Enabling Demand Response programs via Predictive Control of Building-to-Grid systems integrated with PV Panels and Energy Storage Systems

2017 ◽  
Author(s):  
Meysam Razmara ◽  
Guna R. Bharati ◽  
Drew Hanover ◽  
Mahdi Shahbakhti ◽  
Sumit Paudyal ◽  
...  
Keyword(s):  
Energy Storage ◽  
Predictive Control ◽  
Demand Response ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Grid Systems ◽  
Demand Response Programs

scholarly journals Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs

2020 ◽  
Vol 12 (18) ◽  
pp. 7311
Author(s):  
Ali Dargahi ◽  
Khezr Sanjani ◽  
Morteza Nazari-Heris ◽  
Behnam Mohammadi-Ivatloo ◽  
Sajjad Tohidi ◽  
...  
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Demand Response ◽  
Thermal Energy Storage ◽  
Air Conditioning ◽  
Storage Systems ◽  
Forecast Errors ◽  
Energy Storage Systems ◽  
Thermal Energy Storage Systems ◽  
Demand Response Programs

The high penetration rate of renewable energy sources (RESs) in smart energy systems has both threat and opportunity consequences. On the positive side, it is inevitable that RESs are beneficial with respect to conventional energy resources from the environmental aspects. On the negative side, the RESs are a great source of uncertainty, which will make challenges for the system operators to cope with. To tackle the issues of the negative side, there are several methods to deal with intermittent RESs, such as electrical and thermal energy storage systems (TESSs). In fact, pairing RESs to electrical energy storage systems (ESSs) has favorable economic opportunities for the facility owners and power grid operators (PGO), simultaneously. Moreover, the application of demand-side management approaches, such as demand response programs (DRPs) on flexible loads, specifically thermal loads, is an effective solution through the system operation. To this end, in this work, an air conditioning system (A/C system) with a TESS has been studied as a way of volatility compensation of the wind farm forecast-errors (WFFEs). Additionally, the WFFEs are investigated from multiple visions to assist the dispatch of the storage facilities. The operation design is presented for the A/C systems in both day-ahead and real-time operations based on the specifications of WFFEs. Analyzing the output results, the main aims of the work, in terms of applying DRPs and make-up of WFFEs to the scheduling of A/C system and TESS, will be evaluated. The dispatched cooling and base loads show the superiority of the proposed method, which has a smoother curve compared to the original curve. Further, the WFFEs application has proved and demonstrated a way better function than the other uncertainty management techniques by committing and compensating the forecast errors of cooling loads.

scholarly journals Assessing the Demand Side Management Potential and the Energy Flexibility of Heat Pumps in Buildings

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1846 ◽  
Author(s):  
Alessia Arteconi ◽  
Fabio Polonara
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Energy Efficient ◽  
Storage Systems ◽  
Heat Pumps ◽  
Demand Side ◽  
Energy Storage Systems ◽  
Peak Shaving ◽  
Load Shifting ◽  
Demand Response Programs

The energy demand in buildings represents a considerable share of the overall energy use. Given the significance and acknowledged flexibility of thermostatically controlled loads, they represent an interesting option for the implementation of demand side management (DSM) strategies. In this paper, an overview of the possible DSM applications in the field of air conditioning and heat pumps is provided. In particular, the focus is on the heat pump sector. Three case studies are analyzed in order to assess the energy flexibility provided by DSM technologies classified as energy efficient devices, energy storage systems, and demand response programs. The load shifting potential, in terms of power and time, is evaluated by varying the system configuration. Main findings show that energy efficient devices perform strategic conservation and peak shaving strategies, energy storage systems perform load shifting, while demand response programs perform peak shaving and valley filling strategies.

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