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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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.2552035", 
  "language": "eng", 
  "title": "Modelling and simulation of a predictive BESS controller based on load forecasting in a South European island power system", 
  "issued": {
    "date-parts": [
      [
        2018, 
        6, 
        20
      ]
    ]
  }, 
  "abstract": "<p>Modern isolated power grids are constantly evolving to adopt smart grid concepts that can permit higher<br>\nrenewable energy penetration and energy management optimization, in the view of a sustainable RES based<br>\nenergy production EU policy with reduced pollutant emissions. Nevertheless, many islandic power systems<br>\nlike the islands in Southern Europe are still depending on oil-fired diesel engines, while the renewable energy<br>\nproduction is limited due to financial, technical and environmental reasons. In this study, the power system of<br>\na typical non-interconnected South European island consisting of diesel generators and a PV farm is modelled<br>\nand simulated. Scope of this paper is to examine the ability of a Battery Energy Storage System (BESS) to<br>\nachieve load peak shaving combined with maximization of the PV power penetration into the grid leading to<br>\npre-planned zero curtailment. For this purpose, a novel peak shaving algorithm is developed and implemented<br>\ninto an Energy Management System (EMS), for optimal scheduling of the diesel engines. Thereinafter,<br>\ndynamic simulations of the island&rsquo;s power system are carried out employing a predictive control strategy for<br>\ndifferent time scales, ranging from a supervisor BESS controller based on load forecasting, to a real-time<br>\nbattery power regulation. The predictive BESS controller is based on future consumption values forecasting,<br>\nwhich in turn result from an Artificial Neural Network (ANN) and an optimization procedure taking into account<br>\nPV power generation and a peak shaving threshold. Thus, a new diesel engine scheduling is obtained capable<br>\nof replacing the maximum peak power demand with renewable power while at the same time load curve<br>\nsmoothening and reduced diesel generators ramps-up are achieved. The simulations are executed in APROS<br>\n(Advanced Process Simulator) dynamic simulation platform, using built-in components for the BESS modelling,<br>\nan external model for load forecasting and a user-developed EMS structure.</p>", 
  "author": [
    {
      "family": "Chapaloglou, Spyridon"
    }, 
    {
      "family": "Nesiadis, Athanasios"
    }, 
    {
      "family": "Atsonios, Konstantinos"
    }, 
    {
      "family": "Nikolopoulos, Nikos"
    }, 
    {
      "family": "Grammelis, Panagiotis"
    }, 
    {
      "family": "Kakaras, Emmanuel"
    }
  ], 
  "type": "paper-conference", 
  "id": "2552035"
}
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