Bi-level Optimisation of Distributed Energy Systems Incorporating Non-linear Power Flow Constraints

This paper presents a bi-level optimisation process for the design and operation of a distributed energy system taking into account non-linear electrical grid constraints. It includes the optimal selection of various distributed energy resources (micro combined heat and power, photovoltaic, air source heat pump, gas boiler and heat storage) and the optimal operation of the selected resources at the neighbourhood level. The objective is to explore the tradeoff between cost and carbon emissions over the lifespan of the selected resources while satisfying the heat and electrical demands of the buildings as well as avoiding the violation of existing electrical grid constraints. This is accomplished by using two optimisation “levels” within one optimisation process. The main level uses a multi-objective genetic algorithm (GA) to optimise a set of design variables (capacities of technologies in each building). The evaluation of each candidate solution of the GA has two steps. First, the optimal operation of all distributed energy resources is determined using the energy hub approach (a mixed integer linear programming model); the results are passed back to the main level where they are summed to give the objective function value. This is followed by a non-linear power flow calculation to check if the proposed operation violates existing electrical grid constraints. The optimisation framework is applied to a case study consisting of several buildings at the low voltage distribution network level. The optimal design and operation of distributed energy system is determined. The impact of the existing electrical grid in limiting integration of distributed energy resources is shown to be highly significant. The effect on the solutions proposed and how limitations can be decreased are also discussed.