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The purpose of this paper is to optimally operate a Smart Microgrid which is interconnected to the main grid so as to minimize expenditures associated with CO₂ emissions. Microgrids could come into play to aid the network through CO₂ emission reduction while increasing their efficiency through local generation. For this purpose, a Smart Microgrid incorporating Distributed Energy Resources (DER), especially Renewable Energy Sources (RES), is operated optimally while keeping the CO₂ emissions in check in order to minimize the financial burden from emissions stemming from the carbon tax. Since the network is assumed to be interconnected with the main grid, there is a consideration of the expected emissions associated with the imported energy.

An economic/environmental dispatch problem is mathematically formulated using an objective function and the constraints that it is subject to. The methodology is applied on a typical 17-bus test distribution network, representing a Hellenic LV network. Various carbon tax rates and their impact on the system marginal price are examined, in terms of their effect on distributed generation (DG) and as a second step, the effect of imposing lower carbon tax rates for micro-sources with the goal of benefitting from their more eco-friendly generation capabilities. In order to assess that benefit, hourly grid emissions coefficients are derived based on actual grid data.

The CO₂ tax refund policy towards the DG owners can lead to optimal coverage of consumers, optimal financial result both for the DG owners and the operator and greater DG integration within the smart grid.

Greater DG integration within the smart grid by using a CO₂ tax refund policy.

The purpose of this paper is to examine the feasibility of an ideal power network that combines many different renewable energy technologies such as wind power, concentrated solar power (CSP) and hydroelectric power. This paper emphasizes in finding the benefits arising from hydrothermal coordination compared to the non-regulated integration of the hydroelectric units, as well as the benefits from the integration of wind power and CSP.

Artificial Neural Networks were used to estimate wind power output. As for the CSP system, a three-tier architecture which includes a solar field, a transmission-storage system and a production unit was used. Each one of those separate sections is analyzed and the process is modeled. As for the hydroelectric plant, the knowledge of the water’s flow rated has helped estimating the power output, taking into account the technical restrictions and losses during transmission. Also, the economic dispatch problem was solved by using artificial intelligence methods.

Hydrothermal coordination leads to greater thermal participation reduction and cost reduction than a non-regulated integration of the hydrothermal unit. The latter is independent from the degree of integration of the other renewable sources (wind power, CSP).

Hydrothermal coordination in a power system which includes thermal units and CSP for cost and emissions reduction.