Smoothing Net Load Demand Variations Using Residential Demand Management

2019 ◽  
Vol 15 (1) ◽  
pp. 390-398 ◽  
Author(s):  
Fadi Elghitani ◽  
Ehab El-Saadany
Keyword(s):  
Demand Management ◽  
Load Demand ◽  
Residential Demand ◽  
Net Load

Results of the largest residential demand management program in Australia

2005 ◽  
Vol 5 (3-4) ◽  
pp. 249-256 ◽  
Author(s):  
A. Turner ◽  
S. White ◽  
K. Beatty ◽  
A. Gregory
Keyword(s):  
Statistical Analysis ◽  
Demand Management ◽  
Evaluation Study ◽  
Management Program ◽  
Control Group ◽  
Water Efficiency ◽  
Total Saving ◽  
Income Category ◽  
Efficiency Measures ◽  
Residential Demand

This paper provides details and the results of an evaluation study carried out on the largest residential demand management program in Australia, the Sydney Water Corporation (SWC) ‘Every Drop Counts’ (EDC) residential retrofit program. The evaluation measured the water savings of program participants and compared them to a control group. Savings of 20.9 ± 2.5 kilolitres per household per annum (kL/hh/a) were found from statistical analysis of water meter readings of the sample of single residential households analysed. These individual savings effectively provide SWC with a potential total saving of 3,344 ± 400 megalitres per annum (ML/a) for the single residential houses retrofitted alone, i.e. 80% of the 200,000 households retrofitted to date. The evaluation identified that no ‘decay’ in average savings were found over the maximum four year period assessed. Other factors evaluated during the study included: analysis of individual water efficiency measures; comparison of savings with other evaluations; and savings related to occupancy ratio, geographical grouping, income category and defined socioeconomic categories.

Control algorithms to mitigate the effect of uncertainties in residential demand management

2022 ◽  
Vol 306 ◽  
pp. 117971
Author(s):  
Gayan Lankeshwara ◽  
Rahul Sharma ◽  
Ruifeng Yan ◽  
Tapan K. Saha
Keyword(s):  
Demand Management ◽  
Control Algorithms ◽  
Residential Demand

scholarly journals Residential demand management using individualised demand aware price policies

2017 ◽  
Author(s):  
Barry Hayes ◽  
Igor Melatti ◽  
Toni Mancini ◽  
Milan Prodanovic ◽  
Enrico Tronci
Keyword(s):  
Demand Management ◽  
Residential Demand ◽  
Price Policies

Time-Varying Characteristic Based Load Forecasting Method for Distribution Network with DGs

2013 ◽  
Vol 448-453 ◽  
pp. 2434-2438
Author(s):  
Ming Xin Zhao ◽  
Yang Li ◽  
Hai Chen ◽  
Wei Liu ◽  
Pan Zhang
Keyword(s):  
Distributed Generation ◽  
Distribution Network ◽  
Load Forecasting ◽  
Time Varying ◽  
Middle Term ◽  
Load Demand ◽  
Forecasting Method ◽  
Load Characteristics ◽  
Net Load

Middle-term and long-term load forecasting is important for planning of distribution network. With DG (distributed generation) integrated into network, the net load demand of HV/MV transformers become more complicated, load forecasting encounters greater challenge than ever. Uncertainty of wind and solar power has greatly influenced the load characteristics. A new load forecasting method for distribution network with DGs is proposed in this paper, which concerns time-varying characteristic of DG output power. Firstly, we get the conventional spatial load forecasting results. Then, using Monte Carlo simulation, we get the time-varying characteristic of DG. Lastly, superposing time-varying characteristics of conventional load and DGs, we can get the net-load forecasting result for distribution network.

scholarly journals Residential Demand Management Using Individualized Demand Aware Price Policies

2017 ◽  
Vol 8 (3) ◽  
pp. 1284-1294 ◽  
Author(s):  
Barry Hayes ◽  
Igor Melatti ◽  
Toni Mancini ◽  
Milan Prodanovic ◽  
Enrico Tronci
Keyword(s):  
Demand Management ◽  
Residential Demand ◽  
Price Policies

scholarly journals Real-Time Economic Dispatch by Accommodating Implications of Uncertain Renewable Energy Resources

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2484-2488
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Real Time ◽  
Economic Dispatch ◽  
Standard Test ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Economic Implications ◽  
Load Demand ◽  
Net Load

The integration of considerable renewable energy resources in power grids has imposed high variability in the net load demand to be seen by conventional generating stations. The real-time economic dispatch (RTED) of modern power systems must consider minute-to-minute variability in the net load demand on the station during a scheduling interval of 5-15 min. The existing methods therefore may not explicitly handle economic implications of power system. This paper proposes a new method for RTED while fully addressing variability in power generation from renewable energy resources and load demand. The method suggests mean PFs for committed generators by conducting (off-line) economic dispatch for each subinterval of 1 min. Mean PFs are evaluated only once, that is just at the beginning of scheduling interval and will continued throughout the interval. This reduces complexity and dimensionality of the proposed method. The simulation results on a standard test bench validate economic competence of proposed approach over that conventional one.

scholarly journals Research on Capacity Configuration and Optimal Operation of Microgrid Energy Storage under Demand Management

2021 ◽  
Vol 329 ◽  
pp. 01015
Author(s):  
Wensheng Li ◽  
Donglei Sun ◽  
Yajin Li ◽  
Xian Wang ◽  
Rui Liu ◽  
...  
Keyword(s):  
Energy Storage ◽  
Demand Management ◽  
Storage System ◽  
Energy Storage System ◽  
Optimal Operation ◽  
Light Storage ◽  
Load Demand ◽  
Practical Engineering ◽  
Consumption Cost ◽  
User Demand

In order to reduce the energy consumption cost, considering the influence of the correlation of photovoltaic output, load demand and peak valley TOU price in different periods on the optical storage capacity configuration, the system operation strategy and capacity configuration principle are determined based on the peak valley TOU price and energy storage charge state information and the actual size of photovoltaic output and load.Integrated with the historical load, time of use electricity price, state of charge, charge discharge power and other constraints of the energy storage system, the minimum objective function is utilized to optimize the output power of energy storage.The effectiveness of the model is verified by an example. The sensitivity analysis shows that different demand tariff rules affect the user demand declaration strategy. The energy storage system planning selects the light storage combination with appropriate capacity according to the demand tariff rules and the change of energy storage investment cost, which has practical engineering value.

scholarly journals Energy flexibility in residential buildings clusters

2020 ◽  
Vol 197 ◽  
pp. 03002
Author(s):  
Alice Mugnini ◽  
Fabio Polonara ◽  
Alessia Arteconi
Keyword(s):  
Energy Demand ◽  
Demand Curve ◽  
Residential Buildings ◽  
Demand Management ◽  
Great Part ◽  
Optimal Strategies ◽  
Electric Heating ◽  
Heat Pumps ◽  
Heating And Cooling ◽  
Residential Demand

The building sector represents one of the most energy-consuming worldwide and a great part of its consumption is accounted for residential demand for space heating and cooling. Although it is necessary to promote the buildings energy efficiency, energy flexibility is also of paramount importance to optimize the balance between demand and supply. In fact, an energy flexible building is defined as able to change, in a planned manner, the shape of its energy demand curve, electrical and thermal, while the comfort of the end-users is still guaranteed. Objective of this work is to exploit the energy demand management ability of different buildings composing a cluster, when their aggregated demand derived from electric heating systems (i.e. heat pumps) is subject to demand response (DR) strategies. Users with different occupancy profile are considered. By supposing to be able to activate the energy flexibility of the single building with thermostatic load control, different scenarios of cluster composition are evaluated in order to provide guidelines to implement optimal strategies for energy flexibility exploitation without drawback effects connected to the event.

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