Distributed generation on rural electricity networks - a lines company perspective : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Energy Management at Massey University

CD held with Reference copyA number of electricity assets used in rural New Zealand yield a very low return on investment. According to the provisions of the Electricity Act 1992, after 01 April 2013, lines companies may terminate supply to any customer to whom they cannot provide electricity lines services profitably. This research was undertaken to assist the policy makers, lines companies, rural investors on the viability of distributed generation in a rural setting from the point of view of the lines company and the investor as well as to provide recommendations to the problem areas. A dynamic distributed generation model was developed to simulate critical distributed generation scenarios relevant to New Zealand, such as diverse metering arrangements, time dependent electricity prices, peak shaving by load control, peak lopping by dispatchable distributed generation and state subsides, which are not addressed in commercial software. Data required to run the model was collected from a small rural North Island sheep and beef farming community situated at the end of a 26km long radial distribution feeder. Additional operational data were also collected from the community on distributed resources such as solar hot water systems. A number of optimum distributed generation combinations involving a range of technologies under different metering arrangements and price signals were identified for the small and the medium investor. The effect of influencing factors, such as state initiatives and technological growth, on the investor and the lines companies were discussed. Recommendations for future implementation in order to integrate distributed generation on to rural networks were also given. Several key research areas were identified and discussed including low cost micro hydro, wind resource assessment, diversification of the use of the induction generators, voltage flicker and dynamic distributed generation techno-economic forecasting tools

Peak shaving through battery storage for low-voltage enterprises with peak demand pricing

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00-31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency)

Design and analysis of a smart microgrid for a small island in Indonesia

Peer reviewedPublisher PD

Day-ahead optimal battery operation in islanded hybrid energy systems and its impact on greenhouse gas emissions

This paper proposes a management strategy for the daily operation of an isolated hybrid energy system (HES) using heuristic techniques. Incorporation of heuristic techniques to the optimal scheduling in day-head basis allows us to consider the complex characteristics of a specific battery energy storage system (BESS) and the associated electronic converter efficiency. The proposed approach can determine the discharging time to perform the load peak-shaving in an appropriate manner. A recently proposed version of binary particle swarm optimization (BPSO), which incorporates a time-varying mirrored S-shaped (TVMS) transfer function, is proposed for day-ahead scheduling determination. Day-ahead operation and greenhouse gas (GHG) emissions are studied through different operating conditions. The complexity of the optimization problem depends on the available wind resource and its relationship with load profile. In this regard, TVMS-BPSO has important capabilities for global exploration and local exploitation, which makes it a powerful technique able to provide a high-quality solution comparable to that obtained from a genetic algorithm

Final Report: Market and Economic Modelling of the Intelligent Grid

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Energy Storage Systems for Energy Management of Renewables in Distributed Generation Systems

Distributed generation (DG) systems are the key for implementation of micro/smart grids of today, and energy storages are becoming an integral part of such systems. Advancement in technology now ensures power storage and delivery from few seconds to days/months. But an effective management of the distributed energy resources and its storage systems is essential to ensure efficient operation and long service life. This chapter presents the issues faced in integrating renewables in DG and the growing necessity of energy storages. Types of energy storage systems (ESSs) and their applications have also been detailed. A brief literature study on energy management of ESSs in distributed microgrids has also been included. This is followed by a simple case study to illustrate the need and effect of management of ESSs in distributed systems

Energy Management using storage to facilitate high shares of Variable Renewable Energy

Remote islands are a very lucrative market for Variable Renewable Energy (VRE) resources. They rely on expensive fossil fuels, primarily diesel, to suffice their electrical generation demands and to ensure reliability. This not only makes them vulnerable to the fluctuating oil prices in the international market but also depletes their environment. The paper looks into establishing a renewable energy based power generation system facilitated by storage and takes the Island of Bonaire as the case study. Bonaire has good Solar resource summing up to around 1,826 kWh/m2, while a healthy Wind resource until September when it faces low wind speeds until December. Using the actual load profile obtained from the utility at Bonaire; WEB Bonaire, two scenarios are generated using Homer Pro software. The first scenario; business-as-usual, is based on replicating the current power system and establishing a baseline for further comparison. The second scenario; Renewable Energy Scenario, aims to facilitate high shares of Wind and Solar using storage technologies – Hydrogen to be used when the wind resources are low as a seasonal storage, and Lithium Iron Phosphate batteries to absorb surplus energy by VRE technologies and to be used when they are not available on daily basis. The RE scenario lowers the share of Diesel based power generation from 65.78% to 0.53% and results in an LCOE of 12.76€ cents/kWh. The RE scenario demonstrates the efficient use of Hydrogen production and storage over longer periods of times and illustrates its feasibility