Electricity market modelling with photovoltaic active and reactive power generation A. G. Petoussis*. S. G. Petoussis**. X.-P. Zhang***. G. E. Georghiou ****. M. Patsalides****. G. Makrides****. K. R. Godfrey*. * School of Engineering, University of Warwick, Coventry, CV4 7AL, UK (e-mails: a.petoussis@warwick.ac.uk, k.r.godfrey@warwick.ac.uk). ** Network Business Unit, Electricity Authority of Cyprus, Nicosia, CY-1399, Cyprus (e-mail: spetousis@eac.com.cy). *** School of Electronic, Electrical and Computer Engineering, University of Birmingham, Birmingham, B15 2TT, UK (e-mail: x.p.zhang@bham.ac.uk). **** Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, CY-1678, Cyprus (e-mails: geg@ucy.ac.cy, ee03pm1@ucy.ac.cy, eep5mg1@ucy.ac.cy). Abstract: Renewable energy systems are increasingly employed all over the world in order to provide alternative sources of electricity production and reduce CO 2 emissions from conventional power plants. However, as the density of renewable systems increases, certain issues arise that need to be addressed. In particular, for photovoltaic (PV) systems connected to the grid, one parameter of importance is the variation of the PV power output with respect to the intensity of solar irradiance. This paper investigates the impact of the active and reactive power injected to the grid by PV systems, on the electricity market equilibrium, using the linear Supply Function Equilibrium (SFE) model. Numerical results for a 5-bus and the IEEE 57-bus systems, which are based on real PV output performance data collected from an experimental PV park, show the effects on the electricity market equilibrium outcome. Keywords: Electricity market equilibrium, Nodal prices, Photovoltaic power systems, Social welfare, Solar irradiance, Supply function equilibrium. 1. INTRODUCTION 1.1 Renewable Energy and Photovoltaic Technology The expected increase of the world population in accordance with the continuous economic growth of many countries has as a direct consequence an increase of energy demand. At present, most of the energy supply is directly acquired using fossil fuel technologies, which are now reaching their limits in supply and source, while their usage has serious consequences on the environment. Steps for improvement have been undertaken, especially from the European Union (EU), for the development and large-scale diffusion of a range of new and more sustainable technologies. A number of targets have been set for the integration of new energy technologies, with an important step being the commitment of the EU Member States to cover 20% of the total energy needs by utilizing Renewable Energy Sources (RES) by 2020; see Commission of the European Communities (2008). One of the most attractive and potential sources of energy considered to be able to meet the future energy needs is the sun. Installations of PV cells and modules around the world have seen a rapid growth in the past years at an average annual rate of more than 35%. According to the Greenpeace and EPIA (2008) scenario, if adequate support mechanisms are adopted to make solar electricity competitive and serious commitment is made to energy efficiency, the solar power produced globally will satisfy the electric needs of almost 14% of the world’s population by 2030. The most effective market support mechanism for PV systems has been the introduction of feed-in laws, which helps to diminish the differences between the high PV installation costs and the operational costs of conventional generators. These laws oblige the system operator to purchase the power generated by the PV units at a predetermined feed- in tariff for a specified period of time (generally 20 years), giving motivation for further expansion of the PV-based power market; see Greenpeace and EPIA (2008). 1.2 Electricity Market Analysis The electricity market analysis in this paper utilizes the bid- based pool market theory, which is based on the principle of centralized power dispatch. All market participants, mainly strategic generating firms, submit price-quantity bids to the pool specifying the amount of power that they are willing to trade. Once the bidding process for one time-interval is closed, the Independent System Operator (ISO) supervising the pool computes the equilibrium point between supply and demand to obtain the market clearing price in terms of nodal prices based on a social welfare maximization procedure, while the strategic actions of the profit-maximizing generating firms are taken into account.