We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically modeled to find the optimal operation conditions and illustrated with physical interpretation of how to achieve optimal energy management in the cooperative multi-microgrid community. This global electric energy optimization of the cooperative community is realized by the ancillary internal trading between the microgrids in the cooperative community which reduces the extra cost from unnecessary external trading by adjusting the electric energy production amounts of combined heat and power (CHP) generators and amounts of both internal and external electric energy trading of the cooperative community. A simulation study is also conducted to validate the proposed mathematical energy management models.

In this paper, an optimal energy management strategy for a cooperative multi-microgrid system with combined cooling, heat and power (CCHP) is proposed and has been verified for a test case of building microgrids (BMGs). Three different demand types of buildings are considered and the BMGs are assumed to be equipped with their own combined heat and power (CHP) generators. In addition, the BMGs are also connected to an external energy network (EEN), which contains a large CHP, an adsorption chiller (ADC), a thermal storage tank, and an electric heat pump (EHP). By trading the excess electricity and heat energy with the utility grid and EEN, each BMG can fulfill its energy demands. Seasonal energy demand variations have been evaluated by selecting a representative day for the two extreme seasons (summer and winter) of the year, among the real profiles of year-round data on electricity, heating, and cooling usage of all the three selected buildings. Especially, the thermal energy management aspect is emphasized where, bi-lateral heat trading between the energy supplier and the consumers, so-called energy prosumer concept, has been realized. An optimization model based on mixed integer linear programming has been developed for minimizing the daily operation cost of the EEN while fulfilling the energy demands of the BMGs. Simulation results have demonstrated the effectiveness of the proposed strategy.

In order to ensure high crop yield and good quality in greenhouse horticulture, the major environment control variables, such as temperature, humidity, and CO₂ concentration, etc., need to be controlled properly, in order to reduce harmful effects on crop growth by minimizing the fluctuation of the thermal condition. Even though a hot water-based heating system is evidently superior to a hot air-based heating system, in terms of the thermally stable condition or energy saving, a hot air-based heating system has occupied the domestic market due to its economic efficiency from an initial investment cost saving. However, the intrinsic drawbacks of a hot air-based heating system, being more frequent variation of thermal variables and an inordinate disturbance on crops due to its convective heat delivery nature, are believed to be the main reasons for the insufficient crop yield and/or the quality deterioration. In addition, the current thermal environment monitoring system in a greenhouse, in which a sole sensor node usually covers a large part of cultivating area, seems to have a profound need of improvement in order to resolve those problems, in that the assumption of thermal uniform condition, which is adequate for a sole sensor node system, cannot be ensured in some cases. In this study, the qualitative concept of the new control variable—the degree of uniformity—is suggested as an indicator to seek ways of enhancing the crop yield and its quality based on the multiple sensor nodes system with a wireless sensor network. In contrast to a conventional monitoring system, for which a newly suggested concept of qualitative variable cannot be estimated at all, the multiple sensor nodes-based thermal monitoring system can provide more accurate and precise sensing, which enables the degree of uniformity to be checked in real-time and thus more precise control becomes possible as a consequence. From the analysis of the results of the experiment and simulation, it is found that the crops in plastic vinyl houses can be exposed to a serious level of non-uniform thermal condition. For instance, the temperature difference in the longitudinal and widthwise direction is 3.0 °C and 6.5 °C, respectively for the case of 75 × 8 m dimension greenhouse during a typical winter season, and it can be hypothesized that this level of non-uniformity might cause considerable damage to crop growth. In this paper, several variants of control systems, within the framework of the multiple sensor nodes system, is proposed to provide a more thermally-stable cultivating environment and the experimental verification is carried out for different scales of test greenhouses. The results showed that a simple change of heating mode (i.e., from a hot air- to a hot water-based heating system) can bring about a significant improvement for the non-uniformity of temperature (more or less 80%), and an additional countermeasure, with local heat flux control, can lead to a supplementary cut of non-uniformity up to 90%. Among the several variants of local heat flux control systems, the hydraulic proportional mass flow control valve system was proven to represent the best performance, and it can be hypothesized that the newly suggested qualitative variable—the degree of uniformity—with the multiple sensor nodes system can be a good alternative for seeking enhanced cultivating performance, being higher crop yield and better quality along with energy cost saving.

A decision-support tool based on relational database technology is developed to aid the planning of energy supply systems for urban communities. The building-load models derived from the data measured or surveyed in Korea over the last two decades are computerized using Microsoft Access® as an application platform. The tool calculates energy demands for arbitrary combinations of buildings in an urban community without requiring detailed technological information. Nonexpert urban planners can use the package by providing simple input parameters such as floor area, building type, and city where the site is located. The program calculates the time series based on the demands for electricity, heating, cooling, and hot water loads for the 8760 hours of a year. It also produces indicative characteristics of each load type such as the annual maximums, trends of the daily maximums and minimums, and the annual sums of energy. Urban planners can use these characteristics of the load profiles in their decision processes at the early stages of planning. The detailed time series can be further exploited for subsequent analysis, such as device operational simulation or cost estimation if more sophisticated analysis is necessary. A case study for an actual project is presented for demonstrational purposes.

In this paper, an optimal energy management scheme for islanded building microgrid networks is proposed. The proposed building microgrid network comprises of several inter-connected building microgrids (BMGs) and an external energy supplier. Each BMG has a local combined heat and power (CHP) unit, energy storage, renewables and loads (electric and thermal). The external energy system comprises of an external CHP unit, chillers, electric heat pumps and heat pile line, for thermal energy storage. The BMGs can trade energy with other BMGs of the network and can also trade energy with the external energy supplier. In order to efficiently utilize the components of the BMGs and the network, the concept of adjustable power is adopted in this study. Adjustable power can reduce the operation cost of the network by increasing/decreasing the power of dispatchable units. In addition, the failure/recovery of components in the BMGs and the external system are also considered to analyze the performance of the proposed operation method. In order to optimally utilize the available resources during events, precedence among loads of BMGs and the external energy supplier is considered. Simulation results have proved the applicability of the proposed method for both normal islanded mode and with outage/recovery of equipment during the operation horizon. Finally, sensitivity analysis is carried out to analyze the impact of change in components’ parameters values on the saved cost of the network.