Four-leg converters with improved common current sharing and selective voltage-quality enhancement for islanded microgrids

Four-leg dc-ac power converters are widely used for the power grids to manage grid voltage unbalance caused by the interconnection of single-phase or three-phase unbalanced loads. These converters can further be connected in parallel to increase the overall power rating. The control of these converters poses a particular challenge if they are placed far apart with no links between them (e.g., in islanded microgrids). This challenge is studied in this paper with each four-leg converter designed to have improved common current sharing and selective voltage-quality enhancement. The common current sharing, including zero sequence component, is necessary since loads are spread over the microgrid and they are hence the common responsibility of all converters. The voltage-quality enhancement consideration should however be more selective since different loads have different sensitivity levels towards voltage disturbances. Converters connected to the more sensitive load buses should therefore be selectively triggered for compensation when voltage unbalances at their protected buses exceed the predefined thresholds. The proposed scheme is therefore different from conventional centralized schemes protecting only a common bus. Simulation and experimental results obtained have verified the effectiveness of the proposed scheme when applied to a four-wire islanded microgrid.

Distributed optimization in transportation and logistics networks

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

An adaptive IEEE 802.15.4 data transmission scheme for smart grid applications

IEEE 802.15.4 networks (also known as ZigBee networks) has the features of low data rate and low power consumption. In this paper we propose an adaptive data transmission scheme which is based on CSMA/CA access control scheme, for applications which may have heavy traffic loads such as smart grids. In the proposed scheme, the personal area network (PAN) coordinator will adaptively broadcast a frame length threshold, which is used by the sensors to make decision whether a data frame should be transmitted directly to the target destinations, or follow a short data request frame. If the data frame is long and prone to collision, use of a short data request frame can efficiently reduce the costs of the potential collision on the energy and bandwidth. Simulation results demonstrate the effectiveness of the proposed scheme with largely improve bandwidth and power efficiency. © 2011 Springer-Verlag.

Modeling impact of both frame collisions and frame corruptions on IEEE 802.15.4 channel access for smart grid applications

IEEE 802.15.4 standard has been recently developed for low power wireless personal area networks. It can find many applications for smart grid, such as data collection, monitoring and control functions. The performance of 802.15.4 networks has been widely studied in the literature. However the main focus has been on the modeling throughput performance with frame collisions. In this paper we propose an analytic model which can model the impact of frame collisions as well as frame corruptions due to channel bit errors. With this model the frame length can be carefully selected to improve system performance. The analytic model can also be used to study the 802.15.4 networks with interference from other co-located networks, such as IEEE 802.11 and Bluetooth networks. © 2011 Springer-Verlag.

Using SPICE for power system simulations

Power system simulation software is a useful tool for teaching the fundamentals of power system design and operation. However, existing commercial packages are not ideal for teaching work-based students because of high-cost, complexity of the software and licensing restrictions. This paper describes a set of power systems libraries that have been developed for use with the free, student-edition of a Micro-Cap Spice that overcomes these problems. In addition, these libraries are easily adapted to include power electronic converter based components into the simulation, such as HVDC, FACTS and smart-grid devices, as well as advanced system control functions. These types of technology are set to become more widespread throughout existing power networks, and their inclusion into a power engineering degree course is therefore becoming increasingly important.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

Novel communication method between power converters for DC micro-grid applications

Communication between power converters is vital for high performance DC micro-grids controls. However, for residential DC micro-grid applications, using external communication link would increase the system cost, and reduce the system flexibility and reliability. This paper presents a novel method to enable the conventional DC/DC converters to transmit data via the common DC Bus. With this technology, cost-effective low bandwidth communication links between power converters can be established within a DC micro-grid, and advanced distributed control algorithms can be developed. A reliable communication with 2 kbps transmission rate has been implemented between the Boost converters through the common input DC bus.

An adaptive IEEE 802.15.4 MAC layer transmission scheme for applications with heterogeneous traffic

IEEE 802.15.4 networks has the features of low data rate and low power consumption. It is a strong candidate technique for wireless sensor networks and can find many applications to smart grid. However, due to the low network and energy capacities it is critical to maximize the bandwidth and energy efficiencies of 802.15.4 networks. In this paper we propose an adaptive data transmission scheme with CSMA/CA access control, for applications which may have heavy traffic loads such as smart grids. The adaptive access control is simple to implement. Its compatibility with legacy 802.15.4 devices can be maintained. Simulation results demonstrate the effectiveness of the proposed scheme with largely improved bandwidth and power efficiency. © 2013 International Information Institute.

A review of the effects of distributed energy resources and power-electronic controlled loading on distribution network stability

This paper looks at potential distribution network stability problems under the Smart Grid scenario. This is to consider distributed energy resources (DERs) e.g. renewable power generations and intelligent loads with power-electronic controlled converters. The background of this topic is introduced and potential problems are defined from conventional power system stability and power electronic system stability theories. Challenges are identified with possible solutions from steady-state limits, small-signal, and large-signal stability indexes and criteria. Parallel computation techniques might be included for simulation or simplification approaches are required for a largescale distribution network analysis.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.