Abstract—Efficient management during the operational phase of district energy systems has become increasingly complex due to the various static and dynamic factors involved. Existing deterministic algorithms which are largely based on human experience acquired from specific domains, normally fail to consider the overall efficiency of district energy systems in a holistic way. This paper looks into taking a black box approach by using genetic algorithms (GA) to solve a multiobjectiveoptimization problem conforming to economic, environmental and efficiency standards. This holistic optimization model, takes into account both heat and electricity demand profiles, and was applied in Ebbw Vale district, in Wales. The model helps compute optimized daily schedules for the generation mix in the district and different operational strategies are analyzed using deterministic and genetic algorithm (GA) based combined optimization methods. The results evidence that GA can be used to define an optimum strategy behind heat production leading to an increase in profit by 32% and reduction in CO 2 emissions by 36% in the 24 hour period analyzed. This research fits in well with future district energy systems which give priority to integrated and systematic management. Index Terms—Analytical model, district energy management, energy efficiency, genetic algorithms, multiobjective optimization. I. INTRODUCTION Energy systems in the 21st century are required to meet several important goals towards sustainable development including economic, environmental, and social aspects. A systemic approach needs to be taken to derive feasible integrated solutions to solve complex energy problems [1] as they involve multiple goals, many stakeholders and numerous technologies. Global energy production is increasing at a rate which is more than capable of meeting the rising energy demand [2], however, the rapid growth of CO 2 emissions due to increasing energy production, needs to be dealt with. Energy demand reduction or increase in energy efficiency is vital to keep this rate down. Consequently, increased use of renewable energy has gained popularity in countries all around the world. In most cases, these renewable are integrated into the generation mix along with conventional sources of energy. Although there have been Manuscript received October 20, 2015; revised May 1, 2016. This work was supported in part by EU FP7 Project RESILIENT and also by BRE institute of sustainability of Cardiff University. The authors are with the School of Engineering, Cardiff University, the Parade, Cardiff, CF24 3AA, UK (e-mail: jayanb@Cardiff.ac.uk, lih@Cardiff.ac.uk, rezguiy@Cardiff.ac.uk, hippolytej@Cardiff.ac.uk, howellsk5@Cardiff.ac.uk). advancements in individual systems, it is also important to be able to increase the overall efficiency, when these systems work together. Learning to manage this pool of resources together, therefore, needs to be given importance. Decentralized systems at a smaller scale are becoming a feasible choice [1]. They can be used as an alternative or an additional energy supply to the main grid. These include co-generation technologies such as combined heat and power (CHP), using biomass power, solar PV power, wind power…etc. at a local or regional level. Out of these, district heating and cooling systems (DHC) are increasingly being used today [3]. They produce steam and hot/chilled water in a central plant and distribute this to individual buildings (residential and commercial), in its vicinity, through a network of pipelines. They usually tend to be an interesting choice for energy supply in hospitals, industrial parks, office complexes, large campuses (universities), housing estates or small districtswhich can also have a mix of the above buildings. They are known to save energy, consumer space and inhibit air-pollution [4]. DHC systems which use CHP are increasingly being a popular choice not just in Europe, but in many other countries such as United States, China, Russia and India. It is very effective in reducing greenhouse gas emissions (GHG), and increasing economic benefits [5], [6]. DHC networks are also a long-term asset according to the International Energy Agency, as they are a bridge towards the future low carbon energy technologies. For example, they are capable of taking heat from any source including renewable heat sources, hence offering flexibility to integrate new low carbon sources when made available in the future [6]. The development of District Energy Systems – in particular Renewable Energy Sources (RES) – requires new business and technology platforms to manage the increased level of complexity and diversity of global energy management. Intelligent management of these systems is crucial to ensure they are operated at the highest efficiency which takes into account costs, emissions level, and matching demand with supply. The existing studies for district energy systems optimization largely focus on the planning (design) stage. Very few cases look into the optimization during operational phases, e.g. optimizing operational parameters [7]-[11]. This is due to several factors, including: (1) the integration of renewables and the use of co-generation plants in today’s energy mix make the problem more dynamic, uncertain and complex; and (2) many different constraints have to be factored in at each stage of the optimization, and require high computational power to provide near real time results. These are the main challenges that need to be addressed in order to An Analytical Optimization Model for Holistic Multiobjective District Energy Management  A Case Study Approach Mr. Bejay Jayan, Haijiang Li, Yacine Rezgui, Jean-Laurent Hippolyte, and Shaun Howell 156 International Journal of Modeling and Optimization, Vol. 6, No. 3, June 2016 DOI: 10.7763/IJMO.2016.V6.521