Demand response implementation in smart households

Abstract

Home energy management system (HEMS) is essential for residential electricity consumers to participate actively in demand response (DR) programs. Dynamic pricing schemes are not sufficiently effective for endusers without utilizing a HEMS for consumption management. In this paper, an intelligent HEMS algorithm is proposed to schedule the consumption of controllable appliances in a smart household. Electric vehicle (EV) and electric water heater (EWH) are incorporated in the HEMS. They are controllable appliances with storage capability. EVs are flexible energy-intensive loads, which can provide advantages of a dispatchable source. It is expected that the penetration of EVs will grow considerably in future. This algorithm is designed for a smart household with a rooftop photovoltaic (PV) system integrated with an energy storage system (ESS). Simulation results are presented under different pricing and DR programs to demonstrate the application of the HEMS and to verify its' effectiveness. Case studies are conducted using real measurements. They consider the household load, the rooftop PV generation forecast and the built-in parameters of controllable appliances as inputs. The results exhibit that the daily household energy cost reduces 29.5%-31.5% by using the proposed optimizationbased algorithm in the HEMS instead of a simple rule-based algorithm under different pricing schemes.

Dynamic Pricing for Demand Response Considering Market Price Uncertainty

“…Therefore, the cost of purchasing power through bilateral contracts is represented with Equation (15).…”

“…The dynamic prices for residential retail consumers can be used to control the consumption of controllable appliances such as electric vehicles, heat pumps, and electric water heaters [15]. The consumers also require a specialized control system, which is usually known as a home energy management system, to make optimal decisions for changing the demand profile.…”

A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies

“…Bearing in mind all the aforementioned aspects, a new active DSM concept has been proposed for prosumer microgrids. It provides flexibility and interaction between all loads and energy sources on-site (local level) as well as between Distribution System Operators (DSOs) and prosumers, with the possibility to exchange data and actively respond to requests for information like energy pricing (tariffs), incentive or demand reduction signals [10,[17][18][19][20]. These features are important in perspective of a transactive energy (TE)-a relatively new paradigm for the microgrids and the SG, combining information and energy to enable transactions which implements highly coordinated self-optimization and possibility for retail customers-prosumers to effectively participate in mechanisms of the purchase and sale of power and energy [21][22][23].…”

“…Moreover, Home Energy Management Systems (HEMS) based on the BACS standards are considered to improve the operation utility of households in the microgrid concept. The HEMS are usually used to collect data and signals from household appliances, smart meters, various sensors and to optimize power supply and energy demand with this information [20,[33][34][35].…”

Improving an Integer Linear Programming Model of an Ecovat Buffer by Adding Long-Term Planning

“…For the supply of heat demand to houses, a number of options is currently considered in the literature, ranging from residential water heaters, potentially in combination with a small storage tank (e.g., [13,14]), to district heating networks that supply heat to an entire neighborhood. District heating networks might cover a significant portion of the future heating demand in large parts of Europe as discussed in [15].…”