A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response

Parrish, Bryony; Heptonstall, Philip; Gross, Rob; Sovacool, Benjamin K.

doi:10.1016/j.enpol.2019.111221

Cited by 181 publications

(89 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The LA accurately estimates the response potential and response willingness of consumers and can better formulate day-ahead bidding strategies. The three main factors influencing the willingness of residents to participate in DR are the response quantity, awareness and external incentive [21,22]. The response quantity factor refers to the responsiveness of residents during the DR period, which can be calculated by Q DR HVAC,i,j , Q DR EWH,i,j , Q DR EV,i,j .…”

Section: Dr Uncertainty Modelmentioning

confidence: 99%

Day Ahead Bidding of a Load Aggregator Considering Residential Consumers Demand Response Uncertainty Modeling

Song

Shi

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

As the electricity consumption and controllability of residential consumers are gradually increasing, demand response (DR) potentials of residential consumers are increasing among the demand side resources. Since the electricity consumption level of individual households is low, residents’ flexible load resources can participate in demand side bidding through the integration of load aggregator (LA). However, there is uncertainty in residential consumers’ participation in DR. The LA has to face the risk that residents may refuse to participate in DR. In addition, demand side competition mechanism requires the LA to formulate reasonable bidding strategies to obtain the maximum profit. Accordingly, this paper focuses on how the LA formulate the optimal bidding strategy considering the uncertainty of residents’ participation in DR. Firstly, the physical models of flexible loads are established to evaluate the ideal DR potential. On this basis, to quantify the uncertainty of the residential consumers, this paper uses a fuzzy system to construct a model to evaluate the residents’ willingness to participate in DR. Then, based on the queuing method, a bidding decision-making model considering the uncertainty is constructed to maximize the LA’s income. Finally, based on a case simulation of a residential community, the results show that compared with the conventional bidding strategy, the optimal bidding model considering the residents’ willingness can reduce the response cost of the LA and increase the LA’s income.

show abstract

Section: Dr Uncertainty Modelmentioning

confidence: 99%

Day Ahead Bidding of a Load Aggregator Considering Residential Consumers Demand Response Uncertainty Modeling

Song

Shi

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Electrical design engineers of Iraq DPGs aim to meet two objectives [2][3][4]: studying the current residential dwelling load profile characteristics [5][6][7][8][9][10][11] and model the electricity kW demand [12][13][14][15][16][17][18]. The common factor among residential dwellings, called the diversity factor ( ), is the backbone of electricity demand modeling.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Residential Neighborhoods’ Electricity Demand in Iraq Distribution Power Grids

et al. 2021

View full text Add to dashboard Cite

In Baghdad City's distribution power grid, a massive number of 630 kV distribution transformers (DTs) are used in residential neighborhoods. Each DT is joined to nine low-voltage 0.415 kV distribution feeders. Each feeder has a designated size of 1 × 240 mm 2 and is joined to a specified number of residential dwellings (= 30) fixed in the initial design stage. The size and number of low-voltage 0.415 kV distribution feeders are set with no change. In this investigation, we use a new approach for modeling electricity demand in residential neighborhoods in Baghdad City and overcome this constraint by finding the optimum number of residential dwellings joined to the same low-voltage 0.415 kV distribution feeder. Two sets of the experimental equations are created to compute the number of residential dwellings that are required to be joined to the low-voltage 0.415 kV distribution feeder. The multi-gradient particle swarm optimization algorithm is used as an optimization tool to handle these experimental equations. Results show that each low-voltage 0.415 kV distribution feeder can be loaded with 50 dwellings instead of 30 due to the diversity among residential dwellings. Several facts about the load profile characteristics of

show abstract

“…Previous demand response studies have for example investigated the relation between flexibility and gender [22,23], households with children [24,25], flexibility capital [26], social practices [27], temporality of everyday life [28], user typology [29] and non-self-selected prosumers [30]. A systematic review of consumer engagement among households for demand responsibility can be found in [31]. One way of communicating the need for flexibility is the use of electricity feedback, which has been shown to play an equal or more important role than pricing strategies [32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Identifying Challenges in Engaging Users to Increase Self-Consumption of Electricity in Microgrids

et al. 2021

View full text Add to dashboard Cite

A microgrid’s self-consumption rate reflects its ability to retain its own energy and decrease its reliance on the synchronous grid. This paper investigates the empirical case of a microgrid equipped with photovoltaic (PV) panels and identifies challenges in engaging the microgrid’s users to increase their self-consumption. Accordingly, we explored both the physical and social dimensions of the microgrid. The former involved mapping the electricity consumption and production through an exploratory data analysis, and evaluating the associated price signals, while the latter involved the use of design interventions to explore users’ perceptions of the system. We highlight the problem of price signal impedance, the need for cost reflective pricing and the challenge in designing and extending internal price models in settings with various actors. We address the limitations of price signals, alongside alternative unidimensional signals, and emphasize the need for an integrated approach to a user engagement strategy as well as the challenges that this approach entails. Our results shed light on the complexity of energy communities such as microgrids, and why their implementation can introduce multidimensional challenges that demand cross-disciplinary approaches.

show abstract

A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response

Cited by 181 publications

References 32 publications

Day Ahead Bidding of a Load Aggregator Considering Residential Consumers Demand Response Uncertainty Modeling

Day Ahead Bidding of a Load Aggregator Considering Residential Consumers Demand Response Uncertainty Modeling

A Novel Approach for Residential Neighborhoods’ Electricity Demand in Iraq Distribution Power Grids

Identifying Challenges in Engaging Users to Increase Self-Consumption of Electricity in Microgrids

Contact Info

Product

Resources

About