Cascade computing model to optimize energy exchanges in prosumer communities

Abstract

Recently, the increasing availability of renewable energy plants has changed the market of electrical energy. The concept of energy community enables prosumers to exploit and exchange the energy produced locally and reduce the need for external energy sources. This can help to obtain significant cost savings and increase the percentage of green energy. In this paper, we present the Cascade model, which aims to achieve a twofold goal: compute an energy schedule that satisfies the needs of single prosumers, and maximize the energy sharing at the community level, thus minimizing the overall cost. The Cascade model partitions the prosumers in groups: at each step, an optimization problem is solved for all the users of a group. The solution enables defining a super-user that summarizes the energy requirements of the groups considered before. Then, a new group is considered in the next step, and so on, until all the groups have been processed. This approach enables preventing the exponential increase in computing complexity that is inevitable when all the prosumers are considered together, using the model referred to as Unified. Experimental results show that the Cascade model leads to a great reduction of computing time, while the overall cost closely approximates the optimal solution ensured by the Unified model.

Quantum Computing Approach for Energy Optimization in a Prosumer Community

“…The model exploits a unique MILP problem for all the prosumers, and solves it through the Branch and Bound algorithm, which provides the optimal solution for sharing energy at the community level. In the Cascade model, discussed in [27], the overall solution is obtained by iterating a number of MILP problems, solved sequentially.…”

Evolving Concept of Energy Communities in the European Union

“…This can lead to significant cost savings and increase the percentage of green energy [16], as well as provide an opportunity for alternative energy system organisation and management methods in the future: smart energy transmission, distribution and metering [17], [18], digital twinning, introduction of green energy sources, for example, gases, in conventional energy distribution and transmission networks [19]- [22]. In future, it could also help minimise impact of energy delivery disruptions during local energy crisis that could occur in practically every centralised and extended energy delivery network [23].…”

Motives for the Use of Photovoltaic Installations in Poland against the Background of the Share of Solar Energy in the Structure of Energy Resources in the Developing Economies of Central and Eastern Europe

“…In the literature on the use of photovoltaics, there are several technological topics [65], which are focused on issues related to energy transmission and storage [66,67] and optimizing its use [68][69][70]. Much space is also devoted to modern energy trading systems [71,72], including those that use artificial intelligence. The described considerations are most often in the form of analyses conducted on a macroscale, relating to the entire sector.…”