Haile-Selassie Rajamani

Evaluation of community virtual power plant under various pricing schemes

Technological advancement on the electricity grid has focused on maximizing its use. This has led to the introduction of energy storage. Energy storage could be used to provide both peak and off-peak services to the grid. Recent work on the use of small units of energy storage like battery has proposed the vehicle to grid system. It is propose in this work to have energy storage device embedded inside the house of the energy consumer. In such a system, consumers with battery energy storage can be aggregated in to a community virtual power plant. In this paper, an optimized energy resource allocation algorithm is presented for a virtual power plant using genetic algorithm. The results show that it is critical to have a pricing scheme that help achieve goals for grid, virtual power plant, and consumers.

Short term energy forecasting techniques for virtual power plants

The advent of smart meter technology has enabled periodic monitoring of consumer energy consumption. Hence, short term energy forecasting is gaining more importance than conventional load forecasting. An Accurate forecasting of energy consumption is indispensable for the proper functioning of a virtual power plant (VPP). This paper focuses on short term energy forecasting in a VPP. The factors that influence energy forecasting in a VPP are identified and an artificial neural network based energy forecasting model is built. The model is tested on Sydney/ New South Wales (NSW) electricity grid. It considers the historical weather data and holidays in Sydney/ NSW and forecasts the energy consumption pattern with sufficient accuracy.

Stochastic approach for active and reactive power management in distribution networks

In this paper, a stochastic method is proposed to assess the amount of active and reactive power that can be injected/absorbed to/from grid within a distribution market environment. Also, the impact of wind power penetration on the reactive and active distribution-locational marginal prices is investigated. Market-based active and reactive optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand. The uncertainties are modeled by Scenario-based approach. The proposed model is examined with 16-bus UK generic distribution system.

Investigating the Impact of Cyber-Attack on Load Profile of Home Energy Management System

Load profile for a household is key to understanding and applying automated load scheduling executed by the Home Energy Management Systems (HEMS). The provision of securing this basic domestic information as well as preventing intruders from being able to accessing and modifying them should be a matter of high priority. Any malicious attack on this data will have serious impact on the performance of the load scheduling algorithms. This paper is an investigation of how the scheduled load profile of a household can be deformed due to false data injection on the original load profile as a result of cyber-attack on the HEMS. Various incremental false data levels are introduced during an optimization process and the corresponding effect on the overall scheduled load profile is evaluated to understand the actual impact of the cyber-attack. Results show that as noise attack level increases, the optimized load profile shrinks and approaches a straight line which is equivalent to the average value of the original load profile. The implication of having such a load profile as a schedule is the obvious excessive disruption of a household’s energy use which results to having appliances switched ON or OFF at highly undesired times of the day thereby exacerbating user inconvenience.

A Comparative Assessment of Embedded Energy Storage and Electric Vehicle Integration in a Community Virtual Power Plant

Among the key objectives of the smart grid technology are to foster the grid integration of renewable energy as well as market participation of domestic energy consumers through demand response program. Energy storage remains a key component of the smart grid. Past works on integration of energy storage at the domestic side of the electricity grid has identified the electric vehicle technology (EV) and the embedded energy storage (EES) technology, etc. However, it was difficult to compare between these technologies in terms of business incentives and technical performance. This was investigated in this work, and the results are presented. It was propose to use percentage difference to compare between VPP with EES and VPP with EV. The results shows that the difference in prosumers incentives between VPP with EES and VPP with EV is very low. It is approximately 0.89%. However, the percentage difference in VPP operator profit between VPP with EES and VPP with EV is very high. It is approximately 85.3%. The VPP makes very high profit in the VPP EES case compared to VPP EV case. The same also applies to the VPP cumulative performance where the percentage difference in the VPP cumulative performance between VPP with EES and VPP with EV is approximately 10.9%. This has implication on the storage mechanism to be integrated in to a VPP at the domestic level as well the business model to be adopted.

Optimization of Community Based Virtual Power Plant with Embedded Storage and Renewable Generation

The current global challenge of climate change has made renewable energy usage very important. There is an ongoing drive for the deployment of renewable energy resource at the domestic level through feed-in tariff, etc. However, the intermittent nature of renewable energy has made storage a key priority. In this work, a community having a solar farm with energy storage embedded in the house of the energy consumers is considered. Consumers within the community are aggregated in to a local virtual power plant. Genetic algorithm was used to develop an optimized energy transaction for the virtual power plant with respect to differential pricing and renewable generation. The results show that it is feasible to have a virtual power plant setup in a local community that involve the use of renewable generation and embedded storage. The results show that both pricing and renewable generation window should be considered as a factor when setting up a virtual power plant that involve the use of storage and renewable generation at the community level. Also, when maximization of battery state of charge is considered as part of an optimization problem in a day ahead market, certain trade-off would have to be made on the profit of the virtual power plant, the incentive of the prosumer, as well as the provision of peak service to the grid.