Conference paper Open Access

Modelling and simulation of a predictive BESS controller based on load forecasting in a South European island power system

Chapaloglou, Spyridon; Nesiadis, Athanasios; Atsonios, Konstantinos; Nikolopoulos, Nikos; Grammelis, Panagiotis; Kakaras, Emmanuel


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    <subfield code="a">Artificial Neural Networks</subfield>
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    <subfield code="a">Battery Energy Storage System</subfield>
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    <subfield code="a">Energy Management System</subfield>
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    <subfield code="a">Load Forecast</subfield>
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    <subfield code="a">Peak Shaving</subfield>
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    <subfield code="a">Renewable Energy</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
    <subfield code="a">Atsonios, Konstantinos</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
    <subfield code="a">Nikolopoulos, Nikos</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
    <subfield code="a">Grammelis, Panagiotis</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
    <subfield code="a">Kakaras, Emmanuel</subfield>
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    <subfield code="c">2018-06-20</subfield>
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    <subfield code="u">Centre for Research &amp; Technology Hellas /Chemical Process and Energy Resources Institute, 6th km. Charilaou-Thermis, GR 57001 Thermi, Greece</subfield>
    <subfield code="a">Chapaloglou, Spyridon</subfield>
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    <subfield code="a">Modelling and simulation of a predictive BESS controller based on load forecasting in a South European island power system</subfield>
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    <subfield code="c">731249</subfield>
    <subfield code="a">SMart IsLand Energy systems</subfield>
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    <subfield code="a">&lt;p&gt;Modern isolated power grids are constantly evolving to adopt smart grid concepts that can permit higher&lt;br&gt;
renewable energy penetration and energy management optimization, in the view of a sustainable RES based&lt;br&gt;
energy production EU policy with reduced pollutant emissions. Nevertheless, many islandic power systems&lt;br&gt;
like the islands in Southern Europe are still depending on oil-fired diesel engines, while the renewable energy&lt;br&gt;
production is limited due to financial, technical and environmental reasons. In this study, the power system of&lt;br&gt;
a typical non-interconnected South European island consisting of diesel generators and a PV farm is modelled&lt;br&gt;
and simulated. Scope of this paper is to examine the ability of a Battery Energy Storage System (BESS) to&lt;br&gt;
achieve load peak shaving combined with maximization of the PV power penetration into the grid leading to&lt;br&gt;
pre-planned zero curtailment. For this purpose, a novel peak shaving algorithm is developed and implemented&lt;br&gt;
into an Energy Management System (EMS), for optimal scheduling of the diesel engines. Thereinafter,&lt;br&gt;
dynamic simulations of the island&amp;rsquo;s power system are carried out employing a predictive control strategy for&lt;br&gt;
different time scales, ranging from a supervisor BESS controller based on load forecasting, to a real-time&lt;br&gt;
battery power regulation. The predictive BESS controller is based on future consumption values forecasting,&lt;br&gt;
which in turn result from an Artificial Neural Network (ANN) and an optimization procedure taking into account&lt;br&gt;
PV power generation and a peak shaving threshold. Thus, a new diesel engine scheduling is obtained capable&lt;br&gt;
of replacing the maximum peak power demand with renewable power while at the same time load curve&lt;br&gt;
smoothening and reduced diesel generators ramps-up are achieved. The simulations are executed in APROS&lt;br&gt;
(Advanced Process Simulator) dynamic simulation platform, using built-in components for the BESS modelling,&lt;br&gt;
an external model for load forecasting and a user-developed EMS structure.&lt;/p&gt;</subfield>
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