Abstract
This paper proposes a heuristic method for calculating the capacity of a set of residential photovoltaic-battery systems in providing upward flexibility services to the grid in an energy communities framework. The proposed method has been designed to calculate the upward service capacity in a few minutes, assuming a scenario where the grid operator urgently needs an upward service in a specific area. The proposed method calculates the service capacity by exploiting the PV overgeneration and the state of charge of batteries, adopting a distributed approach. If the service capacity varies relevantly over time, a centralized approach is considered allowing the service capacity to remain constant over time. An algorithm is provided that implements the proposed heuristic method that can be easily translated into a software code and solved even in the absence of specific skills and expensive high-level computational tools, i.e. using cost-effective single-board computers. The main benefits and advantages of the proposed method are due to its applicability in real-time problems and to its simplicity which makes it easy to be translated into software code and solved even in the absence of specific skills and high-level computational tools. Therefore, it is a simple and advantageous solution, especially for small energy communities. The numerical results demonstrate the effectiveness of the proposed method and algorithm, studying a set of four residential photovoltaic-battery systems and real input data. For this test case, the algorithm returns a flat service capacity of approximately 8 kW which remains perfectly constant for 1-hour. Lastly, the performance of the proposed heuristic method is compared with the solution of two optimization problems aiming at the same scope.
Highlights
The Clean Energy Package (CEP), in its initial proposal in 2016 and its latest version in 2019, introduces energy communities (ENCOs) into the European legislation; it follows the definition of ‘‘Renewable Energy Community’’ (REC) in the 2018/2001/EU directive on the promotion of the use of energy from renewable sources and the definition of ‘‘Citizen Energy Community’’ (CEC) in 2019/944/EU directive on common rules for the internal electricity market. Both types of energy communities, REC and CEC, are similar there are significant differences; for example, members of a REC must be located in the proximity of the renewable energy projects that are owned/developed by the REC itself but this constraint does not apply to CECs
This paper focuses on a small ENCO, the proposed algorithm is feasible for large communities, with hundreds and hundreds of residential PV-BESS; this is because all the steps that comprise the proposed algorithm are very easy to calculate even in the presence of so many residential photovoltaic-battery systems
The efficiency of the proposed method as a valid and feasible solution for technical-practical issues even for small energy communities was tested through numerical experiments; the test case is a set of four residential photovoltaic-batteries systems together with their real 3-minute profiles captured at meters
Summary
The Clean Energy Package (CEP), in its initial proposal in 2016 (the so-called Winter Package) and its latest version in 2019, introduces energy communities (ENCOs) into the European legislation; it follows the definition of ‘‘Renewable Energy Community’’ (REC) in the 2018/2001/EU directive on the promotion of the use of energy from renewable sources and the definition of ‘‘Citizen Energy Community’’ (CEC) in 2019/944/EU directive on common rules for the internal electricity market. ECs tend to be local communities; this is because the better adaptation to the legal and regulatory frameworks [9] and the ecosystems diversity [10], the better management of the energy needs and energy consumption as in the case of an urban neighbourhood [11] or a municipality [12], [13]
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