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In this paper, we experimentally demonstrate the performance of the recently proposed Energy Packet Switch (EPS) for energy distribution. The N × M EPS aggregates the energy from N sources and dispatches energy to M outputs, each of which feeds one or many loads. Energy is distributed from a source to a load in the form of energy packets. The operation of the EPS is an enabler device to realize a digital microgrid. We carry out exhaustive experiments to show that the EPS grants energy to keep demand satisfied and even in cases when the demand overwhelms the EPS capacity. Results of the experiments show that the EPS ably grants all energy requests that fall within its capacity, and it controls the distribution of energy under extenuating conditions by approaching a level of fairness. The experiments also show the average time that a request waits for the corresponding grant. 

In this paper, we propose the greedy smallest-cost-rate path first (GRASP) algorithm to route power from sources to loads in a digital microgrid (DMG). Routing of power from distributed energy resources (DERs) to loads of a DMG comprises matching loads to DERs and the selection of the smallest-cost-rate path from a load to its supplying DERs. In such a microgrid, one DER may supply power to one or many loads, and one or many DERs may supply the power requested by a load. Because the optimal method is NP-hard, GRASP addresses this high complexity by using heuristics to match sources and loads and to select the smallest-cost-rate paths in the DMG. We compare the cost achieved by GRASP and an optimal method based on integer linear programming on different IEEE test feeders and other test networks. The comparison shows the trade-offs between lowering complexity and achieving optimal-cost paths. The results show that the cost incurred by GRASP approaches that of the optimal solution by small margins. In the adopted networks, GRASP trades its lower complexity for up to 18% higher costs than those achieved by the optimal solution. 

We propose the design of an energy packet switch for forwarding and delivery of energy in digital power grids in this paper. The proposed switch may receive energy from one or multiple power sources, store and forward it in the form of energy packets to requesting loads connected to one or multiple ports of the switch. Energy packets carry discrete amounts of energy for a finely controlled supply. Loads receive discrete amounts of energy through packets rather than a continuing and discretionary energy flow. Using energy packets may help manage the delivery of power in a more reliable, robust, and economical form than that used by the present power grid. The control and management of the proposed switch are based on a request-grant protocol. The switch uses a data network for the transmission of these requests and grants. The energy packet switch may be the centerpiece for creating infrastructure in the realization of the digital power grid. The design of the energy packet switch is based on shared supercapacitors to shape and manage discretization of energy. We introduce the design and analysis of the electrical properties of the proposed switch and describe the procedure used in the switch to determine the amount of energy transmitted to requesting loads. 

The Digital Power Network (DPN) is an energy-on-demand approach. In terms of Internet of Things (IoT), it treats the energy itself as a `thing' to be manipulated (in contrast to energy as the `thing's enabler'). The approach is mostly appropriate for energy starving micro-grids with limited capacity, such as a generator for the home while the power grid is down. The process starts with a request of a user (such as, appliance) for energy. Each appliance, energy source or energy storage has an address which is able to communicate its status. A network server, collects all requests and optimizes the energy dissemination based on priority and availability. Energy is then routed in discrete units to each particular address (say air-condition, or, A/C unit). Contrary to packets of data over a computer network whose data bits are characterized by well-behaved voltage and current values at high frequencies, here we deal with energy demands at highvoltage, low-frequency and fluctuating current. For example, turning a motor ON requires 8 times more power than the level needed to maintain a steady states operation. Our approach is seamlessly integrating all energy resources (including alternative sources), energy storage units and the loads since they are but addresses in the network. Optimization of energy requests and the analysis of satisfying these requests is the topic of this paper. Under energy constraints and unlike the current power grid, for example, some energy requests are queued and granted later. While the ultimate goal is to fuse information and energy together through energy digitization, in its simplest form, this micro-grid can be realized by overlaying an auxiliary (communication) network of controllers on top of an energy delivery network and coupling the two through an array of addressable digital power switches. 

In the current grid, power is available at all times, to all users, indiscriminately. This makes the grid vulnerable to sporadic demands and much effort has been invested to mitigate their effect. We offer here a digital approach to power distribution: an energy-on-demand approach in which the user initiates an energy request to the server of the energy provider before receiving the energy. Considering a micro-grid with a mix of generators (sustainable and other sources), the server optimizes the entire power network before granting the energy requests, fully or partially. The energy is packetized and is routed to the user's address by an array of switches. For example, in an office building, the energy provider may queue energy requests by some air-condition units and grant these requests later. During recovery from a blackout, pockets of instability may be isolated by their unusual energy demands. In its simplest form, this network can be realized by overlaying an auxiliary (control, or, data) network on top of an energy delivery network and coupling the two through an array of addressable digital power switches. In assessing this approach, we are concentrating in this paper on the management of energy requests by using statistical models. An energy network with a limited channel capacity and the optimal path for energy flow in a standard IEEE 39 bus are considered. 

We present experiments with combined reactive and resistive loads on a testbed based on the Controlled-Delivery power Grid (CDG) concept. The CDG is a novel data-based paradigm for distribution of energy in smart cities and smart buildings. This approach to the power grid distributes controlled amounts of power of loads following a request-grant protocol performed through a parallel data network. This network is used as a data plane that notifies the energy supplier about requests and inform loads of the amount of granted power. The energy supplier decides the load, amount, and the time power is granted. Each load is associated with a network address, which is used at the time when power is requested and granted. In this way, power is only delivered to selected loads. Knowing the amount of power being supplied in the CDG requires knowing the precise amount of power demand before this is requested. While the concept works well for an array of resistive loads, it is unclear how to apply it to reactive loads, such as motors, whose power consumption varies over time. Therefore, in this paper, we implement a testbed with multiple loads, two light bulbs as resistive loads and an electrical motor as a reactive load. We then propose to use power profiles for the adoption of the request-grant protocol in the CDG concept. We adopt the use of power profiles to leverage the generation of power requests and evaluate the efficiency of the request-grant protocol on the amount of supplied power. In addition, the deviation of delivered power in the data and power planes is evaluated and results show that the digitized power profile of the reactive loads enables the issuing of power requests for such loads with high accuracy. 

We present a feasibility analysis of the controlled delivery power grid (CDG) that uses aggregated power request by users to reduce communications overhead. The CDG, as an approach to the power grid, uses a data network to communicate requests and grants of power in the distribution of electrical power. These requests and grants allow the energy supplier know the power demand in advance and to designate the loads and the time when power is supplied to them. Each load is assigned a power-network address that is used for communication of requests and grants with the energy supplier. With addressed loads, power is only delivered to selected loads. However, issuing a request for power before delivery takes place requires knowing the demand of power the load consumes during the operation interval. However, it is a general concern that having issuing requests in a time-slot basis may risk request losses and therefore, generate intermittent supply. Therefore, we propose request aggregation to minimize the number of requests issued. We show by simulation that the CDG with request aggregation attains high performance, in terms of satisfaction ratio and waiting time for power supply. 

Resilience of the power grid is most challenged at power blackouts since the issues that led to it may not be fully resolved by the time the power is back. In this paper, a Real-Time Energy Management Algorithm (RTEMA) has been developed to increase the resilience of power systems based on the controlled delivery grid (CDG) concept. In a CDG, loads communicate with a central controller, periodically sending requests for power. The central controller runs an algorithm, based on which it may decide whether to grant the requested energy fully or partially. Therefore, the CDG limits loads discretionary access to electric energy until all problems are resolved. The developed algorithm aims at granting most or all of the requested loads, while maintaining the health of the power system (i.e. the voltage at each bus, and the line loading are within acceptable limits), and minimizing the overall losses. An IEEE 30-bus standard Test Case, encountering a blackout condition, with high penetration of microgrids, has been used to test the developed algorithm. Results proved that the developed algorithm with the CDG have the potential to substantially increase the resilience of power systems.