Demonstration of Peak-Load Shifting with Optimal Residential Thermal Energy Management (original) (raw)
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2018
Energy management systems that efficiently use self-produced renewable energy are becoming popular. However, quantifying their benefits in terms of self-consumption increase and associated financial benefits, is difficult in life conditions. In that context, the Prosumer-Lab project was launched. In the latter a building, grid and PV installation are emulated and real energy management systems can be connected for evaluation. In this article, we describe various control strategies for energy management systems and benchmark their yearly performance in simulation in order to quantify the potential of the different approaches. This works is the first step towards the identification of possible improvements.
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Energies, 2018
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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Smart homes are one part of smart grid and smart distributed generation is one of the important components of smart homes. To minimize the generation costs to investors, a novel approach for smart production of energy in residential buildings is introduced in this paper. CHCP technologies offer a more beneficial way to provide home with heat, cooling and power in addition to advantages of high energy efficiency, emission reduction, and independency from centralized power networks. In this research, an energy dispatch algorithm is presented to minimize the total cost of energy (e.g., cost of natural gas into the engine and boiler and also cost of electricity from the grid) considering energy efficiency constrains for individual components. Additionally, the possibility of buying from or selling electrical power to the electrical local utility is investigated. The system consists of various kinds of loads (electrical, thermal and cooling) and energy resources (combined heat, power and...
Scheduling of demand-side resources for a building energy management system
International Transactions on Electrical Energy Systems, 2017
In this paper, an algorithm for scheduling of demand-side resources is presented for residential loads in dynamic pricing environment. The main objective of this study is to minimize the operational cost of energy consuming devices in an entire building over a day without violating set of consumer comfort preferences. The residential end-use consumer loads considered in the proposed work are heat ventilation and air conditioning system, plug-in hybrid electric vehicle, electric water pump, and electric water heater. The optimal control operation of the loads under a real-time pricing scheme is analyzed using particle swarm optimization. The results show that the proposed scheme gives a significant reduction in the building energy cost as compared to the normal ON/OFF based control operation. Two case studies of 2 typical buildings consisting of 3 and 100 houses are taken to evaluate the proposed optimal control scheme. The comparison between the proposed and normal ON/OFF methods shows that global optimization gives the significant energy as well as cost saving. KEYWORDS demand-side management (DSM), demand response (DR), particle swarm optimization (PSO), real-time pricing (RTP)
Solar Energy
The optimal design of distributed generation systems is of foremost importance to reduce fossil fuel consumption and mitigate the environmental impact of human activities in urban areas. Moreover, an efficient and integrated control strategy is needed for each of the components of a distributed generation plant, in order to reach the expected economic and environmental performances. In this paper, the transition from natural gas to electricity-based heating is evaluated for residential applications, considering the interplay between photovoltaic electricity produced on site and the thermal energy storage, to grant the optimal management of heating devices. The energy demand of an apartment building, under different climatic conditions, is taken as a reference and four power plant solutions are assessed in terms of energy cost and pollution reduction potential, compared to a baseline plant configuration. The performance of each power plant is analyzed assuming an optimized control strategy, which is determined through a graph-based methodology that was previously developed and validated by the authors. Outcomes from our study show that, if heat pumps are used instead of natural gas boilers, energy costs can be reduced up to 41%, while CO 2 emissions can be reduced up to 73%, depending on the climatic conditions. Our results provide a sound basis for considering the larger penetration of photovoltaic plants as an effective solution towards cleaner and more efficient heating technologies for civil applications. The simultaneous utilization of heat pumps (as substitutes of boilers) and photovoltaic panels yields a positive synergy that nullifies the local pollution, drastically cuts the CO 2 emission, and guarantees the economical sustainability of the investment in renewable energy sources without subsidiary mechanisms.
Intelligent Scheduling of a Grid-Connected Heat Pump in a Danish Detached House
2017
This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished gridconnected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation of the system is based on a price-signal considering a three-day period for different weather cases. The results show that the optimal scheduling of the system is successful in terms of reducing the peak load during times when electricity prices are high, thus achieving cost savings as well as maintaining good thermal comfort conditions. The proposed methodology bridges dynamic building modelling with optimization of real-time operation of HVAC systems offering a detailed model for building physics, especially regarding thermal mass and a stochastic price-based control.
Environments, 2018
Matching demand profile and solar irradiance availability is necessary to meet space heating and domestic hot water needs by means of an air-source heat pump and photovoltaic system in a single-family house. Demand-side management, with smart control of the water storage set-point, is a simple but effective technique. Several studies in the literature pursue demand-side matching and self-consumption goals through system adjustments based on the model predictive control. This study proposes a rule-based control strategy, based on instantaneous photovoltaic (PV) power production, with the purpose of enhancing the self-consumption. This strategy exploits the building’s thermal capacitance as a virtual battery, and the thermal storage capacity of the system by running the heat pump to its limit when PV surplus power is available, and by eventually using an electric heater in order to reach higher temperatures. Results of annual dynamic simulations of a building and its heating system sh...
Optimal Scheduling of Heat Pumps for Power Peak Shaving and Customers Thermal Comfort
Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, 2017
Final customers are expected to play an active role in the Smart Grid scenario by offering their flexibility to allow a more efficient and reliable operation of the electric grid. Among the household appliances, heat pumps used for space heating are commonly recognized as flexible loads that can be suitably handled to gain benefit in the Smart Grid context. This paper proposes an optimization algorithm, based on a Mixed-Integer Linear Programming approach, designed to achieve power peak shaving in the distribution grid while providing at the same time the required thermal comfort to the end-users. The developed model allows considering a continuous operation mode of the heat pumps and different comfort requirements defined by the users over the day. Performed simulations prove the proper operation of the proposed algorithm and the technical benefits potentially achievable through the devised management of the heating devices.
Increasing economic benefits by load-shifting of electrical heat pumps
Chemical Engineering Transactions, 2014
Electrical heating is still widely used in the process industry. While the use of immersion heaters for the production of hot water or steam is declining, the adoption rate of electrical heat pumps is increasing rapidly. Heat pumps show great flexibility and potential for energy savings, e.g. through low temperature waste heat recuperation. In combination with thermal storage they also allow for load shifting. Because their main power source is electricity, which up to now cannot be stored efficiently, heat pumps can transpose their thermal load shifting ability to the electrical grid. Today, more and more industrial electricity consumers are adopting energy supply contracts with variable pricing parameters strongly coupled to the energy trading market. Some large consumers even buy and sell on this market directly. In this paper it is proven that for customers with (hourly) variable electricity pricing, the use of electrical heat pumps can lead to additional cost savings without influencing the industrial process. The yield of the heat pumps can be increased during hours with low energy cost, with the thermal buffer absorbing the heat surplus. During hours with high energy cost the heat pump yield is lowered and stored heat is used by the industrial process. Considering that heat can be stored much more efficiently than electricity, the load shifting ability of heat pumps can also be utilised to provide stability on electrical smart grids and to increase electrical self-consumption on microgrids. This paper will also explore the potential of thermal storage through heat pumps for these electrical smart grid applications.