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This paper construct a CCHP and renewable energy based hybrid energy system driven by distributed energy resources (DERs CCHP). Then, the paper constructs performance indexes from energy, economic and environment. Thirdly, the paper proposes a multi-objective optimization model for DERs CCHP system under four optimization of energy rate (ER), total operation cost (TOC), carbon dioxide emission reductions (CER) and joint optimization. Finally, Guangzhou Higher Education Mega Center (GHEMC) in China is taken as the object for comparatively analyzing the operation performance of DERs CCHP system and CCHP system driven by natural gas (NG CCHP system). Results show: Joint optimization mode could balance the results of different optimization modes. DERs CCHP system shows better operation performance. ER of ER optimization, CER optimization and joint optimization are higher than that of NG CCHP system. NPV of all optimization modes is positive, IRR are bigger than the expected yield rate. DERs CCHP system could reduce CO 2 emission by utilizing wind energy and solar energy to replace NG. The sensitivity analysis indicates the performance of the DERs CCHP system will become better with the increase of chiller COP, decrease of NG price and wind-photovoltaic equipment cost. [ABSTRACT FROM AUTHOR]

A Coarse-Grained Parallel Genetic Algorithm (CGPGA) is utilized to search for near-optimal solutions for land use allocation optimization problems in the context of multiple objectives and constraints. Plans are obtained based on the trade-off among three spatial objectives including ecological benefit, accessibility and compatibility. The Multi-objective Optimization of Land Use model integrates these objectives with the fitness function assessed by reference point method (goal programming). The CGPGA, as the first coupling in land use allocation optimization problems, is tested through the experiments with one processor, two processors and four processors to pursue near-optimal land use allocation scenarios and the comparison to these experiments based on Generic Genetic Algorithm (GGA), which clearly shows the robustness of the model we proposed as well as its better performance. Furthermore, the successful convergent (near-convergent) case study utilizing the CGPGA in Tongzhou Newtown, Beijing, China evinces the capability and potential of CGPGA in solving land use allocation optimization problems with better efficiency and effectiveness than GGA. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a simplified energy performance assessment method for existing buildings in cooling season, which is based on energy bill disaggregation and energy performance analysis. This method requests very limited building energy data and can effectively assess the energy performance at building and system levels, and disaggregate the whole-building consumption into consumptions of three groups of end-uses. This method is based on two basic energy balance principles, i.e., the electricity consumption balances at building level and the cooling energy balances between demand side and supply side of HVAC systems. An optimization algorithm is developed to establish best possible cooling energy balances by minimizing the balance residuals and therefore to disaggregate the energy consumption of different users. The performance of the proposed method was validated in two existing buildings in Hong Kong and Beijing. The results, including the disaggregated energy consumptions and the key energy performance indicators of HVAC system, agreed well with the “measured” data in mechanical cooling months. [Copyright &y& Elsevier]