Cluster-based Aggregate Forecasting for Residential Electricity Demand using Smart Meter Data
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The continuous growth of energy needs and the fact that unpredictable energy demand is mostly served by unsustainable (i.e. fossil-fuel) power generators have given rise to the development of Demand Response (DR) mechanisms for flattening energy demand. Bu ...
This text describes the first application of a novel path flow and origin/destination (OD) matrix estimator for iterated dynamic traffic assignment (DTA) microsimulations. The presented approach, which operates on a trip-based demand representation, is der ...
Coordination of decentralized supply chains using contract design is a problem that has been widely addressed in the literature. We consider a divergent supply chain including a supplier and several retailers producing fashion products with short sale seas ...
Demand Response (DR) has traditionally targeted peak shaving for the optimal allocation of the electricity consumption on a time scale that ranges from minutes to hours. However, with the availability of advanced monitoring and communication infrastructure ...
Assessing customer trust in suppliers with regards to its influencing factors is an important open issue in supply chain management literature. In this paper, a customer trust index is designed as the trust level arising from the information sharing degree ...
Periods of peak consumer demand in today’s electricity sector are expensive to satisfy and can be the source of power failures. One possible solution is the use of demand-side management (DSM) applying dynamic pricing mechanisms. However, instead of reduci ...
Mathematical forecasting approaches can lead to reliable demand forecast in some environments by extrapolating regular patterns in time-series. However, unpredictable events that do not appear in historical data can reduce the usefulness of mathematical fo ...
Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context through extrapolating regular patterns in time-series. However, un ...
Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context, extrapolating regular patterns in series. However unpredictable e ...
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