One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids

Increasingly, residential customers are deploying PV units to lower electricity bills and contribute to a more sustainable use of resources. This selective decentralization of power generation, however, creates significant challenges, because current transmission and distribution grids were designed for centralized power generation and unidirectional flows. Restructuring residential neighborhoods as residential microgrids might solve these problems to an extent, but energy retailers and system operators have yet to identify ways of fitting residential microgrids into the energy value chain. One promising way of doing so is the tailoring of residential microgrid tariffs, as this encourages grid-stabilizing behavior and fairly re-distributes the associated costs. We thus identify a set of twelve tariff candidates and estimate their probable effects on energy bills as well as load and generation profiles. Specifically, we model 100 residential microgrids and simulate how these microgrids might respond to each of the twelve tariffs. Our analyses reveal three important insights. Number one: volumetric tariffs would not only inflate electricity bills but also encourage sharp load and generation peaks, while failing to reliably allocate system costs. Number two: under tariffs with capacity charges, time-varying rates would have little impact on both electricity bills and load and generation peaks. Number three: tariffs that bill system and energy retailer costs via capacity and customer charges respectively would lower electricity bills, foster peak shaving, and facilitate stable cost allocation

Control and Stability of Residential Microgrid with Grid-Forming Prosumers

The rise of the prosumers (producers-consumers), residential customers equipped with behind-the-meter distributed energy resources (DER), such as battery storage and rooftop solar PV, offers an opportunity to use prosumer-owned DER innovatively. The thesis rests on the premise that prosumers equipped with grid-forming inverters can not only provide inertia to improve the frequency performance of the bulk grid but also support islanded operation of residential microgrids (low-voltage distribution feeder operated in an islanded mode), which can improve distribution grids’ resilience and reliability without purposely designing low-voltage (LV) distribution feeders as microgrids. Today, grid-following control is predominantly used to control prosumer DER, by which the prosumers behave as controlled current sources. These grid-following prosumers deliver active and reactive power by staying synchronized with the existing grid. However, they cannot operate if disconnected from the main grid due to the lack of voltage reference. This gives rise to the increasing interest in the use of grid-forming power converters, by which the prosumers behave as voltage sources. Grid-forming converters regulate their output voltage according to the reference of their own and exhibit load sharing with other prosumers even in islanded operation. Making use of grid-forming prosumers opens up opportunities to improve distribution grids’ resilience and enhance the genuine inertia of highly renewable-penetrated power systems. Firstly, electricity networks in many regional communities are prone to frequent power outages. Instead of purposely designing the community as a microgrid with dedicated grid-forming equipment, the LV feeder can be turned into a residential microgrid with multiple paralleled grid-forming prosumers. In this case, the LV feeder can operate in both grid-connected and islanded modes. Secondly, gridforming prosumers in the residential microgrid behave as voltage sources that respond naturally to the varying loads in the system. This is much like synchronous machines extracting kinetic energy from rotating masses. “Genuine” system inertia is thus enhanced, which is fundamentally different from the “emulated” inertia by fast frequency response (FFR) from grid-following converters. Against this backdrop, this thesis mainly focuses on two aspects. The first is the small-signal stability of such residential microgrids. In particular, the impact of the increasing number of grid-forming prosumers is studied based on the linearised model. The impact of the various dynamic response of primary sources is also investigated. The second is the control of the grid-forming prosumers aiming to provide sufficient inertia for the system. The control is focused on both the inverters and the DC-stage converters. Specifically, the thesis proposes an advanced controller for the DC-stage converters based on active disturbance rejection control (ADRC), which observes and rejects the “total disturbance” of the system, thereby enhancing the inertial response provided by prosumer DER. In addition, to make better use of the energy from prosumer-owned DER, an adaptive droop controller based on a piecewise power function is proposed, which ensures that residential ESS provide little power in the steady state while supplying sufficient power to cater for the demand variation during the transient state. Proposed strategies are verified by time-domain simulations

Optimal energy management for a residential microgrid including a vehicle-to-grid system

An optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-togrid system and renewable energy sources. In order to achieve a realistic and convenient management, we take into account: (1) the household load split into three different profiles depending on the characteristics of the elements considered; (2) a realistic approach to owner behavior by introducing the novel concept of range anxiety; (3) the vehicle battery management considering the mobility profile of the owner and (4) different domestic renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The results obtained show daily costs in the range of 2.82eto 3.33e; the proximity of these values to the actual energy costs for Spanish households validate the modeling. The experimental results of applying the designed managing strategies show daily costs savings of nearly 10%.Postprint (author’s final draft

Comparative study of energy management strategies in collaborative microgrids of domestic prosumers

An optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-togrid system and renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The microgrids are ubicated in Xermade, Galicia, Spain.Postprint (published version

Joint Control of Manufacturing and Onsite Microgrid System Via Novel Neural-Network Integrated Reinforcement Learning Algorithms

Microgrid is a promising technology of distributed energy supply system, which consists of storage devices, generation capacities including renewable sources, and controllable loads. It has been widely investigated and applied for residential and commercial end-use customers as well as critical facilities. In this paper, we propose a joint state-based dynamic control model on microgrids and manufacturing systems where optimal controls for both sides are implemented to coordinate the energy demand and supply so that the overall production cost can be minimized considering the constraint of production target. Markov Decision Process (MDP) is used to formulate the decision-making procedure. The main computing challenge to solve the formulated MDP lies in the co-existence of both discrete and continuous parts of the high-dimensional state/action space that are intertwined with constraints. A novel reinforcement learning algorithm that leverages both Temporal Difference (TD) and Deterministic Policy Gradient (DPG) algorithms is proposed to address the computation challenge. Experiments for a manufacturing system with an onsite microgrid system with renewable sources have been implemented to justify the effectiveness of the proposed method