Home energy storage devices, which house electricity locally for later consumption, are at their essence rechargeable batteries. They’re controlled by computers with intelligent software to handle charging and discharging cycles and are instrumental in the performance and economy of smart homes featuring renewable energy.
Certainly, there are both challenges and opportunities associated with sustainable energy supplies and energy storage. Let’s look at some of the newest research on home energy storage to see what’s happening in the field and what’s likely to emerge in this area of clean consumer tech in the near future.
Household renewable energy generation through the use of solar panels is becoming more commonplace as installation costs are lessening and electricity prices are rising. Solar energy is an intermittent source, only generated during the day and subject to interference from weather and seasonal variation.
Capital Costs & Comfort as Part of Home Energy Storage Decisions
Recognizing that a smart home energy management system is critical for consumers to intelligently and conveniently manage the use of an energy storage system (ESS) alongside domestic appliances, renewable energy (RES) generation, and electric vehicles (EVs), Huan Hou and associates propose a holistic model to center the preference of users when scheduling the involved physical equipment of different natures. They also describe the advantages of a dedicated charging and discharging strategy for both the ESS and an EV, taking into account capital costs to provide better flexibility and economic advantages as well as to prolong the life of the batteries. They conclude, based on mixed integer linear programming, that the energy schedule of a smart home can be accommodated to guarantee both the lowest cost and the comfort for the users.
Severe Weather Events & Energy Storage
A paper by Schmidt and associates proposes a mathematical model for home energy storage management that enhances the home’s resilience in the face of severe weather events. The model automatically decides in advance when to start the ESS recharging. To do so, it formulates the operational condition of the local distribution network, estimates the probability of a power outage associated with the incidence of strong winds, and monitors the meteorological parameters and state of charge of the local ESS. Results show contributions to increasing the home’s electric resilience, with little interference in the standard operation of the ESS.
Home Energy & Demand Side Management
An intelligent multi-objective household demand side management (DSM) is proposed in this study by Lokeshgupta and Sivasubramani. Generally, the residential DSM deals with various controllable appliances that normally have different operating time priorities according to the consumers’ preferences. Because of this, the DSM problem is modeled as a mixed integer optimization problem. These researchers demonstrate how a multi-objective mixed integer linear programming technique (MOMILP) can solve the identified residential DSM problem.
Distributionally Robust Optimization
Zhoa and associates compare how energy storage and demand response resources, in combination with intermittent renewable generation, are expected to provide domestic customers with the ability to reducing their electricity consumption. Their study highlights the role that an intelligent battery control and solar generation can play to increase renewable uptake while reducing customers’ electricity bills without intruding on people’s daily life. Through a range of interventions, they determine that the optimal performance of a home energy management system is derived by applying distributionally robust optimization, which their testing determines to be optimally effective and computationally efficient while considering uncertainty.
V2H & BESS
What happens when vehicle to home (V2H) capability of the available electric vehicle is used in coordination with a battery energy storage system (BESS) under the control of a home energy management system? Zenali and associates acknowledge that there are uncertainties derived from the power production of roof-mounted solar photovoltaic panels, so a household’s load demand is factored into the real-time electricity price. They implement a 2-stage stochastic process in which an artificial neural network (ANN) is trained using an historical time series as well as integrating a proper analytical battery degradation cost model into the problem.
How To Determine Optimal BESS?
This paper by Sharma and team proposes a method of determining the optimal size of a BESS for a typical net zero energy (NZE) home with a rooftop solar photovoltaic system to minimize the annual net payment for electricity and battery cost. They determine the optimal battery size through solving an optimization problem which is formulated using hourly load and PV generation data for a South Australian home, battery annual payment rate, retail price (RP), and feed-in tariff (FIT). Additionally, they investigate the effects of interest rate, RP, and FIT have on the annual net payment. They determine that, with current installation cost of BESS and South Australian RP and FIT, the use of a local BESS is economically beneficial for the homeowner.
What is the largest energy consuming sector that accounts for more than 1/3 of global energy demand? It’s the built environment, and more policy and regulations need to embrace beneficial incentives to reduce residential energy demand and emissions by stimulating renewable distributed energy resources.
The fastest growing distributed energy resource right now is electricity generation from solar photovoltaic, which could reach 22% of global electricity generation in 2050. Europe currently uses feed-in tariffs to provide reimbursement to residential households for the generation of rooftop PV electricity — households typically receive a subsidy when electricity is fed back into the grid. Alternatives are needed, however, as countries decrease their feed-in tariff compensation when grid parity and policy goals are reached.
Home energy management is one of the crucial components for such a future smart grid environment. Decentralized power generation in private homes, especially by photovoltaic systems, is already common in many parts of the world. The developments of batteries, both for electric vehicles and for stationary storage, is leading to a mass market for those batteries. The economy of a photovoltaic system, residential stationary battery storage, and EV needs deliberation as it is fully integrated into the home.
We should all be having conversations about such renewable energy conversions in our own residential spaces.
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