Energy management system control and experiment for future home

Abstract

to enable zero net-energy consumption and optimal power management for future homes or buildings, the dc electric distribution systems (dc nano-grid) finds feasibility and simplicity for integrating multi-type renewable energy sources. However, integrating all the sources and loads in a simple, reliable and smart way is still challenging. This paper introduces a 380V emulator testbed of 10kW, and then proposes a distributed droop control method to integrate all source converters. Control functions in components level and system level will be defined and discussed, and energy storage management and its control law in dc nano-grid is proposed. System level energy management control strategies in a day/24 hours are examined and discussed with considerations of residential load demand profile, local renewable energy source profile and schedules of electricity rate. System level static experiments within 24h are given for verification purposes.

Designing near-optimal policies for energy management in a stochastic environment

“…This behavior is evident from the subplot titled, Power output from Battery kW. The third scenario arises during the hour interval [8,9] ∪ (15,17] when the sign of the present imbalance differs from the sign of expected future imbalance. In this case, the policy is designed to not alter the battery state.…”

“…It must be noted that the admissible decision space consists of the decisions which, when implemented do not result in the violation of the system constraints (refer to Appendix A for details). Also, from Equation 8, we note that u k and v k are not independently determined. Therefore, the corresponding policies π G and π B are dependent.…”

“…A review of topologies and technologies for nanogrid energy management was presented in [5]. In [8], a distributed droop control for source converters combined with heuristic control laws for energy storage management is presented. On the other hand, we consider a non-controllable forecast-driven PV generation model with the objective of optimizing operational cost using energy storage.…”

Power Quality in DC Power Distribution Systems and Microgrids

“…DC architectures have been explored for data center applications with the goal of increasing efficiency, in part by eliminating the need for an inverter on the UPS end of the power distribution path and the rectifier on the load end of the power path [2,3]. In commercial or residential buildings, the use of DC distribution architectures is proposed in literature to increase efficiency by allowing the use of larger and more efficient centralized distribution rectification stages rather than individual point-of-load rectifiers for the loads requiring DC [4][5][6]. Other proposed applications for DC architectures are for microgrid applications to more efficiently integrate energy storage and distributed renewable generation that produce DC voltage, such as in suggested cellular communication microgrids [7,8].…”

Optimized energy management system to reduce fuel consumption in remote military microgrids

“…The optimization strategy includes lifetime and economic considerations for the BESS, thus managing the cost of the microgrid while reducing fuel consumption. Applications of online and offline optimization techniques in the management of energy supply and demand are widely available as in [3], [4] and [5] and more recently in [6] and [7]. They are applied not only to microgrids, as in [8], but also to assess the impact on bigger energy system, as in [9].…”