Regional energy planning based on distribution grid hosting capacity

Matteo Moncecchi; Davide Falabretti; Marco Merlo; Matteo Moncecchi; Davide Falabretti; Marco Merlo

doi:10.3934/energy.2019.3.264

AIMS Energy

2019, Volume 7, Issue 3: 264-284. doi: 10.3934/energy.2019.3.264

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Research article Topical Sections

Regional energy planning based on distribution grid hosting capacity

Energy Department, Politecnico di Milano, Italy

Received: 26 February 2019 Accepted: 14 May 2019 Published: 29 May 2019

In a liberalized energy market, policymakers cannot over-impose the deployment of new distributed generators, either in terms of location or in terms of size/technology; on the opposite, they are asked to promote incentives, penalties or constraints in order to foster a generation portfolio evolution fitting with the energy need of the loads.
In the paper, given a local distribution grid, a two-step procedure is proposed to define the most effective energy policy, willing to drive a proper evolution of the generation portfolio, i.e., to maximize the renewable sources exploitation taking into account the grid constraints. The approach proposed is based on a stochastic (Monte Carlo) procedure. Given a generation portfolio, many scenarios are evaluated, changing generators’ nominal power, point of common coupling and also a slightly different technologies share. Actually, the final goal of the procedure proposed is to simulate the stochastic behavior of users with respect to the regional energy policy (i.e., to perform a multi-dimensional sensitivity analysis) in order to validate the proposed generation portfolio.
In particular, in the first step of the procedure, it is defined a portfolio in which generators are aggregated with respect to the power plant technology (PV, wind, small hydro, big hydro, etc.). Such a portfolio is optimized in order to maximize the matching between local production and local consumption. In the second step, a Monte Carlo simulation is implemented to stochastically take into account a significant number of possible configurations of each portfolio (number of generators, unit size, location, etc.). Given the generator’s distribution, a probability index based on a Hosting Capacity concept is proposed as a performance index. Conductors’ thermal limits and slow voltage variations on the electrical network are evaluated for several generator’s distributions and for different dispersed generation penetrations. The final goal of the approach proposed is to define the optimal local generation portfolio fitting both with the load profiles and with the bounds of the distribution grid already in place. Such an output resulted to be a valuable piece of information for decisionmakers in order to properly promote regional energy planning policies.
In order to validate the approach and demonstrate its capabilities, the procedure proposed has been applied to the real medium voltage distribution grid relevant to the Italian city of Aosta, i.e., real-life topologies, renewable-based generation and load fluctuation have been simulated.
- energy planning,
- renewable integration,
- distribution grid,
- dispersed generation,
- Hosting Capacity
Citation: Matteo Moncecchi, Davide Falabretti, Marco Merlo. Regional energy planning based on distribution grid hosting capacity[J]. AIMS Energy, 2019, 7(3): 264-284. doi: 10.3934/energy.2019.3.264

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Abstract

In a liberalized energy market, policymakers cannot over-impose the deployment of new distributed generators, either in terms of location or in terms of size/technology; on the opposite, they are asked to promote incentives, penalties or constraints in order to foster a generation portfolio evolution fitting with the energy need of the loads.
In the paper, given a local distribution grid, a two-step procedure is proposed to define the most effective energy policy, willing to drive a proper evolution of the generation portfolio, i.e., to maximize the renewable sources exploitation taking into account the grid constraints. The approach proposed is based on a stochastic (Monte Carlo) procedure. Given a generation portfolio, many scenarios are evaluated, changing generators’ nominal power, point of common coupling and also a slightly different technologies share. Actually, the final goal of the procedure proposed is to simulate the stochastic behavior of users with respect to the regional energy policy (i.e., to perform a multi-dimensional sensitivity analysis) in order to validate the proposed generation portfolio.
In particular, in the first step of the procedure, it is defined a portfolio in which generators are aggregated with respect to the power plant technology (PV, wind, small hydro, big hydro, etc.). Such a portfolio is optimized in order to maximize the matching between local production and local consumption. In the second step, a Monte Carlo simulation is implemented to stochastically take into account a significant number of possible configurations of each portfolio (number of generators, unit size, location, etc.). Given the generator’s distribution, a probability index based on a Hosting Capacity concept is proposed as a performance index. Conductors’ thermal limits and slow voltage variations on the electrical network are evaluated for several generator’s distributions and for different dispersed generation penetrations. The final goal of the approach proposed is to define the optimal local generation portfolio fitting both with the load profiles and with the bounds of the distribution grid already in place. Such an output resulted to be a valuable piece of information for decisionmakers in order to properly promote regional energy planning policies.
In order to validate the approach and demonstrate its capabilities, the procedure proposed has been applied to the real medium voltage distribution grid relevant to the Italian city of Aosta, i.e., real-life topologies, renewable-based generation and load fluctuation have been simulated.

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