A Survey on Home Energy Management <s> C. ENERGY BILLING SCHEMES <s> In this paper, we propose mathematical optimization models of household energy units to optimally control the major residential energy loads while preserving the user preferences. User comfort is modelled in a simple way, which considers appliance class, user preferences and weather conditions. The wind-driven optimization (WDO) algorithm with the objective function of comfort maximization along with minimum electricity cost is defined and implemented. On the other hand, for maximum electricity bill and peak reduction, min-max regret-based knapsack problem (K-WDO) algorithm is used. To validate the effectiveness of the proposed algorithms, extensive simulations are conducted for several scenarios. The simulations show that the proposed algorithms provide with the best optimal results with a fast convergence rate, as compared to the existing techniques. <s> BIB001 </s> A Survey on Home Energy Management <s> C. ENERGY BILLING SCHEMES <s> Over the last few years, the fast-growing energy needs across the world have intensified a central challenge: how to reduce the generation and operation costs in power systems and, in parallel, to minimize the hydrocarbon emissions. Moreover, one-quarter of world's population still lacks access to electricity, as the cost of building conventional power grids is not affordable by third world countries. On the other hand, behind-the-meter (BTM) energy systems offer cost-effective solutions to aforementioned challenges, as they enable end-users to satisfy their energy needs with distributed energy generation and storage technologies. To that end, this paper presents a detailed survey of BTM energy management systems. The paper starts with the classification of the electrical loads with respect to their physical properties, priority ranking, and sizes. Next, the literature on BTM energy management systems is systematically classified into three main categories: technology layer, economic layer, and social layer. The technology layer spans the studies related to power systems including distributed generation and storage technologies, whereas the economic layer shows how economic incentives along with optimization and scheduling techniques are employed to shape the energy consumption. The social layer, on the other hand, presents the recent studies on how to employ social sciences to reduce the energy consumption without requiring any technological upgrades. This paper also provides an overview of the enabling technologies and standards for communication, sensing, and monitoring purposes. In the final part, a case study is provided to illustrate an implementation of the system. <s> BIB002
In the past, utility companies commonly used to consider flat rate-based pricing, being customers charged according to a given static rate per energy consumed unit. Recently, owing to technological advances on smart metering, dynamic billing schemes have become increasingly preponderant. Five main billing approaches can be found in the literature (see e.g. BIB002 , BIB001 ), namely: (a) All-in-rate -billing is carried out at a given static rate, which remains unchanged throughout the day. (b) TOU -splits a given day into several periods. For each period, energy is billed at a fixed rate. Periods usually change over time, as well as the underlying billing rates. Periods and energy prices can depend on the season of the year, day of the week, or any other criterion. (c) CPP -defines a peak rate at which customers are billed during critically overloaded periods. These periods are defined by the utility, based on a threshold regarding the total consumption for a customer. In the remainder of the time, this approach is exactly as TOU. (d) RTP -energy tariffs are updated at a given rate, usually on hourly or daily basis. (e) Inclining Block Rate (IBR) -IBR considers a unit electricity rate, which increases with consumption in blocks of several hundred kWh. By considering higher demands more expensive, this billing scheme promotes load distribution over time.