Simplified Algorithm for Dynamic Demand Response in Smart Homes Under Smart Grid Environment

Abstract

Under Smart Grid environment, the consumers may respond to incentive-based smart energy tariffs for a particular consumption pattern. Demand Response (DR) is a portfolio of signaling schemes from the utility to the consumers for load shifting/shedding with a given deadline. The signaling schemes include Time-of-Use (ToU) pricing, Maximum Demand Limit (MDL) signals etc. This paper proposes a DR algorithm which schedules the operation of home appliances/loads through a minimization problem. The category of loads and their operational timings in a day have been considered as the operational parameters of the system. These operational parameters determine the dynamic priority of a load, which is an intermediate step of this algorithm. The ToU pricing, MDL signals, and the dynamic priority of loads are the constraints in this formulated minimization problem, which yields an optimal schedule of operation for each participating load within the consumer provided duration. The objective is to flatten the daily load curve of a smart home by distributing the operation of its appliances in possible low-price intervals without violating the MDL constraint. This proposed algorithm is simulated in MATLAB environment against various test cases. The obtained results are plotted to depict significant monetary savings and flattened load curves.

Demand Response Model for Hardware Implementation

“…The optimization model considers consumer's net revenue maximization, i.e., the maximization of the difference between the revenue obtained from selling the excess generation to the grid and buying electricity costs, subject to a set of constraints. The mathematical formulation of the developed model is given by (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16), where the variables and explanation of each equation are given at the end of the addressed mathematical formulation. obtained for the simulation period T, where λvt and λct are the energy selling and buying price, respectively; Pvt and Pct are the power sold and bought from the grid, respectively, all of them considered at a time instant t, that in this paper is set to a 15-minute time period.…”

“…However, it really matters to develop algorithms that allow consumers to keep load management autonomy, guaranteeing and enhancing their wellbeing. In addition, the existence of an adequate interface tool between the mathematical algorithm, controllable loads (CL) and the consumer itself, is preponderant to domestic consumers' inclusion into load management and to consolidate consumers as active stakeholders in the power grid management [5].…”

Heuristic DRP‐DG optimization strategy adopted for maximizing total social welfare in the real time Indian utility network

“…The participation of customers in energy management strategies greatly helps in reducing the maximum peak demand [22]. Load priority is employed to fix the dynamic load scheduling in a residential smart grid environment [23]. The time of use (TOU) strategy introduced in [24] reduces the peak of the load curve and thus aids in cost saving.…”