113 research outputs found

    An NSGA-II based Multi-Objective Approach for Distribution System Voltage Control

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    The aim of this work is to offer a voltage control strategy for distribution networks that experience voltage unbalance due to single phase and unbalanced loads and voltage rise due to high penetration of Distributed Generation units. The objectives are minimization of voltage imbalance on each node and total power losses on the entire network. The control of node voltages by Distributed Generation units has potential to clash with the more traditional method of voltage control adopted by Distribution Network Operators namely, tap changing voltage regulators and shunt capacitors. We look at a coordinated method of voltage control that solves the multi-objective optimization problem of voltage profile improvement and power loss reduction using a Pareto optimal and elitist evolutionary optimization algorithm called Non-dominated Sorting Genetic Algorithm II (NSGA-II). The study system is the IEEE 123 bus distribution test feeder which is highly unbalanced and includes most of the elements of a real network

    An Object-Oriented Framework for Analysis of MV/LV Distribution Systems

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    This work was conducted as part of the AMEN (Agentbased Modelling of Electricity Networks) project, funded by the Engineering and Physical Sciences Research Council in the UK under Grant Reference EP/K033492/1.The interest of this work is in designing and developing a simulation package for comprehensive analysis of a distribution system based on object-oriented principles. Towards such an objective, we propose a design of a framework based on an object-oriented approach that is capable of handling such features and yet is simple and flexible enough for further extension. Here, we present a novel derivation of an object oriented methodology to firstly model the various components of a present day distribution system, and then to solve for the power flows across the system. Innovative aspects of the implementation of the derived system are how the various components are represented for power flow calculations using a standard backward/forward algorithm. An IEEE test feeder is used to demonstrate the framework. This work is of interest to model developers, distribution network planners, software designers and most importantly to users in the academia and industry

    Managing complexity in the smart grid through a new approach to demand response

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    CASCADE was a consortium project with Cranfield UniversityAdoption of weather-dependent renewable generation of electricity has introduced additional complexity to the challenge of maintaining a dynamic equilibrium between generation and electricity demand. At the same time the need for electricity to power heating and transport in place of fossil fuels will lead to congestion in distribution networks. Part of the solution will be to manage domestic electricity demand using signals between the smart grid and smart home, but this must be done in a way that does not provoke further instability. We use an agent-based model of household electricity consumption and supply to show how the complexity of domestic demand can be shaped allowing it to make a contribution to system stability. A possible role for this method in balancing conflicting interests between electricity consumers, suppliers, and distribution network operators is discussedEPSRC under the CASCADE project (EP/GO59969/1

    Will domestic consumers take up the Renewable Heat Incentive? An analysis of the barriers to heat pump adoption using agent-based modelling

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    Project name is AMEN from Agent-based Modelling of Electricity Networks.The UK Government introduced the tariff-based domestic Renewable Heat Incentive (RHI) in April 2014 to encourage installation of renewable heat technologies as a key component of its carbon reduction policy. Of these, heat pumps are considered to be the most promising for widespread adoption and as such are the subject of this paper. Pilot studies prior to introduction of the policy identified non-financial barriers to uptake, such as the "hassle factor" involved, and initial figures indeed indicate that uptake is lower than expected. We analyse these non-financial barriers using an agent-based model and conclude that there is a tipping point beyond which adoption is likely to fall very sharply. We suggest that the RHI's complex and stringent compliance requirements for home inspections and heat emitter performance may well have driven adoption past this point and that further intervention may be required if the key aims of the RHI are to be achieved

    The original Stonehenge? A dismantled stone circle in the Preseli Hills of west Wales

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    The discovery of a dismantled stone circle—close to Stonehenge’s bluestone quarries in west Wales— raises the possibility that a 900-year-old legend about Stonehenge being built from an earlier stone circle contains a grain of truth. Radiocarbon and OSL dating of Waun Mawn indicate construction c. 3000 BC, shortly before the initial construction of Stonehenge. The identical diameters of Waun Mawn and the enclosing ditch of Stonehenge, and their orientations on the midsummer solstice sunrise, suggest that at least part of the Waun Mawn circle was brought from west Wales to Salisbury Plain. This interpretation complements recent isotope work that supports a hypothesis of migration of both peo- ple and animals from Wales to Stonehenge

    An agent based model for optimal generation mix based on price elasticity of aggregated consumer demand

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    This work has its interests in the relation between the generation mix within a power system and the elasticity of demand based on the prices emerging from the short term electricity market. The paper starts by describing a new agent-based modelling framework that involves electricity producers, consumers and suppliers as agents participating in a market environment. The framework allows for investigating the effect of demand elasticities on bidding of generators in the short term market and its influence on their revenue in the long term. We focus on the increasingly important issue of renewable technology such as wind generation and the volatility it brings into the electricity market. Specifically we investigate three scenarios with varying mix of generating technologies such as coal, gas and wind turbines and measure the aggregate demand response to signals such as the System Buy Prices (SBP) emerging out of the balancing market

    Agent-based modelling of the UK short term electricity market: effects of intermittent wind power

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    This work focuses on modelling the electricity trading and market mechanism currently in place in the UK, using an agent-based approach and a learning strategy for the agents to update their bidding rules. The ongoing consultations by the Department of Energy and Climate Change on the possible models for a capacity mechanism reflect the unavoidable shift towards low-carbon and more intermittent sources of generation. One of the issues of concern is the way the system operator adapts the balancing mechanism to run in a more efficient and economical way. Here we present an agent-based model comprising two interconnected parts: a representation of the power exchange and a model of the balancing mechanism along with the settlement system. In order to assess the influence of different types of generation on the system balancing prices, we model the generating units based on the size and type of fuel involved. The agent-based model incorporates the operating decisions and control mechanisms of the system operator, and the functions of various trading entities such as generators and suppliers participating within this market. Based on this model, we report investigations into the effect of high penetrations of distributed intermittent generation in influencing the energy balancing prices
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