Efficient energy consumption and operation management in a smart building with microgrid
TL;DR: In this article, the optimal scheduling of smart homes' energy consumption is studied using a mixed integer linear programming (MILP) approach, in order to minimise a 1-day forecasted energy consumption cost, DER operation and electricity consumption household tasks are scheduled based on real-time electricity pricing, electricity task time window and forecasted renewable energy output.
About: This article is published in Energy Conversion and Management.The article was published on 2013-10-01. It has received 305 citations till now. The article focuses on the topics: Energy consumption & Peak demand.
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TL;DR: In this paper, the forecast errors of wind speed and solar irradiance are modeled by related probability distribution functions and then, by using the Latin hypercube sampling (LHS), the plausible scenarios of renewable generation for day-head energy and reserve scheduling are generated.
343 citations
Cites methods from "Efficient energy consumption and op..."
...A Beta PDF is utilized for each unimodal [13,15], as set out in the following:...
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TL;DR: A noncooperative Stackelberg game between the RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid.
Abstract: In this paper, the benefits of distributed energy resources are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A noncooperative Stackelberg game between the RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid. From the properties of the game, it is shown that the maximum benefit to the SFC, in terms of reduction in total cost, is obtained at the unique and strategy-proof Stackelberg equilibrium (SE). It is further shown that the SE is guaranteed to be reached by the SFC and RUs by executing the proposed algorithm in a distributed fashion, where participating RUs comply with their best strategies in response to the action chosen by the SFC. In addition, a charging–discharging scheme is introduced for the SFC's storage device that can further lower the SFC's total cost if the proposed game is implemented. Numerical experiments confirm the effectiveness of the proposed scheme.
297 citations
Cites background from "Efficient energy consumption and op..."
...For instance, the authors in [19] study an efficient energy consumption and operation management scheme for a smart building to reduce energy expenses and gas emissions by utilizing DERs....
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..., by scheduling the use of its flexible devices [19] to a later time, and thus becomes more interested in making further revenue....
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...As can be seen from the above discussion, the scope of research on the use of DERs in smart grid is not limited to power and energy research communities such as in [1], [2], [4] and [19], but also extends to other research communities including those in smart grid [14], [26], and industrial electronics (IE) [5], [11]–[13], [17], [20]–[25], [27]....
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TL;DR: This paper aims to review different research works on DR optimisation problems and some directions for future research are proposed.
Abstract: Demand response programs offer efficient solutions for many power system problems, such as high generation cost, high demand’s peak to average ratio, high emissions, reliability issues and congestion in generation, transmission and distribution systems. Their main function is to assist power systems during peak demand hours and also during contingencies. They are a subcategory of the family of demand side management (DSM) strategies. DR programs are classified into two broad categories; price-based DR programs and incentive-based DR programs. In order to exploit their full potential, DR programs must be implemented optimally. Such a problem, which here is referred to as “DR optimisation problem”, is a hot research topic and has been frequently researched in the literature. This paper aims to review different research works on DR optimisation problems. Based on the conducted review, some directions for future research are proposed.
293 citations
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TL;DR: In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units and a shared facility controller.
Abstract: In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A non-cooperative Stackelberg game between RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid. From the properties of the game, it is shown that the maximum benefit to the SFC in terms of reduction in total cost is obtained at the unique and strategy proof Stackelberg equilibrium (SE). It is further shown that the SE is guaranteed to be reached by the SFC and RUs by executing the proposed algorithm in a distributed fashion, where participating RUs comply with their best strategies in response to the action chosen by the SFC. In addition, a charging-discharging scheme is introduced for the SFC's storage device (SD) that can further lower the SFC's total cost if the proposed game is implemented. Numerical experiments confirm the effectiveness of the proposed scheme.
245 citations
TL;DR: In this paper, an energy resources management model for a microgrid (MG) is proposed, which considers practical constraints, renewable power forecasting errors, spinning reserve requirements and EVs owner satisfaction, and a case study with a typical MG including 200 EVs is used to illustrate the performance of the proposed method.
206 citations
Cites background from "Efficient energy consumption and op..."
...The idea supporting the formation of the MG is that a paradigm consisting of a cluster of distributed generations and aggregated loads is adequately reliable and economically viable as an operational electric system [2,3]....
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References
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TL;DR: This work improves the basic formulation of cooperative PSO by introducing stochastic repulsion among the particles and simultaneously scheduling all DER schedules, to investigate the potential consumer value added by coordinated DER scheduling.
Abstract: We describe algorithmic enhancements to a decision-support tool that residential consumers can utilize to optimize their acquisition of electrical energy services. The decision-support tool optimizes energy services provision by enabling end users to first assign values to desired energy services, and then scheduling their available distributed energy resources (DER) to maximize net benefits. We chose particle swarm optimization (PSO) to solve the corresponding optimization problem because of its straightforward implementation and demonstrated ability to generate near-optimal schedules within manageable computation times. We improve the basic formulation of cooperative PSO by introducing stochastic repulsion among the particles. The improved DER schedules are then used to investigate the potential consumer value added by coordinated DER scheduling. This is computed by comparing the end-user costs obtained with the enhanced algorithm simultaneously scheduling all DER, against the costs when each DER schedule is solved separately. This comparison enables the end users to determine whether their mix of energy service needs, available DER and electricity tariff arrangements might warrant solving the more complex coordinated scheduling problem, or instead, decomposing the problem into multiple simpler optimizations.
824 citations
TL;DR: The numerical results show attributes of the two approaches for solving the real-time optimal DR management problem for residential appliances via stochastic optimization and robust optimization approaches.
Abstract: This paper evaluates the real-time price-based demand response (DR) management for residential appliances via stochastic optimization and robust optimization approaches. The proposed real-time price-based DR management application can be imbedded into smart meters and automatically executed on-line for determining the optimal operation of residential appliances within 5-minute time slots while considering uncertainties in real-time electricity prices. Operation tasks of residential appliances are categorized into deferrable/non-deferrable and interruptible/non-interruptible ones based on appliances' DR preferences as well as their distinct spatial and temporal operation characteristics. The stochastic optimization adopts the scenario-based approach via Monte Carlo (MC) simulation for minimizing the expected electricity payment for the entire day, while controlling the financial risks associated with real-time electricity price uncertainties via the expected downside risks formulation. Price uncertainty intervals are considered in the robust optimization for minimizing the worst-case electricity payment while flexibly adjusting the solution robustness. Both approaches are formulated as mixed-integer linear programming (MILP) problems and solved by state-of-the-art MILP solvers. The numerical results show attributes of the two approaches for solving the real-time optimal DR management problem for residential appliances.
700 citations
TL;DR: In this article, a simplified bottom-up load model is presented to generate realistic domestic electricity consumption data on an hourly basis from a few up to thousands of households using input data that is available in public reports and statistics.
Abstract: Electricity consumption data profiles that include details on the consumption can be generated with a bottom-up load models. In these models the load is constructed from elementary load components that can be households or even their individual appliances. In this work a simplified bottom-up model is presented. The model can be used to generate realistic domestic electricity consumption data on an hourly basis from a few up to thousands of households. The model uses input data that is available in public reports and statistics. Two measured data sets from block houses are also applied for statistical analysis, model training, and verification. Our analysis shows that the generated load profiles correlate well with real data. Furthermore, three case studies with generated load data demonstrate some opportunities for appliance level demand side management (DSM). With a mild DSM scheme using cold loads, the daily peak loads can be reduced 7.2% in average. With more severe DSM schemes the peak load at the yearly peak day can be completely levelled with 42% peak reduction and sudden 3 h loss of load can be compensated with 61% mean load reduction. Copyright © 2005 John Wiley & Sons, Ltd.
528 citations
TL;DR: In this article, the optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS).
497 citations
TL;DR: In this paper, the patterns of electricity consumption were studied for 27 representative dwellings in Northern Ireland, and a clear correlation was found between average annual electricity consumption and floor area, and the difference in the annual demand on the grid between detached and terraced houses is between 24 and 30%.
374 citations