relation to residential buildings and commercial buildings such as industrial plants.

Additionally, the present disclosure contemplates the possibility of obtaining/capturing real-time data (e.g., system state data in relation to the solar thermal water heating system) for adjustment of control strategies as well as further energy-based analysis. This can allow the possibility of prediction/projection (e.g., generating projection data) indicative of critical future information such as peak periods of electric power and water demand so as to facilitate control scheduling. Hence the, for example, solar thermal water heating system can be considered to have awareness of critical future information.

With real-time data and projection data (e.g., predicted information), the aforementioned control strategies can be developed and/or designed in a more flexible manner, and can be made optimal for the operation of the, for example, solar thermal water heating system.

The foregoing will be discussed in further detail with reference to Fig. 1 to Fig. 5 hereinafter. Referring to Fig. 1 , a renewable energy-based system 100 is shown according to an embodiment of the disclosure. The renewable energy-based system 100 can be suitable for the application of, for example, heating of water via the use of a renewable energy source (e.g., sun which provides solar energy). The renewable energy-based system 100 will be simply referred to as system 100 hereinafter. The system 100 can, in one example, be suitable for the application of heating water (i.e., the system 100 can be used for heating water). In another example, the system 100 can be suitable for the application of refining water. In yet another example, the system 100 can be used for cooling air. Other example applications/usages such as cooling of water are also useful.

For the purpose of brevity, the system 100 be discussed in an example context of heating water hereinafter.

The system 100 can include a harvesting portion 102, an operational portion 104, a processing portion 106 and a control portion 108. The harvesting portion 102 can be coupled to any one of the operational portion 104, the processing portion 106, the control portion 108, or any combination thereof. The operational portion 104 can be coupled to any one of the harvesting portion 102, the processing portion 106, the control portion 108, or any combination thereof. The processing portion 106 can be coupled to any one of the harvesting portion 102, the operational portion 104, the control portion 108, or any combination thereof. The control portion 108 can be coupled to any of one the harvesting portion 102, the operational portion 104, the processing portion 106, or any combination thereof. Coupling can generally be by manner of one or both of wired based coupling and wireless based coupling.

In one embodiment, the harvesting portion 102 can be coupled to the operational portion 104. Additionally, the operational portion 104 can be coupled to one or both of the processing portion 106 and the control portion 108. Moreover, the control portion 108 can be coupled to the processing portion 106.

The harvesting portion 102 can include a harvesting part 102a and a conversion part 102b, according to an embodiment of the disclosure. The harvesting part 102a can be coupled to the conversion part 102b. The harvesting part 102a can be configured to harvest renewable energy from a renewable source (e.g., solar, wind, tides) and the conversion part 102b can be configured to convert the harvested renewable energy into a form (e.g., electricity) suitable for powering the operational portion 104. For example, the harvesting portion 102 can correspond to solar-powered photovoltaic (PV) panels, the harvesting part 102a can correspond to one or more solar panels and the conversion part 102b can correspond to one or more PV components.

The operational portion 104 can be suitable for, for example, one or more water heating related operations. For example, the operational portion 102 can be suitable for the application of heating water. In this regard, the harvesting portion 102 can be configured to harvest renewable energy (e.g., from a renewable energy source such as solar) and converting the harvested renewable energy into supply (e.g., electricity) for powering the operational portion 104 so as to facilitate the heating of water. Moreover, as will be discussed later with reference to Fig. 2, the operational portion 104 can be controlled based on a control method. The control method can be based on one or both of the processing portion 106 and the control portion 108.

The processing portion 106 can be configured to receive and process real-time data and projection data in a manner so as to generate at least one control signal. The processing portion 106 can, for example, correspond to a processor (e.g., microprocessor). This will be discussed later in further detail with reference to Fig. 2.

The control portion 108 configured to receive the control signal. Based on the control signal(s), the control portion 108 can be configured to control the operational portion 104. Specifically, the control portion 108 can be configured to optimize operation of the operational portion 104. The control portion 108 can, for example, correspond to a controller type Integrated Circuit (IC) chip. This will be discussed later in further detail with reference to Fig. 3.

To put the foregoing discussion concerning Fig. 1 in context, the present disclosure generally contemplates, according to an aspect of the disclosure, a renewable- energy based system 100 which can include an operational portion 104 suitable for heating water. The renewable-energy based system 100 can further include a harvesting portion 102 which can be configured to harvest renewable energy and convert the harvested renewable energy into supply for powering the operational portion 104 so as to facilitate the heating of water. The renewable-energy based system 100 can yet further include a processing portion 106 which can be configured to receive and process real-time data and projection data in a manner so as to generate at least one control signal. Moreover, the renewable-energy based system 100 can include a control portion 108 which can be configured to receive the control signal, and based on the control signal, configured to optimize operation of the operational portion 104.

Earlier mentioned, the operational portion 104 can be controlled based on a control method. This will now be discussed in detail with reference to Fig. 2 hereinafter. Referring to Fig. 2a, a control method 200 in association with the renewable energy- based system 100 is shown according to an embodiment of the disclosure.

The control method 200 can include a real-time data obtaining step 202, a historic data obtaining step 204, a data processing step 206 and a generating step 208.

With regard to the real-time data obtaining step 202, the present disclosure contemplates that real-time data can include one or more of environmental based data, system state data in relation to the renewable energy-based system, demand data, user-based data and supply data, or any combination thereof.

Environmental based data can, for example, include any one of solar irradiance, wind speed, weather information and ambient temperature associated with the renewable energy-based system, or any combination thereof. Demand data can, for example, include any one of electric power consumption associated with at least one user, water consumption associated with at least one user and heating requirement associated with at least one user, or any combination thereof. The user(s) can be associated with user(s) of the system 100. User-based data can, for example, include one or both of number of users using the system 100 and user preference associated with at least one user. Supply data can, for example, include pricing information associated with any one of electric power, water and gas, or any combination thereof.

With regard to the historic data obtaining step 204, the present disclosure contemplates that historic data can be obtained from a data server (not shown), according to an embodiment of the disclosure. The data server can, in one example, correspond to a third-party system which is not a part of the system 100. The data server can, in another example, be a part of the system 100. In yet another example, a portion of the data server can be a part of the system 100 and another portion of the data server can be outside of the system 100. Moreover, the historic data can be processed in a manner so as to obtain projection data. For example, the control method 200 can include learning one or both of associations and patterns in relation to the historic data so as to obtain/derive projection data, according to an embodiment of the disclosure.

With regard to the data processing step 206, the real-time data and the projection data can be processed (e.g., by a processor) in a manner so as to generate at least one control signal which can be communicated to one or more portions of the system 100.

The control signal can include one or more control parameters for controlling one or more portions of the system 100.

To put the foregoing discussion concerning Fig. 2 in perspective, the present disclosure contemplates a control method 200 which can be associated with a renewable energy-based system 100. The control method 200 can include obtaining real-time data and obtaining historic data. The control method 200 can further include processing the historic data in a manner so as to obtain projection data. The control method 200 can yet further include processing the real-time data and the projection data to generate at least one control signal. The control signal(s) can be communicated to the renewable energy-based system 100. Moreover, the control signal(s) can include at least one control parameter for controlling at least one portion of the renewable energy-based system 100. The control method 200 (real-time data, historic data, projection data, the control signal(s) etc.) will be discussed in further detail with reference in Fig. 3, according to an embodiment of the disclosure.

Referring to Fig. 2b, an apparatus 250, in association with the system 100 and/or the control method 200, is shown, in accordance with an embodiment of the disclosure.

The apparatus 250 can include a receiving module 252, a processing module 254 and a transmission module 256. The receiving module 252 can be coupled to the processing module 254. The processing module 254 can be coupled to the transmission module 256. Each of the receiving module 252, the processing module 254 and the transmission module 256 can be one or both of a hardware-based module and a software-based module.

In one example, the receiving module 252 can correspond to a hardware receiver, the processing module 254 can correspond to a processor (e.g., microprocessor) and the transmission module 256 can correspond to a hardware transmitter. Therefore, each of the receiving module 252, the processing module 254 and the transmission module 256 can correspond to a hardware-based module, in accordance with an embodiment of the disclosure.

In another example, the present disclosure contemplates that software -based transmitter(s) and/or receiver(s) can be a possibility.

The receiving module 252 can be configured to receive the aforementioned real-time data and the aforementioned projection data.

The processing module 254 can be configured to process the real-time data and the projection data in a manner so as to generate at least one control signal.

The transmission module 256 can be configured to transmit at least one control signal. The control signal(s) can be communicated to the system 100 (e.g., a renewable- energy based system) for controlling at least a portion of the system 100. The foregoing will now be discussed in further detail in relation to an example implementation. The example implementation can be in the context of a Solar Thermal Water Heating (STWH) system 300a as will be discussed with reference to Fig. 3 hereinafter. Fig. 3a shows a STWH system 300a, in accordance with an embodiment of the disclosure and Fig. 3b shows an energy management framework 300b, in accordance with an embodiment of the disclosure. Fig. 3c shows the STWH system in further detail, according to an embodiment of the disclosure. Specifically, the system 100 can, for example, correspond to a STWH system 300a in accordance with an embodiment of the disclosure. Moreover, the STWH system 300a can be controlled based on the control method 200 which can be associated with the energy management framework 300b. In this regard, the energy management framework 300b can be associated with the STWH system 300a.

Referring to Fig, 3a, a Solar Thermal Water Heating (STWH) system 300a is shown in accordance with an embodiment of the disclosure. The STWH system 300a can be operated in connection with a building 302 (e.g., residential building and/or commercial building).

As shown, the STWH system 300a can include one or more storage tanks 304 for storing water (e.g., heated water or water to be heated). The STWH system 300a can further include at least one solar thermal collector panel 306 which can be configured to receive solar energy for conversion into supply (e.g., electricity) suitable for heating water stored in the storage tank(s) 304. The STWH system 300a can yet further include one or more auxiliary heaters 308 which can be configured to provide auxiliary heating to water stored in the storage tank(s) 304. Moreover, the STWH system 300a can include one or more circulator pumps 310 and one or more controllers 312. The circulator pump(s) 310 can, for example, be configured to circulate heated water within the STWH system 300a and/or to the building 302. The controller(s) 312 can, for example, be configured to control the STWH system 300a based on the aforementioned control method 200. The STWH system 300a can further include one or more inlet/outlet pipes (not shown) which can serve as conduit(s) for communication of water within the STWH system 300a and/or from the STWH system 300a to the building 302. The STWH system 300a can yet further include one or more electronic components (not shown) and/or one or more on-site sensors (not shown).

In one embodiment, the solar thermal collector panel(s) 306 can, for example, correspond to/relate to the harvesting portion 102. The controller(s) 312 can, for example, correspond to/relate to one or both of the processing portion 106 and the control portion 108. The storage tank(s) 304, the auxiliary heater(s) 308, the circulator pump(s) 310 and/or the inlet/outlet pipe(s) etc. can correspond to/ relate to the operational portion 104.

Generally, the efficiency of the STWH system 300a can be based on well-designed solar thermal collector(s) (i.e., the solar thermal collector panel(s) 306) and proper operation mechanisms.

For the present disclosure, the contemplated STWH system 300a should also be reliable in that not only the efficiency of the solar thermal collector panel(s) 306 is taken into account. The contemplated STWH system 300a further accounts for the operation of auxiliary heater(s) 308 (e.g., heat pumps and/or electric heaters) for producing heat energy in the absence of solar energy.

As such, the present disclosure contemplates an energy management framework, as will be shown in Fig. 3b, which can include one or more dynamic optimized control strategies taking system state data (i.e., also referable to as“system information”) such as the grid information (e.g. electricity price) and water demand information into account, for the operation of solar thermal based heating and the auxiliary heater(s) 308. Such system state data can be current and/or predicted. The aforementioned dynamic optimized control strategy/strategies can be validated experimentally as will be discussed later in further detail.

In operation, the storage tank(s) 304 can be configured to store heat energy produced/extracted from one or both of the solar thermal collector panel(s) 306 and the auxiliary heater(s) 308. Heated water can be supplied from the storage tank(s) 304 to the building 302. Appreciably, the auxiliary heater(s) 308 can function as secondary heating to at least reduce/mitigate disruption to supply of hot water (e.g., in a situation where there is solar energy disruption during cloudy/rainy weather conditions).

Moreover, the present disclosure contemplates that a portion of hot water from the storage tank(s) 304 heated to specific/pre-defined temperature(s) prior to supply to the building 302. For example, the building 302 can include a kitchen zone (not shown) which can have a kitchen tank (not shown). Heat energy (e.g., from the solar thermal collector panel(s) 306 and/or the auxiliary heater(s) 308) can, for example, be stored in the kitchen tank. Appreciably, in this manner, additional back-up heating can be provided in addition to the aforementioned secondary heating. Earlier mentioned, the STWH system 300a can be controlled based on the control method 200 which can be associated with the energy management framework 300b.

The present disclosure contemplates that by implementing the energy management framework 300b in association with the STWH system 300a, improvement(s) in energy efficiency and/or cost efficiency can be possible.

The energy management framework 300b will now be discussed in further detail with reference to Fig. 3b hereinafter. Referring to Fig. 3b, an energy management framework 300b is shown, in accordance with an embodiment of the disclosure. As shown, the energy management framework 300b can include a weather information block 320, a system information block 322, a demand information block 324, a price information block 326, a user information block 328, a historic data block 330 and a projection data block 332. The energy management framework 300b can further include an optimization and control block 334. The energy management framework 300b can yet further include an output block 336.

Any one or more of the weather information block 320, the system information block 322, the demand information block 324, the price information block 326 and the user information block 328, or any combination thereof, can be coupled to the optimization and control block 334.

Moreover, any one or more of the weather information block 320, the system information block 322, the demand information block 324, the price information block 326 and the user information block 328, or any combination thereof, can be coupled to the projection data block 332.

Furthermore, the historic data block 330 can be coupled to the projection data block 332.

Additionally, the projection data block 332 can be coupled to the optimization and control block 334.

The optimization and control block 334 can be coupled to the output block 336.

The aforementioned block(s) can be one or both of hardware-based block(s) and software-based block(s) (i.e., a block can correspond to a hardware and/or software based block). Regarding the weather information block 320, information (i.e., relating to/corresponding to the aforementioned environmental based data) such as solar irradiance, wind speed, ambient temperature can be collected, according to an embodiment of the disclosure. The present disclosure contemplates that such information can be collected from one or more external based systems (i.e., 3 ^rd party system(s) which can be external relative to the STWH system 300a) such as one or more meteorological systems. In this regard, the weather information block 320 can, in one example, be considered to be a hardware-based block. In another example, the weather information block 320 can be considered to be a software-based block in that such information can be obtained from a world wide web-based database associated with the, for example, meteorological system(s).

Regarding the system information block 322, information (i.e., relating to/corresponding to the aforementioned system state data) such as the status of the storage tank(s) 304, the solar thermal collector panel(s) 306, the auxiliary heater(s) 308, the circulator pump(s) 310, the controller(s) 312, the inlet/outlet pipe(s) and/or the electronic component(s) can be collected. The present disclosure contemplates that such information (e.g., pump pressure of the circulator pump(s) 310, water temperature within the storage tank(s) 304, water volume within the storage tank(s) 304 and/or water flow rates via the inlet/outlet pipe(s)) can be obtained through one or more onsite sensors and/or one or more loT (Internet of Things) based devices. In this regard, the system information block 322 can, for example, considered to be a hardware-based block.

Regarding the demand information block 324, information (i.e., relating to/corresponding to the aforementioned demand data) such as electric power, water and/or heat demand can be collected. The present disclosure contemplates that such information can, in one example, be collected from one or more external based systems (i.e., 3 ^rd party system(s) which can be external relative to the STWH system 300a) such as, one or more utilities system. In another example, the aforementioned on-site sensor(s) (which can, for example, be positioned at the inlet/outlet pipe(s) to determine water flow, at the storage tank(s) 304 to determine water consumption and/or at the auxiliary heater(s) 308 to determine electricity consumption) can be configured to generate at least one of the demand data. In this regard, the demand information block 324 can, in one example, be considered to be a hardware-based block. In another example, the demand information block 324 can be considered to be a software-based block in that such information can be obtained from a world wide web-based database associated with the, for example, utilities system(s).

Regarding the price information block 326, information (i.e., relating to/corresponding to the aforementioned supply data) such as pricing of electricity, water and/or gas can be obtained. The present disclosure contemplates that such information can be collected from one or more external based systems (i.e., 3 ^rd party system(s) which can be external relative to the STWH system 300a) such as, one or more utilities system. In this regard, the price information block 326 can, in one example, be considered to be a hardware-based block. In another example, the price information block 326 can be considered to be a software -based block in that such information can be obtained from a world wide web-based database associated with the, for example, utilities system(s). Regarding the user information block 328, information (i.e., relating to/corresponding to the aforementioned user-based data) such as number of users (e.g., using the STWH system 300a) and/or one or more users’ preference (e.g., when using the STWH system 300a) can be collected. The present disclosure contemplates that such information can be obtained through one or more onsite sensors and/or one or more loT (Internet of Things) based devices. In this regard, the user information block 328 can, for example, considered to be a hardware-based block.

The present disclosure contemplates that the aforementioned real-time data can be based on any one or more of, or any combination of, the weather information block 320, the system information block 322, the demand information block 324, the price information block 326 and the user information block 328.

Regarding the historic data block 330, the present disclosure contemplates the possibility that the aforementioned real-time data can be collected and stored in one or both of a local memory device (not shown) within the STWH system 300a and a remote cloud server (not shown) which can be external with respect to the STWH system 300a. The local memory device can be an example of an electronic device (e.g., a hard disk drive) in the STWH system 300a. Moreover, regarding the historic data block 330, information such as historic data in relation to one or more of, or any combination of, the weather information block 320, the system information block 322, the demand information block 324, the price information block 326 and the user information block 328 can be collected, and, if desired, subsequently retrieved (e.g., for processing by manner of, for example, analysis to obtain/derive the projection data). In this regard, historic data can be based on past (i.e., previous instances) real-time data collected and stored in the local memory device and/or the remote cloud server.

In one example, concerning the weather information block 320, historic data such as weather condition (e.g., sunny or rainy) relating to certain months, certain days of the week and/or certain parts (e.g., time resolution based) of certain days can be collected. In another example, concerning the system information block 322, historic data (e.g., which can be daily based, monthly based and/or time resolution based) such as pump pressure of the circulator pump(s) 310, water temperature within the storage tank(s) 304, water volume within the storage tank(s) 304 and/or water flow rates via the inlet/outlet pipe(s) can be collected. In yet another example, demand information block 324, historic data (e.g., which can be daily based, monthly based and/or time resolution based) in relation to user consumption of electric power, water and/or heat demand can be collected. In a further example, concerning the price information block 326, historic data concerning the monthly (or daily/time resolution based) pricing of electricity, water and/or gas can be collected. In yet a further example, concerning the user information block 328, historic data in relation to the number of users using the STWH system 300a (e.g., number of users within a month and/or a day, or number of users based on time resolution) and/or one or more users’ typical preference (e.g., heating of water to a specific/desired temperature) when using the STWH system 300a can be collected. In this regard, the historic data block 330 can be considered to be a hardware -based block (e.g., a local memory device) and/or a software-based block (e.g., a software module which can be configured to retrieve past real-time data from the local memory device and/or the remote cloud server). Moreover, it can be appreciated that historic data can be short term based (e.g., daily), long term based (e.g., monthly) or time period based with one or more time resolutions (e.g., in blocks of 15 minutes or in hourly blocks). Historic data can be the basis from which one or more prediction models can be derived/generated as will be discussed in relation to the projection data block 332 hereinafter.

Regarding the projection data block 332, information such as one or more prediction models can be derived/generated. Such prediction model(s) can be short term based, long term based and/or time period based (e.g., with various time resolutions such as a frequency of 15 minutes, 30 minutes or 60 minutes). The present disclosure contemplates that such prediction model(s) can be useful for input optimization and control strategy. The present disclosure contemplates that the aforementioned dynamic optimized control strategy/strategies can be based, at least in part, on such prediction model(s), according to an embodiment of the disclosure.

The projection data block 332 can correspond to a deep learning module which can be one or both of hardware based and software based (i.e. hardware based and/or software based; at least one of hardware based and software based)., in accordance with an embodiment of the disclosure.

The deep learning module can, for example, be based on Long Short-Term Memory (LSTM) based techniques can be used for the purpose of training. LSTM is an artificial Recurrent Neural Network (RNN) based architecture associated with the field of deep learning. As a general example, the deep learning module, or at least a portion thereof, can be Artificial Intelligence based.

The present disclosure contemplates that the deep learning module can be configured to process (e.g., by manner of analysis) the above-mentioned historic data as so to generate one or more prediction models. The prediction model(s) can, for example correspond to an algorithm. Based on the prediction model(s), the aforementioned projection data can be generated. Earlier mentioned, the control method 200 can, according to an embodiment of the disclosure, include learning one or both of associations and patterns in relation to the historic data

In one example, the deep learning module can be configured to learn/analyze, based on the aforementioned historic data, whether the weather would, for example, be typically sunny or rainy the next few days/the next week/the next month. In another example, the deep learning module can be configured to learn/analyze, based on the aforementioned historic data, whether certain portion(s)/part(s) (e.g., the storage tank(s) 304, the solar thermal collector panel(s) 306, the auxiliary heater(s) 308, the circulator pump(s) 310 and/or the controller(s) 312) of the STWH system 300a may require maintenance or replacement at some point in time. In yet another example, the deep learning module can be configured to learn/analyze, based on the aforementioned historic data, whether demand would be high/low during certain parts of a day. In a further example, the deep learning module can be configured to learn, based on the aforementioned historic data, whether a high number of users using the STWH system 300a can be expected during certain days and/or during certain periods in a day. In yet a further example, the deep learning module can be configured to learn/analyze, based on the aforementioned historic data, whether a user or a group of users using the STWH system 300a would prefer water to be heated to a certain temperature.

Appreciably, these examples can be examples of the earlier mentioned learnt associations and/or learnt patterns.

The present disclosure contemplates that the prediction model(s) can be derived based on one or both of the learnt associations and the learnt patterns, and the projection data can be based on the prediction model(s). Moreover, it can be appreciated that the prediction model(s) can be one of short term based, long term based and mixed time period based, according to an embodiment of the disclosure. Therefore, the prediction model(s) can, for example, relate to any one or more of, or any combination of, system-based prediction model(s), user-based prediction model(s) and environment-based prediction model(s), in accordance with an embodiment of the disclosure.

The system-based prediction model(s) can be associated with one or more portions (e.g., the storage tank(s) 304, the solar thermal collector panel(s) 306, the auxiliary heater(s) 308, the circulator pump(s) 310 and/or the controller(s) 312) of the STWH system 300a. In this regard, projection data can, in one embodiment, relate to predicted information concerning one or more portions of the STWH system 300a (e.g., whether maintenance of one or more parts of the STWH system 300a might be required, whether water volume stored in the storage tank(s) 304 might be enough to meet consumption demands during certain parts of a day). The user-based prediction model(s) can be associated with the user(s) of the STWH system 300a. In this regard, projection data can, in one embodiment, relate to predicted information concerning the user(s) of the STWH system 300a (e.g., the number of users who might be using the STWH system 300a during certain parts of a day, whether consumption demand might be higher during certain parts of a day/during certain parts of a week or a month, the preferred water heating temperature of one or more users).

The environment-based prediction model(s) can be associated with the environment associated with the STWH system 300a. In this regard, projection data can, in one embodiment, relate to predicted information concerning the environment associated with the STWH system 300a (e.g., whether the weather would typically be sunny, rainy or cloudy during certain parts of a day/during certain parts of a week or a month). Therefore, projection data can, for example, relate to predicted information concerning one or more portions of the STWH system 300a (e.g., water volume within the storage tank(s) may drop below acceptable threshold in a few hours’ time), predicted information concerning the user(s) of the STWH system 300a (e.g., the number of users may increase/decrease in 30 minutes’ time) and/or predicted information concerning the environment associated with the STWH system 300a (e.g., it will be rainy in three days’ time), according to an embodiment of the disclosure.

In one embodiment, the projection data block 332 can correspond to a hardware- based module (not shown) carrying the prediction model(s). In another embodiment, the projection data block 332 can correspond to a software-based module (not shown) corresponding to an algorithm which can, in turn, correspond to the prediction model(s). In yet another embodiment, the projection data block 332 can correspond to a combination of hardware based and software based modules.

Based on one or both of the projection data and the real-time data one or more control signals can be generated. Specifically, based on one or both of the projection data and the real-time data, one or more dynamic optimized control (also referable to as“one or more control strategies”) can be derived. The control signal(s) can be based on the control strategy/control strategies. Such control strategy/control strategies can be useful for optimizing operation of the STWH system 300a, as will be discussed with reference to the optimization and control block 334 hereinafter.

Regarding the optimization and control block 334, one or more control strategies can, for example, be derived for optimizing (e.g., based on efficiency and/or reliability) operation of the STWH system 300a, according to an embodiment of the disclosure.

In one example, a control strategy can be directed at controlling the solar thermal collector panel(s) 306 and/or the auxiliary heater(s) 308 to operate in an efficient manner so as to improve overall efficiency and/or reliability of the STWH system 300a. For example, the real-time data can be indicative of the current weather being a sunny day and projection data can be indicative of the next day being a rainy day. Based on the real-time data (i.e., indicative of current weather being sunny), auxiliary heater(s) 308 which may be operated based on power from the grid (i.e., from power stations) may be reserved for later use and not current use. Auxiliary heater(s) 308 can be activated for improved reliability where although the real-time data is indicative of sunny weather, but the projection data is indicative of the possibility of disruption (e.g., due to cloudiness) to such sunny conditions. Moreover, provisions can be arranged for additional harvesting (e.g., addition of solar thermal collector panel(s) 306) and storage of energy on certain days where projection data can be indicative of sunny weather.

In another example, a control strategy can be directed at controlling pump pressure of the circulator pump(s) 310 in an appropriate manner (e.g., ramp up/reduce pump pressure gradually) where, for example, the real-time data is indicative of the actual number of users and the projection data is indicative of an increase/decrease in the number of users sometime later (e.g., 10 minutes later). By suitable gradual ramping up or ramping down, the present disclosure contemplates that sudden surges/spikes (e.g., in connection to supply required by the auxiliary heater(s) 308 and/or supply required from the solar thermal collector panel(s) 306) can be avoided. This may be useful in preserving system integrity of the STWH system 300a (e.g., prevent breakdown which may be caused/induced by stress due to sudden surges/spikes).

In yet another example, a control strategy can be directed at scheduling the STWH system 300a for heating water based on real-time data indicative of current electricity, gas and/or water pricing and projection data indicative of predicted electricity, gas and/or water pricing at some point in time later (e.g., an hour later). For example, if the projection data can be indicative that it would be more price efficient to heat water later as compared to currently (i.e., based on real-time data), heating of water can be scheduled accordingly.

Generally, dynamic optimized control of the operation of the STWH system 300a can, for example, be in relation to time scheduling or real time control strategies in terms of different objectives. For example, the users (or system managers) would be able to pursue their own efficiency objectives such as minimizing the total electricity cost (i.e., price efficiency) and/or minimizing the peak power consumption (i.e., to ensure reliability by avoiding instances of overloading the STWH system 300a). The optimization and control block 334 can correspond to the aforementioned controller(s) 312, in accordance with an embodiment of the disclosure. The controller(s) 312 can, for example, include the earlier discussed processing portion 106 (e.g., a processor such as a microprocessor) and/or the earlier discussed control portion 108 (e.g., controller type IC chip). In this regard, the optimization and control block 334 can correspond to a hardware-based block, in accordance with an embodiment of the disclosure.

Appreciably, the real-time data and the projection data can be processed (e.g., by the processing portion 106) by manner of, for example, comparative based processing (i.e., comparing current information and predictive information) to derive one or more control strategies, according to an embodiment of the disclosure. Based on the control strategy/control strategies, one or more control signals can be generated (e.g., by a processor) and for, for example, managing operation status (e.g., via the control portion 108) in connection with one or more portions (e.g., the storage tank(s) 304, the solar thermal collector panel(s) 306, the auxiliary heater(s) 308 and/or the circulator pump(s) 310) of the STWH system 300a. This will be briefly discussed with reference to the output block 336 hereinafter.

With regard to the output block 336, the control portion 108, based on the control signal(s), can, for example, generate corresponding control parameter(s) (i.e., also referable to as“control command(s)”) in connection with one or more portions of the STWH system 300a.

In accordance with an embodiment of the disclosure, the output block 336 can be associated with one or more sub-systems which can include a solar thermal system, an auxiliary heater system and/or a distribution system. The solar thermal system can, for example, be associated with the solar thermal collector panel(s) 306. The auxiliary heater system can, for example, be associated with the auxiliary heater(s) 308. The distribution system can, for example, be associated with the storage tank(s) 304 and/or the inlet/outlet pipe(s). The solar thermal system can, for example, include one or more circulation pump(s) 310 and can be associated with one or more speed settings. The solar thermal system can further be associated with an ON/OFF” setting (i.e. ,“ON” to activate the solar thermal system;“OFF” to deactivate the solar thermal system), according to an embodiment of the disclosure.

The auxiliary heater system can, for example, include one or more circulation pump(s) 310 and can be associated with one or both of one or more speed settings and one or more temperature control settings. The auxiliary heater system can further be associated with an“ONYOFF” setting (i.e.,“ON” to activate the auxiliary heater system; “OFF” to deactivate the auxiliary heater system), according to an embodiment of the disclosure.

The distribution system can, for example, include one or more circulation pump(s) 310 and can be associated with one or more speed settings. The distribution system can further be associated with an “ON/OFF” setting (i.e., “ON” to activate the distribution system;“OFF” to deactivate the distribution system), according to an embodiment of the disclosure. In one example, the control command(s) can be in relation to“ONYOFF” and/or speed setting(s) in connection with the circulation pump(s) 310

In another example, the control command(s) can in be in relation to“ONYOFF”, speed setting(s) and/or threshold temperature setting(s).

From the foregoing, it is appreciable that the STWFI system 300a, generally, can include at least one circulation pump 310, at least one auxiliary heater 308, at least one storage tank 304, at least one inlet/outlet pipe and at least one electric/electronic component (e.g., onsite sensor, hard disk drive). The control signal(s) can be communicated to one or more portions of the STWFI system 300a and the control parameter(s) can be used for controlling any one or more of, or any combination of, the circulation pump(s) 310, the auxiliary heater(s) 308, the storage tank(s) 304, the inlet/outlet pipe(s) and the electric/electronic component(s). Each of the aforementioned meteorological station(s) and the utilities station(s) can correspond to a third-party system.

Fig. 3c shows the example implementation of Fig. 3a in further detail, according to an embodiment of the disclosure. Specifically, the STWFI system 300a is shown in further detail, in accordance with an embodiment of the disclosure.

The present disclosure contemplates that, as shown, there can be, for example, two types of solar thermal collector panels 306 which can correspond to two types of solar thermal collector arrays (STCs) (e.g., a flat-plate type collector and an evacuated tube type collector), according to an embodiment of the disclosure.

Moreover, as shown, the auxiliary heater(s) 308 can, for example, include one or both of a heat pump and an electric heater, according to an embodiment of the disclosure.

Furthermore, there can be a kitchen zone aside the aforementioned building 302.

Additionally, there can, for example, be a main water supply source which supplies water (e.g., to be heated) to the storage tank(s) 304, according to an embodiment of the disclosure.

Earlier mentioned, the aforementioned dynamic optimized control strategy/strategies (i.e. , referable simply as “control strategy/strategies”) can be validated experimentally.

Specifically, as will be discussed in further detail with reference to Fig. 4 (i.e., showing a set of graphs) and Fig. 5 (i.e., showing a set of tables), the aforementioned energy management framework 300b can be validated to demonstrate feasibility and/or effectiveness, in accordance with an embodiment of the disclosure. The present disclosure contemplates energy analysis, forecasting, and/or control processes in relation to the operation process of the STWH system 300a. In this context, one or more aspects of the present disclosure can be experimentally validated in a numerical manner (e.g., simulation) to demonstrate feasibility and/or effectiveness.

Concerning numerical based validation, simulation can be performed to examine the aforementioned control strategy/strategies based on, for example, a set of previous real-time data (i.e., a set of historic data) of STWH system 300a from a commercial building in Singapore. That is, historical data in relation to hot water demand consumed in the commercial building can be obtained. Additionally, the specification of the STWH system 300a can be obtained. Furthermore, environmental based data (e.g., data concerning the weather) and supply data (e.g., electricity tariff) can also be consideration factors. During simulation testing, different weather scenarios (e.g., sunny, rainy, cloudy, and even dark conditions as the worst case) can be considered.

As shown in Fig. 4 (i.e., based on a set of graphs), the effectiveness the control strategy/strategies can be numerically validated in the context of various objectives such as Cost-optimal (i.e., Case 1 ), Peak Reduction (i.e., Case 2), and Dual Cost- Peak Objectives (i.e., Case 3).

The present disclosure further contemplates that two approaches can be considered for comparison. One approach can be an On-Demand Control (ODC) approach which requires no forecast information and could be performed in real-time. The ODC approach can provide insights concerning the upper bound of the control performance.

Another approach can be an Optimal Day-ahead Scheduling (ODS) approach that assumes the prior information concerning the future 24-hours is perfectly known. The solution of the ODS approach is theoretical optimum based on exact future information, and thus can serve as a lower bound the control performance for different objectives. The case results concerning the foregoing approach(es) (e.g., ODC and ODS; case 1 to case 3) are shown in Fig. 5 which depicts a set of two tables showing improvement(s) in terms of cost-efficiency and reduction in the peak demand.

The present disclosure contemplates that the ODC approach can be considered to be a simple and real-time control method, and can have the potential for practical implementation. Hence, the present disclosure contemplates that the results of the ODC approach can serve as a reference benchmark for performance comparison (s)

In one example, the ODS approach can obtain a maximum cost-savings of 7:32%, compared to the ODC approach in the context of the cost-optimal objective.

In another example, in the context of the peak reduction objective, the ODS approach can archive a maximum of 61 :55% peak-reduction compared to the ODC approach.

In another example, in the context of dual cost-peak objectives, the cost-savings and peak-reduction of the ODS approach are 3:59% and 61 :55% respectively as compared to the ODC approach. However, the potentiality of the ODS approach for practical implementation can be considered to be limited due to the requirement of perfect future information and extensive computation time. Thus, the present disclosure contemplates that the ODS approach may yet be suitable for practical implementation.

It should be further appreciated by the person skilled in the art that variations and combinations of features described above, not being alternatives or substitutes, may be combined to form yet further embodiments. In one example, the STWH system 300a can include additional storage tank(s) 304 with additional auxiliary heaters, further heating water to various described water temperature for specified use. For example, the STWH system 300a can have two differently sized storage tanks 304 (e.g., a main tank and a kitchen tank) In another example, the solar thermal collector panel(s) 306 can be of any size, type (even multi-types), and number. For example, as mentioned earlier, there can be two types of solar thermal collector panels 306 which can correspond to two types of solar thermal collector arrays (STCs) (e.g., a flat-plate type collector and an evacuated tube type collector).

In yet another example, the number of auxiliary heater(s) 308 can be flexibly based on different heat sources (e.g., air-based heat source, water-based heat source, or ground-based heat source).

In the foregoing manner, various embodiments of the disclosure are described for addressing at least one of the foregoing disadvantages. Such embodiments are intended to be encompassed by the following claims, and are not to be limited to specific forms or arrangements of parts so described and it will be apparent to one skilled in the art in view of this disclosure that numerous changes and/or modification can be made, which are also intended to be encompassed by the following claims.